AMT - Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm

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name="citation_fulltext_world_readable" content=""> <meta name="citation_publisher" content="Copernicus GmbH"/> <meta name="citation_title" content="Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm"/> <meta name="citation_abstract" content="<p><strong class="journal-contentHeaderColor">Abstract.</strong> We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (<span class="inline-formula">XCO<sub>2</sub></span>) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (<span class="inline-formula">XCH<sub>4</sub></span>; full-physics and proxy product), water vapour (<span class="inline-formula">XH<sub>2</sub>O</span>) and the relative ratio of semi-heavy water (<span class="inline-formula">HDO</span>) to water vapour (<span class="inline-formula"><i>δ</i>D</span>). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (<span class="inline-formula">XCO</span>) and nitrous oxide (<span class="inline-formula">XN<sub>2</sub>O</span>) for which we also show first results. We also present an update on <span class="inline-formula">XCO<sub>2</sub></span> from both instruments.</p> <p>For <span class="inline-formula">XCO<sub>2</sub></span>, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties.</p> <p>With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average <span class="inline-formula">XN<sub>2</sub>O</span> product. Global <span class="inline-formula">XN<sub>2</sub>O</span> maps show a gradient from the tropics to higher latitudes on the order of 15 <span class="inline-formula">ppb</span>, which can be explained by variations in tropopause height. The new GOSAT-2 <span class="inline-formula">XN<sub>2</sub>O</span> product compares well with TCCON. Its station-to-station variability is lower than 2 <span class="inline-formula">ppb</span>, which is about the magnitude of the typical <span class="inline-formula">N<sub>2</sub>O</span> variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average <span class="inline-formula">XN<sub>2</sub>O</span> are on the order of 8 <span class="inline-formula">ppb</span> peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few <span class="inline-formula">XN<sub>2</sub>O</span> measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context.</p>"/> <meta name="citation_publication_date" content="2022/06/09"/> <meta name="citation_online_date" content="2022/06/09"/> <meta name="citation_journal_title" content="Atmospheric Measurement Techniques"/> <meta name="citation_volume" content="15"/> <meta name="citation_issue" content="11"/> <meta name="citation_issn" content="1867-1381"/> <meta name="citation_doi" content="https://doi.org/10.5194/amt-15-3401-2022"/> <meta name="citation_firstpage" content="3401"/> <meta name="citation_lastpage" content="3437"/> <meta name="citation_author" content="Noël, Stefan"/> <meta name="citation_author_institution" content="Institute of Environmental Physics, University of Bremen, FB 1, P.O. 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Tech., 6, 1533–1547, https://doi.org/10.5194/amt-6-1533-2013, 2013. a, b"> <meta name="citation_funding_source" content="citation_funder=Japan Aerospace Exploration Agency;citation_funder_id=501100004020;citation_grant_number=19RT000692"> <meta name="citation_funding_source" content="citation_funder=Japan Aerospace Exploration Agency;citation_funder_id=501100004020;citation_grant_number=JX-PSPC-527269"> <meta name="citation_funding_source" content="citation_funder=European Organization for the Exploitation of Meteorological Satellites;citation_funder_id=501100010560;citation_grant_number=EUM/CO/19/4600002372/RL"> <meta name="citation_funding_source" content="citation_funder=European Space Agency;citation_funder_id=501100000844;citation_grant_number=4000126450/19/I-NB"> <meta name="citation_pdf_url" content="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.pdf"/> <meta name="citation_xml_url" content="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.xml"/> <meta name="fulltext_pdf" content="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.pdf"/> <meta name="citation_language" content="English"/> <meta name="libraryUrl" content="https://amt.copernicus.org/articles/"/> <meta property="og:image" content="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-avatar-web.png"/> <meta property="og:title" content="Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm"> <meta property="og:description" content="Abstract. We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (XCO2) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (XCH4; full-physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments. For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are on the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few XN2O measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context."> <meta property="og:url" content="https://amt.copernicus.org/articles/15/3401/2022/"> <meta property="twitter:image" content="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-avatar-web.png"/> <meta name="twitter:card" content="summary_large_image"> <meta name="twitter:title" content="Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm"> <meta name="twitter:description" content="Abstract. We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (XCO2) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (XCH4; full-physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments. For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are on the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. 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} #templateSearchLoadingModal .co_LoadingDotsContainer .text { text-align: center; font-weight: bold; padding-bottom: 1rem; } #templateSearchLoadingModal .co_LoadingDotsContainer .dot { background-color: #0072BC; border: 2px solid white; border-radius: 50%; float: left; height: 2rem; width: 2rem; margin: 0 5px; -webkit-transform: scale(0); transform: scale(0); -webkit-animation: animation_dots_breath 1000ms ease infinite 0ms; animation: animation_dots_breath 1000ms ease infinite 0ms; } #templateSearchLoadingModal .co_LoadingDotsContainer .dot:nth-child(2) { -webkit-animation: animation_dots_breath 1000ms ease infinite 300ms; animation: animation_dots_breath 1000ms ease infinite 300ms; } #templateSearchLoadingModal .co_LoadingDotsContainer .dot:nth-child(3) { -webkit-animation: animation_dots_breath 1000ms ease infinite 600ms; animation: animation_dots_breath 1000ms ease infinite 600ms; } #templateSearchResultModal [class*="grid-"] { padding-left: 10px !important; padding-right: 10px !important; } #templateSearchResultTerm { font-weight: bold; } #resultsSearchHeader { display: block !important; } #scrolltopmodal { font-size: 3.0em; margin-top: 0 !important; margin-right: 15px; } @-webkit-keyframes animation_dots_breath { 50% { -webkit-transform: scale(1); transform: scale(1); opacity: 1; } 100% { opacity: 0; } } @keyframes animation_dots_breath { 50% { -webkit-transform: scale(1); transform: scale(1); opacity: 1; } 100% { opacity: 0; } } @media (min-width: 768px) and (max-width: 991px) { #templateSearchResultModal .modal-dialog { max-width: 90%; } } </style> <script> if(document.querySelector('meta[name="global_moBaseURL"]').content == "https://meetingorganizer.copernicus.org/") FINDER_URL = document.querySelector('meta[name="global_moBaseURL"]').content.replace('meetingorganizer', 'finder-app')+"search/library.php"; else FINDER_URL = document.querySelector('meta[name="global_moBaseURL"]').content.replace('meetingorganizer', 'finder')+"search/library.php"; SEARCH_INPUT = document.getElementById('search_query_solr'); SEARCH_INPUT_MODAL = document.getElementById('search_query_modal'); searchRunning = false; offset = 20; INITIAL_OFFSET = 20; var MutationObserver = window.MutationObserver || window.WebKitMutationObserver || window.MozMutationObserver; const targetNodeSearchModal = document.getElementById("templateSearchResultModal"); const configSearchModal = { attributes: true, childList: true, subtree: true }; // Callback function to execute when mutations are observed const callbackSearchModal = (mutationList, observer) => { for (const mutation of mutationList) { if (mutation.type === "childList") { // console.log("A child node has been added or removed."); picturesGallery(); } else if (mutation.type === "attributes") { // console.log(`The ${mutation.attributeName} attribute was modified.`); } } }; // Create an observer instance linked to the callback function const observer = new MutationObserver(callbackSearchModal); // Start observing the target node for configured mutations observer.observe(targetNodeSearchModal, configSearchModal); function _addEventListener() { document.getElementById('search_query_solr').addEventListener('keypress', (e) => { if (e.key === 'Enter') _runSearch(); }); document.getElementById('start_site_search_solr').addEventListener('click', (e) => { _runSearch(); e.stopPropagation(); e.stopImmediatePropagation(); return false; }); $('#templateSearchResultModal').scroll(function() { if ($(this).scrollTop()) { $('#scrolltopmodal:hidden').stop(true, true).fadeIn().css("display","inline-block"); } else { $('#scrolltopmodal').stop(true, true).fadeOut(); } }); } function scrollModalTop() { $('#templateSearchResultModal').animate({ scrollTop: 0 }, 'slow'); // $('#templateSearchResultModal').scrollTop(0); } function picturesGallery() { $('body').off('click', '.paperlist-avatar img'); $('body').off('click', '#templateSearchResultContainer .paperlist-avatar img'); searchPaperListAvatar = []; searchPaperListAvatarThumb = []; search_pswpElement = document.querySelectorAll('.pswp')[0]; if (typeof search_gallery != "undefined") { search_gallery = null; } $('body').on('click', '#templateSearchResultContainer .paperlist-avatar img', function (e) { if(searchPaperListAvatarThumb.length === 0 && searchPaperListAvatar.length === 0) { $('#templateSearchResultContainer .paperlist-avatar img').each(function () { var webversion = $(this).attr('data-web'); var width = $(this).attr('data-width'); var height = $(this).attr('data-height'); var caption = $(this).attr('data-caption'); var figure = { src: webversion, w: width, h: height, title: caption }; searchPaperListAvatarThumb.push($(this)[0]); searchPaperListAvatar.push(figure); }); } var target = $(this); var index = $('#templateSearchResultContainer .paperlist-avatar img').index(target); var options = { showHideOpacity:false, bgOpacity:0.8, index:index, spacing:0.15, history: false, focus:false, getThumbBoundsFn: function(index) { var thumbnail = searchPaperListAvatarThumb[index]; var pageYScroll = window.pageYOffset || document.documentElement.scrollTop; var rect = thumbnail.getBoundingClientRect(); 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showError(-1); return false; } // httpRequest.timeout = 20000; // time in milliseconds httpRequest.withCredentials = false; httpRequest.ontimeout = (e) => { showError(-1, "result timeout"); searchRunning = false; }; httpRequest.onreadystatechange = function() { if (httpRequest.readyState === XMLHttpRequest.DONE) { searchRunning = false; if (httpRequest.status === 200) { let rs = JSON.parse(httpRequest.responseText); if(rs) { if(rs.isError) { showError(rs.errorCode, rs.errorMessage); } else { let html = rs.resultHTMLs; $("#modal_search_query").val(rs.term); $("#templateSearchResultTerm").html(rs.term); $("#templateSearchResultNr").html(rs.resultsNr); $("#templateRefineSearch").html(rs.filter); if(rs.filter == false) { console.log('filter empty'); $("#refineSearchModal").removeClass('d-block').addClass('d-none'); } if(rs.resultsNr==1) $("#templateSearchResultNrPlural").hide(); else $("#templateSearchResultNrPlural").show(); if(rs.resultsNr==0) { hideModal('templateSearchLoadingModal'); $("#templateSearchResultContainer").html(""); $("#templateSearchResultContainerEmpty").removeClass("d-none"); showModal('templateSearchResultModal'); } else { if((rs.resultsNr - offset)>0) { html = html + generateShowMoreButton(offset, term); } $("#templateSearchResultContainerEmpty").addClass("d-none"); if( offset == INITIAL_OFFSET) { hideModal('templateSearchLoadingModal'); $("#templateSearchResultContainer").html(html); showModal('templateSearchResultModal'); } else { $('#showMore').remove(); startHtml = $("#templateSearchResultContainer").html(); $("#templateSearchResultContainer").html(startHtml + html); } // prepareForPhotoSwipe(); } } } else { showError(-2, "invalid result"); } } else { showError(-3, "There was a problem with the request."); } } }; if(offset == INITIAL_OFFSET) { hideModal('templateSearchResultModal'); showModal('templateSearchLoadingModal'); } httpRequest.open("GET", FINDER_URL+"?project="+projectID+"&term="+encodeURI(term)+((offset>INITIAL_OFFSET)?("&offset="+(offset-INITIAL_OFFSET)) : "")); httpRequest.send(); searchRunning = true; } function _runSearch() { var projectID = document.querySelector('meta[name="global_projectID"]').content; var term = _searchTrimInput(SEARCH_INPUT.value); if(term.length > 0) { _sendAjax(projectID, term); } else { showError(2, 'Empty search term') } } function _searchTrimInput(str) { return str.replace(/^\s+|\s+$/gm, ''); } function run() { _addEventListener(); $('#templateSearchInfoBtn, #modalSearchInfoBtn').popover({ sanitize: false, html: true, content: $("#templateSearchInfo").html(), placement: "bottom", template: '<div class="popover" role="tooltip"><div class="arrow"></div><button class="m-1 float-right btn btn-sm btn-danger" id="templateSearchInfoClose"><i class="fas fa-times-circle"></i></button><h3 class="popover-header"></h3><div class="popover-body"></div></div>', title: "Search tips", }); $(document).click(function (e) { let t = $(e.target); let a = t && t.attr("data-toggle")!=="popover" && t.parent().attr("data-toggle")!=="popover"; let b = t && $(".popover").has(t).length===0; if(a && b) { $('#templateSearchInfoBtn').popover('hide'); $('#modalSearchInfoBtn').popover('hide'); } }); $('#templateSearchInfoBtn').on('shown.bs.popover', function () { $("#templateSearchInfoClose").click(function(e){ $('#templateSearchInfoBtn').popover('hide'); e.stopPropagation(); e.stopImmediatePropagation(); return false; }); }) $('#templateSearchResultModal').on('hidden.bs.modal', function(e) { $('body').off('click', '#templateSearchResultContainer .paperlist-avatar img'); var pswpElement = document.querySelectorAll('.pswp')[0]; var gallery = null; var paperListAvatar = []; var paperListAvatarThumb = []; $('.paperlist-avatar img').each(function(){ var webversion = $(this).attr('data-web'); var width = $(this).attr('data-width'); var height = $(this).attr('data-height'); var caption =$(this).attr('data-caption'); var figure = { src:webversion, w:width, h:height, title:caption }; paperListAvatarThumb.push($(this)[0]); paperListAvatar.push(figure); }); $('body').on('click', '.paperlist-avatar img', function (e) { if(paperListAvatarThumb.length === 0 && paperListAvatar.length === 0){ $('.paperlist-avatar img').each(function(){ var webversion = $(this).attr('data-web'); var width = $(this).attr('data-width'); var height = $(this).attr('data-height'); var caption =$(this).attr('data-caption'); var figure = { src:webversion, w:width, h:height, title:caption }; paperListAvatarThumb.push($(this)[0]); paperListAvatar.push(figure); }); } var target = $(this); var index = $('.paperlist-avatar img').index(target); var options = { showHideOpacity:true, bgOpacity:0.8, index:index, spacing:0.15, getThumbBoundsFn: function(index) { var thumbnail = paperListAvatarThumb[index]; var pageYScroll = window.pageYOffset || document.documentElement.scrollTop; var rect = thumbnail.getBoundingClientRect(); return {x:rect.left, y:rect.top + pageYScroll, w:rect.width}; } }; gallery = new PhotoSwipe( pswpElement, PhotoSwipeUI_Default,[paperListAvatar[index]],options); gallery.init(); }); }); $('#templateSearchResultModal').on('hide.bs.modal', function(e) { $("#templateRefineSearch").removeClass('d-block').addClass('d-none'); $("#refineSearchModalHide").removeClass('d-block').addClass('d-none'); $("#refineSearchModal").removeClass('d-none').addClass('d-block'); offset = INITIAL_OFFSET; }) $(document).on("click", "#showMore", function(e){ offset+=INITIAL_OFFSET; runSearchModal() e.stopPropagation(); e.stopImmediatePropagation(); return false; }); $(document).ready(function() { $(document).on("click", "#refineSearchModal", function (e) { $("#templateRefineSearch").removeClass('d-none').addClass('d-block'); $(this).removeClass('d-block').addClass('d-none'); $("#refineSearchModalHide").removeClass('d-none').addClass('d-block'); }); $(document).on("click", "#refineSearchModalHide", function (e) { $("#templateRefineSearch").removeClass('d-block').addClass('d-none'); $(this).removeClass('d-block').addClass('d-none'); $("#refineSearchModal").removeClass('d-none').addClass('d-block'); }); $(document).on("click", "#modal_start_site_search", function (e) { runSearchModal(); e.stopPropagation(); e.stopImmediatePropagation(); return false; }); }); } function runSearchModal() { var projectID = document.querySelector('meta[name="global_projectID"]').content; var queryString = $('#library-filters').serialize(); var term = _searchTrimInput($('#modal_search_query').val()); term+='&'+queryString; if(term.length > 0) { _sendAjax(projectID, term); } else { showError(2, 'Empty search term') } } if(document.getElementById('search_query_solr')) { run(); } </script> </div></div> </div> </div> </div> </div> </header>  <main class="one-column version-2023"> <div id="content" class="container"> <div id="page_content_container" class="CMSCONTAINER row"> <div class="col"> <div class="article"> <div id="top"></div> <div class="row no-gutters header-block mb-1 align-items-end"> <div class="col-12 col-xl-5"> <div class="row d-xl-none mb-3"> <div class="col-12" > <div class="d-none d-lg-block articleBackLink"> <a href="https://amt.copernicus.org/">Articles</a> | <a href="https://amt.copernicus.org/articles/15/issue11.html">Volume 15, issue 11</a> </div> <div class="tab co-angel-left d-md-none"></div> <div class="tab co-angel-right d-md-none"></div> <div class="mobile-citation"> <ul class="tab-navigation no-styling"> <li class="tab1.articlf active"><nobr><a href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.html">Article</a></nobr></li><li class="tab3.discussioo"><nobr><a href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-discussion.html">Peer review</a></nobr></li><li class="tab450.metrict"><nobr><a href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-metrics.html">Metrics</a></nobr></li><li class="tab500.relationt"><nobr><a href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-relations.html">Related articles</a></nobr></li> </ul> </div> </div> </div> <div class="d-lg-none"> <span class="articleBackLink"><a href="https://amt.copernicus.org/">Articles</a> | <a href="https://amt.copernicus.org/articles/15/issue11.html">Volume 15, issue 11</a> </span> <div class="citation-header" id="citation-content"> <div class="citation-doi">https://doi.org/10.5194/amt-15-3401-2022</div> <div class="citation-copyright">© Author(s) 2022. This work is distributed under <br class="hide-on-mobile hide-on-tablet" />the Creative Commons Attribution 4.0 License.</div> </div> </div> <div class="hide-on-mobile hide-on-tablet"> <div class="citation-header"> <div class="citation-doi">https://doi.org/10.5194/amt-15-3401-2022</div> <div class="citation-copyright">© Author(s) 2022. This work is distributed under <br class="hide-on-mobile hide-on-tablet" />the Creative Commons Attribution 4.0 License.</div> </div> </div> </div> <div class="col-7 d-none d-xl-block"> <div class="text-right articleBackLink"> <a href="https://amt.copernicus.org/">Articles</a> | <a href="https://amt.copernicus.org/articles/15/issue11.html">Volume 15, issue 11</a> </div> <div class="tab co-angel-left d-md-none"></div> <div class="tab co-angel-right d-md-none"></div> <div class="mobile-citation"> <ul class="tab-navigation no-styling"> <li class="tab1.articlf active"><nobr><a href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.html">Article</a></nobr></li><li class="tab3.discussioo"><nobr><a href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-discussion.html">Peer review</a></nobr></li><li class="tab450.metrict"><nobr><a href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-metrics.html">Metrics</a></nobr></li><li class="tab500.relationt"><nobr><a href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-relations.html">Related articles</a></nobr></li> </ul> </div> </div> </div> <div class="ms-type row no-gutters d-none d-lg-flex mb-1 mt-0 align-items-center"> <div class="col"> <div class="row no-gutters align-items-center"> <div class="col-auto"> Research article </div> <div class="col">  | <a target="_blank" href="https://creativecommons.org/licenses/by/4.0/" rel="license" class="licence-icon-svg"><img src="https://www.atmospheric-measurement-techniques.net/licenceSVG_16.svg"></a> </div> </div> </div> <div class="col-auto text-right">09 Jun 2022</div> </div> <div class="ms-type row no-gutters d-lg-none mb-1 align-items-center"> <div class="col-12"> Research article | <a target="_blank" href="https://creativecommons.org/licenses/by/4.0/" rel="license" class="licence-icon-svg "><img src="https://www.atmospheric-measurement-techniques.net/licenceSVG_16.svg"></a> | <span>09 Jun 2022</span> </div> </div> <a class="article-avatar hide-on-mobile hide-on-tablet" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-avatar-web.png" target="_blank"> <img border="0" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-avatar-thumb150.png" data-caption="© Author(s). Distributed under the Creative Commons Attribution 4.0 License." data-web="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-avatar-web.png" data-width="600" data-height="396"> </a> <h1>Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm</h1> <div class="auto-fixed-top-forced article-title"> <div class="grid-container show-on-fixed" style="display: none"> <div class="grid-85 mobile-grid-85 tablet-grid-85 grid-parent"> <span class="d-block hide-on-mobile hide-on-tablet journal-contentHeaderColor">Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm</span> <span class="d-block hide-on-desktop journal-contentHeaderColor">Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm</span> <span>Stefan Noël et al.</span> </div> <div class="grid-1 mobile-grid-15 tablet-grid-15 grid-parent text-right"> <a id="scrolltop" class="scrollto" href="https://amt.copernicus.org/articles/15/3401/2022/#top"><i class="co-home"></i> </a> </div> </div> </div> <div class="mb-3 authors-with-affiliations"> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804986">Stefan Noël<a href="mailto:stefan.noel@iup.physik.uni-bremen.de"><i class="fal fa-envelope ml-1"></i></a></span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804987">Maximilian Reuter</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804988">Michael Buchwitz</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804989">Jakob Borchardt</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804990">Michael Hilker</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804991">Oliver Schneising</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804992">Heinrich Bovensmann</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804993">John P. Burrows</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804994">Antonio Di Noia</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804995">Robert J. Parker</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804996">Hiroshi Suto</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804997">Yukio Yoshida</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804998">Matthias Buschmann</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author804999">Nicholas M. Deutscher</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805000">Dietrich G. Feist</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805001">David W. T. Griffith</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805002">Frank Hase</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805003">Rigel Kivi</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805004">Cheng Liu</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805005">Isamu Morino</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805006">Justus Notholt</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805007">Young-Suk Oh</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805008">Hirofumi Ohyama</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805009">Christof Petri</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805010">David F. Pollard</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805011">Markus Rettinger</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805012">Coleen Roehl</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805013">Constantina Rousogenous</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805014">Mahesh Kumar Sha</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805015">Kei Shiomi</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805016">Kimberly Strong</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805017">Ralf Sussmann</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805018">Yao Té</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805019">Voltaire A. Velazco</span>,</nobr> <nobr><span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805020">Mihalis Vrekoussis</span>,</nobr> <nobr>and <span class="hover-cursor-pointer journal-contentLinkColor hover-underline" data-toggle="modal" data-target=".author805021">Thorsten Warneke</span></nobr> </div> <div class="modal fade author804986" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Stefan Noël</h3> <div class="row no-gutters"> <div class="col-12">CORRESPONDING AUTHOR</div> <div class="col-12"><a href="mailto:stefan.noel@iup.physik.uni-bremen.de"><i class="fal fa-envelope mr-2"></i>stefan.noel@iup.physik.uni-bremen.de</a></div> </div> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0002-5216-9110" data-title="https://orcid.org/0000-0002-5216-9110"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0002-5216-9110</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804987" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Maximilian Reuter</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0001-9141-3895" data-title="https://orcid.org/0000-0001-9141-3895"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0001-9141-3895</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804988" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Michael Buchwitz</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0001-7616-1837" data-title="https://orcid.org/0000-0001-7616-1837"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0001-7616-1837</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804989" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Jakob Borchardt</h3> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804990" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Michael Hilker</h3> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804991" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Oliver Schneising</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0003-1725-8246" data-title="https://orcid.org/0000-0003-1725-8246"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0003-1725-8246</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804992" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Heinrich Bovensmann</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0001-8882-4108" data-title="https://orcid.org/0000-0001-8882-4108"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0001-8882-4108</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804993" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">John P. Burrows</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0003-1547-8130" data-title="https://orcid.org/0000-0003-1547-8130"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0003-1547-8130</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804994" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Antonio Di Noia</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0002-5052-0763" data-title="https://orcid.org/0000-0002-5052-0763"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0002-5052-0763</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Earth Observation Science, University of Leicester, LE1 7RH, Leicester, UK </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804995" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Robert J. Parker</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0002-0801-0831" data-title="https://orcid.org/0000-0002-0801-0831"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0002-0801-0831</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Earth Observation Science, University of Leicester, LE1 7RH, Leicester, UK </div> </div> <div class="row"> <div class="col-12 mb-3"> National Centre for Earth Observation, University of Leicester, Leicester, UK </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804996" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Hiroshi Suto</h3> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804997" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Yukio Yoshida</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0002-3515-1488" data-title="https://orcid.org/0000-0002-3515-1488"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0002-3515-1488</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804998" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Matthias Buschmann</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0001-5077-9524" data-title="https://orcid.org/0000-0001-5077-9524"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0001-5077-9524</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author804999" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Nicholas M. Deutscher</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0002-2906-2577" data-title="https://orcid.org/0000-0002-2906-2577"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0002-2906-2577</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, NSW 2522, Wollongong, Australia </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805000" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Dietrich G. Feist</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0002-5890-6687" data-title="https://orcid.org/0000-0002-5890-6687"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0002-5890-6687</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Max Planck Institute for Biogeochemistry, 07745 Jena, Germany </div> </div> <div class="row"> <div class="col-12 mb-3"> Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, 82234 Oberpfaffenhofen, Germany </div> </div> <div class="row"> <div class="col-12 mb-3"> Ludwig-Maximilians-Universität München, Lehrstuhl für Physik der Atmosphäre, 80539 Munich, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805001" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">David W. T. Griffith</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0002-7986-1924" data-title="https://orcid.org/0000-0002-7986-1924"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0002-7986-1924</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, NSW 2522, Wollongong, Australia </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805002" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Frank Hase</h3> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Karlsruhe Institute of Technology, IMK-ASF, 76021 Karlsruhe, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805003" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Rigel Kivi</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0001-8828-2759" data-title="https://orcid.org/0000-0001-8828-2759"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0001-8828-2759</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Finnish Meteorological Institute, Space and Earth Observation Centre, Tähteläntie 62, 99600 Sodankylä, Finland </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805004" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered 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Precision Instrumentation, University of Science and Technology of China, 230026 Hefei, China </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805005" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Isamu Morino</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0003-2720-1569" data-title="https://orcid.org/0000-0003-2720-1569"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0003-2720-1569</a> </div> </div> </div> <button 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fade author805011" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Markus Rettinger</h3> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Karlsruhe Institute of Technology, IMK-IFU, 82467 Garmisch-Partenkirchen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805012" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Coleen Roehl</h3> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> California Institute of Technology, Global Environmental Center, Pasadena, CA 91125, USA </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805013" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Constantina Rousogenous</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0001-9505-5239" data-title="https://orcid.org/0000-0001-9505-5239"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" 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class="container-fluid p-0"> <h3 class="modal-title">Kei Shiomi</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0002-1206-8614" data-title="https://orcid.org/0000-0002-1206-8614"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0002-1206-8614</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805016" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Kimberly Strong</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0001-9947-1053" data-title="https://orcid.org/0000-0001-9947-1053"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0001-9947-1053</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Department of Physics, University of Toronto, Toronto, ON, M5S 1A7, Canada </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805017" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Ralf Sussmann</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0002-1970-7538" data-title="https://orcid.org/0000-0002-1970-7538"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" 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class="container-fluid p-0"> <h3 class="modal-title">Voltaire A. Velazco</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0002-1376-438X" data-title="https://orcid.org/0000-0002-1376-438X"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0002-1376-438X</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, NSW 2522, Wollongong, Australia </div> </div> <div class="row"> <div class="col-12 mb-3"> Deutscher Wetterdienst, Meteorological Observatory, 82383 Hohenpeissenberg, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805020" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Mihalis Vrekoussis</h3> <div class="row no-gutters"> <div class="col-12"> <a class="orcid-authors-logo" target="_blank" href="https://orcid.org/0000-0001-8292-8352" data-title="https://orcid.org/0000-0001-8292-8352"><svg class="mr-2" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><image xlink:href="https://www.atmospheric-measurement-techniques.net/orcid_icon.svg" src="https://www.atmospheric-measurement-techniques.net/orcid_icon_128x128.png" width="100%" height="100%"></image></svg>https://orcid.org/0000-0001-8292-8352</a> </div> </div> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus </div> </div> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> <div class="row"> <div class="col-12 mb-3"> Center of Marine Environmental Sciences (MARUM), University of Bremen, Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="modal fade author805021" tabindex="-1" aria-hidden="true"> <div class="modal-dialog modal-dialog-centered modal-dialog-scrollable"> <div class="modal-content"> <div class="modal-header"> <div class="container-fluid p-0"> <h3 class="modal-title">Thorsten Warneke</h3> </div> <button type="button" class="close" data-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="container-fluid p-0"> <div class="row"> <div class="col-12 mb-3"> Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany </div> </div> </div> </div> </div> </div> </div> <div class="abstract sec" id="abstract"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-show="#abstract .co-arrow-open,.abstract-content" data-hide="#abstract .co-arrow-closed,.abstract-mobile-bottom-border"><div class="h1"><span class="section-number"> </span>Abstract<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed" style="display:none"></i><i class="co-arrow-open" style="display:inline-block"></i></span></div></span></div> <div class="abstract-content show-no-js"><p id="d1e563">We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (<span class="inline-formula">XCO<sub>2</sub></span>) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (<span class="inline-formula">XCH<sub>4</sub></span>; full-physics and proxy product), water vapour (<span class="inline-formula">XH<sub>2</sub>O</span>) and the relative ratio of semi-heavy water (<span class="inline-formula">HDO</span>) to water vapour (<span class="inline-formula"><i>δ</i>D</span>). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (<span class="inline-formula">XCO</span>) and nitrous oxide (<span class="inline-formula">XN<sub>2</sub>O</span>) for which we also show first results. We also present an update on <span class="inline-formula">XCO<sub>2</sub></span> from both instruments.</p><p id="d1e652">For <span class="inline-formula">XCO<sub>2</sub></span>, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties.</p><p id="d1e666">With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average <span class="inline-formula">XN<sub>2</sub>O</span> product. Global <span class="inline-formula">XN<sub>2</sub>O</span> maps show a gradient from the tropics to higher latitudes on the order of 15 <span class="inline-formula">ppb</span>, which can be explained by variations in tropopause height. The new GOSAT-2 <span class="inline-formula">XN<sub>2</sub>O</span> product compares well with TCCON. Its station-to-station variability is lower than 2 <span class="inline-formula">ppb</span>, which is about the magnitude of the typical <span class="inline-formula">N<sub>2</sub>O</span> variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average <span class="inline-formula">XN<sub>2</sub>O</span> are on the order of 8 <span class="inline-formula">ppb</span> peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few <span class="inline-formula">XN<sub>2</sub>O</span> measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context.</p></div><span class="abstract-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet" style="display:none"></span></div> <div id="oldMobileDownloadBox" class="widget dark-border hide-on-desktop download-and-links"> <div class="legend journal-contentLinkColor">Download & links</div> <div class="content"> <ul class="additional_info no-bullets no-styling"> <li> <a class="triangle" data-toggle=".box-notice" data-duration="300" title="PDF Version (19128 KB)" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.pdf" > Article (PDF, 19128 KB) </a> </li> </ul> </div> </div> <div id="downloadBoxOneColumn" class="widget dark-border hide-on-desktop download-and-links"> <div class="legend journal-contentLinkColor">Download & links</div> <div class="content"> <ul class="additional_info no-bullets no-styling"> <li><a class="triangle" title="PDF Version (19128 KB)" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.pdf">Article</a> <nobr>(19128 KB)</nobr> </li> <li> <a class="triangle" title="XML Version" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.xml">Full-text XML</a> </li> <li><a class="triangle" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.bib">BibTeX</a></li> <li><a class="triangle" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.ris">EndNote</a></li> </ul> </div> </div> <div id="share" class="oneColumnShareMobileBox widget dark-border hide-on-desktop"> <div class="legend journal-contentLinkColor">Share</div> <div class="content row m-0 py-1"> <div class="col-auto pl-0"> <a class="share-one-line" href="https://www.mendeley.com/import/?url=https%3A%2F%2Famt.copernicus.org%2Farticles%2F15%2F3401%2F2022%2F" title="Mendeley" target="_blank"> <img src="https://www.atmospheric-measurement-techniques.net/mendeley.png" alt="Mendeley"/> </a> </div> <div class="col-auto"> <a class="share-one-line" href="https://www.reddit.com/submit?url=https%3A%2F%2Famt.copernicus.org%2Farticles%2F15%2F3401%2F2022%2F" title="Reddit" target="_blank"> <img src="https://www.atmospheric-measurement-techniques.net/reddit.png" alt="Reddit"> </a> </div> <div class="col-auto"> <a class="share-one-line last" href="https://twitter.com/intent/tweet?text=Retrieval+of+greenhouse+gases+from+GOSAT+and+GOSAT-2+using+the+FOCAL+algorithm https%3A%2F%2Famt.copernicus.org%2Farticles%2F15%2F3401%2F2022%2F" title="Twitter" target="_blank"> <img src="https://www.atmospheric-measurement-techniques.net/twitter.png" alt="Twitter"/> </a> </div> <div class="col-auto"> <a class="share-one-line" href="https://www.facebook.com/share.php?u=https%3A%2F%2Famt.copernicus.org%2Farticles%2F15%2F3401%2F2022%2F&t=Retrieval+of+greenhouse+gases+from+GOSAT+and+GOSAT-2+using+the+FOCAL+algorithm" title="Facebook" target="_blank"> <img src="https://www.atmospheric-measurement-techniques.net/facebook.png" alt="Facebook"/> </a> </div> <div class="col-auto pr-0"> <a class="share-one-line last" href="https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Famt.copernicus.org%2Farticles%2F15%2F3401%2F2022%2F&title=Retrieval+of+greenhouse+gases+from+GOSAT+and+GOSAT-2+using+the+FOCAL+algorithm" title="LinkedIn" target="_blank"> <img src="https://www.atmospheric-measurement-techniques.net/linkedin.png" alt="LinkedIn"> </a> </div> <div class="col pr-0 mobile-native-share"> <a href="#" data-title="Atmospheric Measurement Techniques" data-text="*Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm* Stefan Noël et al." data-url="https://amt.copernicus.org/articles/15/3401/2022/" class="mobile-native-share share-one-line last"><i class="co-mobile-share display-none"></i></a> </div> </div> </div> <div id="citation-footer" class="sec"> <div class="h1-special journal-contentHeaderColor">How to cite. </div> <div class="citation-footer-content show-no-js"> <p> <div class="citation-footer"> Noël, S., Reuter, M., Buchwitz, M., Borchardt, J., Hilker, M., Schneising, O., Bovensmann, H., Burrows, J. P., Di Noia, A., Parker, R. J., Suto, H., Yoshida, Y., Buschmann, M., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Kivi, R., Liu, C., Morino, I., Notholt, J., Oh, Y.-S., Ohyama, H., Petri, C., Pollard, D. F., Rettinger, M., Roehl, C., Rousogenous, C., Sha, M. K., Shiomi, K., Strong, K., Sussmann, R., Té, Y., Velazco, V. A., Vrekoussis, M., and Warneke, T.: Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm, Atmos. Meas. Tech., 15, 3401–3437, https://doi.org/10.5194/amt-15-3401-2022, 2022. </div> </p> </div> </div> <div id="article-dates" class="sec"> <div class="article-dates dates-content my-3"> <nobr>Received: 08 Feb 2022</nobr> – <nobr>Discussion started: 21 Mar 2022</nobr> – <nobr>Revised: 17 May 2022</nobr> – <nobr>Accepted: 19 May 2022</nobr> – <nobr>Published: 09 Jun 2022</nobr> </div> </div> <div id="1_introduction" class="sec"><div class="section1-content hide-on-mobile-soft show-no-js"><span id="page3402"></span></div></div><div class="sec intro" id="section1"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section1 .co-arrow-open,.section1-content" data-show="#section1 .co-arrow-closed,.section1-mobile-bottom-border"><div id="Ch1.S1" class="h1"><span class="label">1</span> Introduction<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section1-content show-no-js hide-on-mobile-soft"><p id="d1e785">Global, long-term data sets of atmospheric constituents are essential to improve our understanding of the behaviour of the Earth's atmosphere. Remote sensing by satellite instruments provides a way to derive large-scale information from measurements. In a time of changing climate, reliable remote sensing data products have gained importance, as they are a crucial input, for example, for models used for climate projections and air quality simulations. Information about the global distribution of greenhouse gases and about their sources and sinks plays an important role in this context.</p><p id="d1e788">Several retrieval methods exist for the derivation of atmospheric information from satellite measurements. In many cases these approaches are based on spectral information from different wavelength regions, and they concentrate on (and are optimised for) a single product. However, the derivation of a different product usually requires the consideration of various additional atmospheric constituents and processes.</p><p id="d1e791">Recently, <span class="cit" id="xref_text.1"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> presented a first version (v1.0) of an <span class="inline-formula">XCO<sub>2</sub></span> data product from GOSAT <span class="cit" id="xref_paren.2">(Greenhouse gases Observing SATellite; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx33" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Kuze et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx33" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2009</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx34" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2016</a>)</span> and GOSAT-2 <span class="cit" id="xref_paren.3">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx62" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Suto et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx62" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> measurements in the near-infrared (NIR) and shortwave infrared (SWIR) spectral regions derived with the FOCAL (Fast atmOspheric traCe gAs retrievaL) method <span class="cit" id="xref_paren.4">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx49" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Reuter et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx49" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx49" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">a</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx50" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">b</a>)</span>. FOCAL was originally applied to measurements of the Orbiting Carbon Observatory-2 <span class="cit" id="xref_paren.5">(OCO-2; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx15" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Eldering et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx15" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a>; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx9" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Crisp et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx9" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a>)</span> and is based on a full-physics retrieval in which scattering is approximated by a single layer. <span class="cit" id="xref_text.6"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> focused on the <span class="inline-formula">XCO<sub>2</sub></span> results, but the application of FOCAL to the GOSAT instruments includes the determination of various other atmospheric quantities. In the current paper, we present results from an updated version (v3.0) of the GOSAT and GOSAT-2 FOCAL retrieval. Although we will also show the results for the new <span class="inline-formula">XCO<sub>2</sub></span> data, the main focus of the paper is on the presentation and initial validation of the additional quantities that can be derived with a single retrieval, thus showing the capabilities of the FOCAL method beyond <span class="inline-formula">XCO<sub>2</sub></span>. In addition to <span class="inline-formula">XCO<sub>2</sub></span>, we present the GOSAT and GOSAT-2 FOCAL results for methane (<span class="inline-formula">XCH<sub>4</sub></span>; full-physics and proxy product), water vapour (<span class="inline-formula">XH<sub>2</sub>O</span>) and semi-heavy water (<span class="inline-formula">HDO</span>, respectively its ratio to <span class="inline-formula">H<sub>2</sub>O</span> denoted as <span class="inline-formula"><i>δ</i>D</span>). The relative amount of water vapour isotopes like <span class="inline-formula">HDO</span> provides information about the age and origin of water vapour. For GOSAT-2, we will also show results for carbon monoxide (<span class="inline-formula">XCO</span>) and nitrous oxide (<span class="inline-formula">XN<sub>2</sub>O</span>) data. The final FOCAL data products also contain information about the uncertainties for each ground pixel.</p><p id="d1e958"><span id="page3403"></span>A multitude of greenhouse gas products derived from GOSAT measurements are available from a number of independent institutions. The Japanese National Institute for Environmental Studies (NIES) provides operational <span class="inline-formula">XCO<sub>2</sub></span>, <span class="inline-formula">XCH<sub>4</sub></span> <span class="cit" id="xref_paren.7">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx74" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Yoshida et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx74" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2013</a>)</span> and <span class="inline-formula">XH<sub>2</sub>O</span> products <span class="cit" id="xref_paren.8">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx14" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Dupuy et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx14" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2016</a>)</span>. NASA also released an <span class="inline-formula">XCO<sub>2</sub></span> product based on the ACOS v9 retrieval, recently described by <span class="cit" id="xref_text.9"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx63" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Taylor et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx63" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2022</a>)</span>. A precursor of the FOCAL <span class="inline-formula">XCO<sub>2</sub></span> product v1.0 from <span class="cit" id="xref_text.10"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> is the BESD v01.04 product, which is also from the Institute of Environmental Physics (IUP), Bremen <span class="cit" id="xref_paren.11">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx26" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Heymann et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx26" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2015</a>)</span>. This is a near-real-time product produced for the Copernicus Atmospheric Monitoring Service (CAMS, <span class="uri"><a href="https://atmosphere.copernicus.eu/" target="_blank">https://atmosphere.copernicus.eu/</a></span>, last access: 30 July 2020). Copernicus is the Earth observation programme of the EU and ESA. Current plans call for a replacement of BESD with a near-real-time version of the FOCAL <span class="inline-formula">XCO<sub>2</sub></span> product described in this paper in the near future. Several GOSAT products are produced for the Copernicus Climate Change Service (C3S, <span class="uri"><a href="https://climate.copernicus.eu/" target="_blank">https://climate.copernicus.eu/</a></span>, last access: 30 July 2020). In this context, the Netherlands Institute for Space Research (SRON) provides <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span> data <span class="cit" id="xref_paren.12">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx7" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Butz et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx7" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2011</a>; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx55" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Schepers et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx55" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2012</a>)</span>. Similar products are also generated by the University of Leicester <span class="cit" id="xref_paren.13">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx8" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Cogan et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx8" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2012</a>; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx42" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Parker et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx42" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2011</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx43" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2020</a>)</span>. Water vapour results from GOSAT were presented by <span class="cit" id="xref_text.14"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx65" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Trent et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx65" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2018</a>)</span>. The ratio of <span class="inline-formula">HDO</span> to <span class="inline-formula">H<sub>2</sub>O</span> (<span class="inline-formula"><i>δ</i>D</span>) was derived for some case studies by <span class="cit" id="xref_text.15"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx17" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Frankenberg et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx17" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2013</a>)</span> and <span class="cit" id="xref_text.16"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx4" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Boesch et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx4" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2013</a>)</span>.</p><p id="d1e1122">For GOSAT-2, operational <span class="inline-formula">XCO<sub>2</sub></span>, <span class="inline-formula">XCH<sub>4</sub></span>, <span class="inline-formula">XCO</span> and <span class="inline-formula">XH<sub>2</sub>O</span> SWIR products have been released by NIES (see <span class="uri"><a href="https://prdct.gosat-2.nies.go.jp/" target="_blank">https://prdct.gosat-2.nies.go.jp/</a></span>, last access: 6 June 2021). There is no <span class="inline-formula">XN<sub>2</sub>O</span> product for GOSAT-2 from NIES available yet. Actually, there are only few measurements of <span class="inline-formula">N<sub>2</sub>O</span> from satellite. There were some attempts to retrieve <span class="inline-formula">N<sub>2</sub>O</span> from GOSAT measurements in the thermal infrared (TIR); see <span class="cit" id="xref_text.17"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx30" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Kangah et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx30" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a>)</span>. Furthermore, <span class="cit" id="xref_text.18"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Barret et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> presented results from the Infrared Atmospheric Sounding Interferometer (IASI) instrument on Metop. A dedicated satellite project, the Monitoring Nitrous Oxide Sources <span class="cit" id="xref_paren.19">(MIN2OS; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx53" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Ricaud et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx53" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> mission, is currently planned.</p><p id="d1e1222">The main aim of the current study is to give an overview of the large number of newly available FOCAL data products for GOSAT and GOSAT-2. To get an impression of the quality of these products, we compare them with ground-based measurements from the Total Carbon Column Observing Network <span class="cit" id="xref_paren.20">(TCCON; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx72" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wunch et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx72" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2011</a>)</span>. For GOSAT, we also include comparisons with other available <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span> GOSAT data sets.</p><p id="d1e1252">TCCON is a network of Fourier transform spectrometers, which measure spectra in the near-infrared spectral range while viewing directly at the sun. From these measurements, information about the abundance of several atmospheric constituents is obtained, including <span class="inline-formula">CO<sub>2</sub></span>, <span class="inline-formula">CH<sub>4</sub></span>, <span class="inline-formula">N<sub>2</sub>O</span>, <span class="inline-formula">CO</span>, <span class="inline-formula">H<sub>2</sub>O</span> and <span class="inline-formula">HDO</span>. TCCON measurements are very accurate <span class="cit" id="xref_paren.21">(see <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx71" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wunch et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx71" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2010</a>)</span> and thus well suited for the validation of satellite data.</p><p id="d1e1325">The paper is structured as follows: after this introduction, we present the input data used in this study in Sect. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.S2" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2</a>. We then describe the updated retrieval algorithm in Sect. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.S3" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">3</a>, followed by the results of the study (including first validation) in Sect. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.S4" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">4</a>. Finally, we summarise everything in the conclusions (Sect. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.S5" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">5</a>). Additional information is given in Appendix A and B.</p></div><span class="section1-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div class="sec" id="section2"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section2 .co-arrow-open,.section2-content" data-show="#section2 .co-arrow-closed,.section2-mobile-bottom-border"><div id="Ch1.S2" class="h1"><span class="label">2</span> Input data<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section2-content show-no-js hide-on-mobile-soft"><p id="d1e1344">The input data used in this study are essentially the same as for the v1.0 product described in <span class="cit" id="xref_text.22"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> with some updates described in the following. As input spectra, we use calibrated GOSAT and GOSAT-2 L1B radiances for both polarisation directions of the three NIR/SWIR bands at around 0.76, 1.6 and 2.0 <span class="inline-formula">µ</span>m. All data until the end of 2020 are processed. For GOSAT, we use product version V220.220, extended by V230.230 for about the last 2 months of 2020. The GOSAT-2 L1B product version is now V102.102. The instrumental line shape (ILS) data are the same as in <span class="cit" id="xref_text.23"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>.</p><p id="d1e1361">The solar irradiance and solar-induced fluorescence (SIF) reference spectra are unchanged. The cross sections have been updated; we now use data from HITRAN2016 <span class="cit" id="xref_paren.24">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx20" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Gordon et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx20" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a>, downloaded on 23 March 2021)</span> in combination with updated cross sections from the NASA (National Aeronautics and Space Administration) ACOS/OCO-2 project, i.e. ABSCO v5.1 data <span class="cit" id="xref_paren.25">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx44" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Payne et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx44" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2020</a>)</span>.</p><p id="d1e1372">As in <span class="cit" id="xref_text.26"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>, surface properties are obtained from the Global Multi-resolution Terrain Elevation Data <span class="cit" id="xref_paren.27">(GMTED2010; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx10" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Danielson and Gesch</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx10" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2011</a>)</span> of the U.S. Geological Survey (USGS) and the National Geospatial-Intelligence Agency (NGA). Meteorology is taken from ECMWF (European Centre for Medium-range Weather Forecasts) ERA5 reanalysis data <span class="cit" id="xref_paren.28">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx25" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Hersbach et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx25" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2020</a>)</span>.</p><p id="d1e1386">There has been a change in the a priori profile data used for <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span>. These are now derived using a Simple cLImatological Model for atmospheric <span class="inline-formula">CO<sub>2</sub></span> and <span class="inline-formula">CH<sub>4</sub></span>, respectively called SLIMCO2 and SLIMCH4 (see Appendix <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A</a> for details). All other a priori data and the related uncertainties are unchanged compared to v1.0. The SLIMCO2 and SLIMCH4 data are also used in the bias correction for <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span>; see Sect. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.S3.SS3.SSS3" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">3.3.3</a> below. As “truth”, we use a subset of the SLIM data from 2019 that has been selected based on a comparison with TCCON data <span class="cit" id="xref_paren.29">(see <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>, for a detailed description)</span>.</p><p id="d1e1468">The same TCCON GGG2014 data are used for comparisons as in <span class="cit" id="xref_text.30"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>, but now for the extended time period until the end of 2020. All involved TCCON stations and related references are listed in Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">1</a>.</p><span class="tableCitations"><span class="cit" id="xref_text.32"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx19" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Goo et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx19" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a>)</span><span class="cit" id="xref_text.33"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx16" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Feist et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx16" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a>)</span><span class="cit" id="xref_text.34"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx12" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Deutscher et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx12" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2019</a>)</span><span class="cit" id="xref_text.35"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx40" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Notholt et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx40" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2019</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx40" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">a</a>)</span><span class="cit" id="xref_text.36"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx38" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Morino et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx38" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2018</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx38" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">b</a>)</span><span class="cit" id="xref_text.37"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx22" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Griffith et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx22" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx22" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">a</a>)</span><span class="cit" id="xref_text.38"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx27" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Iraci et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx27" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2016</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx27" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">a</a>)</span><span class="cit" id="xref_text.39"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx73" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wunch et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx73" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a>)</span><span class="cit" id="xref_text.40"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx59" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Strong et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx59" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2019</a>)</span><span class="cit" id="xref_text.41"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx13" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Dubey et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx13" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a>)</span><span class="cit" id="xref_text.42"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx60" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Sussmann and Rettinger</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx60" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2018</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx60" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">a</a>)</span><span class="cit" id="xref_text.43"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx35" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Liu et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx35" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2018</a>)</span><span class="cit" id="xref_text.44"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx28" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Iraci et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx28" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2016</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx28" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">b</a>)</span><span class="cit" id="xref_text.45"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx3" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Blumenstock et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx3" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a>)</span><span class="cit" id="xref_text.46"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx24" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Hase et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx24" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a>)</span><span class="cit" id="xref_text.47"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx68" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wennberg et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx68" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2016</a>)</span><span class="cit" id="xref_text.48"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx57" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Sherlock et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx57" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx57" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">a</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx58" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">b</a>)</span><span class="cit" id="xref_text.49"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx46" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Pollard et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx46" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2019</a>)</span><span class="cit" id="xref_text.50"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx45" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Petri et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx45" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2020</a>)</span><span class="cit" id="xref_text.51"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx41" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Notholt et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx41" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2019</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx41" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">b</a>)</span><span class="cit" id="xref_text.52"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx66" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Warneke et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx66" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2019</a>)</span><span class="cit" id="xref_text.53"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx64" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Te et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx64" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a>)</span><span class="cit" id="xref_text.54"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx69" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wennberg et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx69" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a>)</span><span class="cit" id="xref_text.55"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx67" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wennberg et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx67" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2015</a>)</span><span class="cit" id="xref_text.56"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx11" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">De Mazière et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx11" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a>)</span><span class="cit" id="xref_text.57"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx36" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Morino et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx36" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a>)</span><span class="cit" id="xref_text.58"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx31" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Kawakami et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx31" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a>)</span><span class="cit" id="xref_text.59"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx32" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Kivi et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx32" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a>)</span><span class="cit" id="xref_text.60"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx37" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Morino et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx37" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2018</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx37" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">a</a>)</span><span class="cit" id="xref_text.61"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx23" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Griffith et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx23" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx23" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">b</a>)</span><span class="cit" id="xref_text.62"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx61" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Sussmann and Rettinger</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx61" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2018</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx61" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">b</a>)</span></span><div class="table-wrap" id="Ch1.T1"><div class="caption"><p id="d1e1479"><strong class="caption-number">Table 1</strong>TCCON stations used in this study (update of similar table in <span class="cit" id="xref_altparen.31"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a></span>).</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t01.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t01-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t01-web.png" data-width="2067" data-height="1961" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t01.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t01.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t01.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t01.xlsx" target="_blank">Download XLSX</a></p></div><p id="d1e2322">In addition to the validation with ground-based data we also include comparisons with other GOSAT data sets for <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span>, namely the ACOS v9r <span class="inline-formula">XCO<sub>2</sub></span> product from NASA <span class="cit" id="xref_paren.63">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx63" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Taylor et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx63" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2022</a>)</span>; the full-physics and proxy products from the University of Leicester <span class="cit" id="xref_paren.64">(UoL <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span> FP v7.3, UoL <span class="inline-formula">XCH<sub>4</sub></span> proxy v9.0; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx8" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Cogan et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx8" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2012</a>)</span>; the full-physics and proxy products from SRON <span class="cit" id="xref_paren.65">(RemoTeC FP <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span> v2.3.8, RemoTeC <span class="inline-formula">XCH<sub>4</sub></span> proxy product v2.3.9; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx7" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Butz et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx7" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2011</a>)</span>; and the operational bias-corrected GOSAT <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span> products from NIES v02.9x <span class="cit" id="xref_paren.66">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx74" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Yoshida et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx74" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2013</a>)</span>. The ACOS v9 data set is the “lite” product, downloaded in April 2020, which contains data up to end of 2019. We use only ACOS data with quality flag 0.</p></div><span class="section2-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div class="sec" id="section3"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section3 .co-arrow-open,.section3-content" data-show="#section3 .co-arrow-closed,.section3-mobile-bottom-border"><div id="Ch1.S3" class="h1"><span class="label">3</span> Retrieval algorithm<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section3-content show-no-js hide-on-mobile-soft"><p id="d1e2471">The retrieval used in this study is a three-step approach consisting of pre-processing, processing and post-processing. It uses as input the calibrated GOSAT/GOSAT-2 spectral<span id="page3404"></span> radiances, independently for each polarisation direction. Since the retrieval method is essentially the same as the one described in <span class="cit" id="xref_text.67"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> for product version 1.0, we will describe in the following only the differences applied for the updated product version (v3.0; v2 was an unreleased internal version). Most relevant changes for the current product version were in the pre-processing and post-processing parts.</p><p id="d1e2477">The computational speed could be slightly improved in v3.0 compared to v1.0. For GOSAT, the retrieval for one ground pixel is typically done within about 20 <span class="inline-formula">s</span>, GOSAT-2 processing takes a few seconds more due to the additional fitting windows. Note that this time is for the simultaneous retrieval for all data products. Times for pre-processing and post-processing are negligible compared to the retrieval.</p><div class="sec"><h2 id="Ch1.S3.SS1"><span class="label">3.1</span> Pre-processing</h2> <p id="d1e2495">The pre-processing step collects and prepares all data required for the processing. This step especially includes the measured GOSAT and GOSAT-2 spectra, as well as geolocation and matching meteorological and topographic information (from ECMWF ERA5 and GMTED2010). Furthermore, some initial filtering (especially for clouds) is performed. The cloud filtering method is based on the derivation of an effective albedo and a water vapour absorption filter from the spectral data as described in <span class="cit" id="xref_text.68"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>. This makes use of the facts that clouds are usually bright and are located above the surface such that the amount of water vapour above the cloud is low.</p> <p id="d1e2501">For the new FOCAL products, two filter limits of the pre-processing have been relaxed to increase the final data yield: we now use a maximum solar zenith angle (SZA) of 90<span class="inline-formula"><sup>∘</sup></span> and also latitudes up to <span class="inline-formula">±90</span><span class="inline-formula"><sup>∘</sup></span>. In v1.0, both limits were set to 70<span class="inline-formula"><sup>∘</sup></span>. Note that these limits are applied for pre-processing; further filtering is done later during post-processing, depending on the different products (see Sect. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.S3.SS3" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">3.3</a>). All other filtering (including the cloud filter) is unchanged compared to v1.0. The main difference in pre-processing to v1.0 is, therefore, that for v3.0 high latitudes are not necessarily filtered out before processing. This allows for more flexibility in the definition of product-specific post-processing filters by taking into<span id="page3405"></span> account different sensitivities of each product. Furthermore, as mentioned above, we now use SLIMCO2 and SLIMCH4 data as a priori data for <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span>.</p> </div><div class="sec"><h2 id="Ch1.S3.SS2"><span class="label">3.2</span> Processing</h2> <p id="d1e2573">Both v1.0 and v3.0 processing versions use the FOCAL algorithm described in <span class="cit" id="xref_text.69"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx50" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Reuter et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx50" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx50" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">b</a>)</span>. FOCAL is a full-physics retrieval method, which approximates scattering in the atmosphere by a single layer. With this, the forward model to simulate radiation can be expressed as an analytical formula, which allows for a high computational speed. The v3.0 updates to FOCAL include the use of a modified version of FOCAL, which assumes isotropic instead of Lambertian scattering at the scattering layer, and we also fit <span class="inline-formula">H<sub>2</sub>O</span> in the NIR band (see Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T2" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2</a>).</p> <span class="tableCitations"></span><div class="table-wrap" id="Ch1.T2"><div class="caption"><p id="d1e2597"><strong class="caption-number">Table 2</strong>Definition of GOSAT/GOSAT-2 spectral fit windows (same for <span class="inline-formula"><i>S</i></span> and <span class="inline-formula"><i>P</i></span> polarisation). Windows 7 and 8 are only available for GOSAT-2. Cross sections are from HITRAN2016 except for those marked with “<span class="inline-formula"><sup>a</sup></span>”, which are from ABSCO v5.1, and those marked with “<span class="inline-formula"><sup>b</sup></span>”, which are from <span class="cit" id="xref_text.70"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx21" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Gorshelev et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx21" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a>)</span> and <span class="cit" id="xref_text.71"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx56" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Serdyuchenko et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx56" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2014</a>)</span>.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t02.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t02-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t02-web.png" data-width="2067" data-height="1189" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t02.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t02.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t02.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t02.xlsx" target="_blank">Download XLSX</a></p></div> <p id="d1e3245">The FOCAL retrieval is based on an optimal estimation algorithm <span class="cit" id="xref_paren.72">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx54" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Rodgers</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx54" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2000</a>)</span>, taking as main input measured calibrated spectra and their uncertainties. The quantities to be retrieved are collected in the state vector, and secondary inputs to the retrieval algorithm are corresponding a priori values and their uncertainties in the form of an a priori error covariance matrix. The main output of the FOCAL retrieval is the values and uncertainties of the elements of the state vector. The state vector elements of v3.0 (see Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T3" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">3</a>) are almost the same as in v1.0; however, we increased the degrees of the background polynomials to improve the fit residuals such that now all fitted polynomials are of degree 3 except for the small solar-induced fluorescence (SIF) windows where we use a degree of 1 and the <span class="inline-formula">XN<sub>2</sub>O</span> window where a degree of 4 is used. The latter is done because the sensitivity of <span class="inline-formula">XN<sub>2</sub>O</span> to surface effects turned out to be larger than for the other products. All quantities in the state vector are retrieved simultaneously. For <span class="inline-formula">CO<sub>2</sub></span>, <span class="inline-formula">CH<sub>4</sub></span> and <span class="inline-formula">H<sub>2</sub>O</span>, we derive profiles on five layers which are then converted to total column averages.</p> <p id="d1e3316"><span class="inline-formula"><i>δ</i>D</span>, <span class="inline-formula">XCO</span> and <span class="inline-formula">XN<sub>2</sub>O</span> are derived via scaling factors. The <span class="inline-formula">XCH<sub>4</sub></span> proxy product is derived after the retrieval from these full-physics products (see below). In the case of GOSAT-2, all scattering parameters as well as methane, water vapour and <span class="inline-formula"><i>δ</i>D</span> are only fitted in windows 1 to 6 (i.e. those spectral ranges which are also available for GOSAT). This is done to provide consistent products for the two sensors.</p> <p id="d1e3370">As in v1.0, for GOSAT – but not GOSAT-2 – we compute a spectral correction factor to account for changes in the spectral calibration with time. In v3.0 the factor is obtained from the spectral difference of Fraunhofer lines in the solar irradiance and measured radiance in the SIF window, which is more stable than the least-squares fitting procedure used in v1.0. This new method only corrects for shifts on the scale of one spectral sampling interval (0.2 <span class="inline-formula">cm<sup>−1</sup></span>); this, however, is sufficient, as additional spectral shift and squeeze factors are determined in the later retrieval for both versions.</p> <p id="d1e3387">We also use a noise model to correct the uncertainties of the GOSAT and GOSAT-2 spectra estimated during pre-processing and consider possible forward model uncertainties in the retrieval. This noise model is the same as in v1.0, but we recomputed the parameters for all fitting windows based on an input data set consisting of 1 d per month in 2019 for both GOSAT and GOSAT-2. The resulting parameters are, however, similar for v1.0 and v3.0.</p> </div><div class="sec"><h2 id="Ch1.S3.SS3"><span class="label">3.3</span> Post-processing</h2> <p id="d1e3399">The main changes between v1.0 and v3.0 occur in the post-processing step. The overall concept of our new approach is that we tried to establish a generic, mostly automated, procedure that provides reproducible results and thus can be applied to all gases under consideration. However, it still allows for an optimisation for each product.</p> <p id="d1e3402">The following post-processing steps are in general applied to all products: </p><ol><li> <p id="d1e3407">basic filtering,</p></li><li> <p id="d1e3411">quality filtering,</p></li><li> <p id="d1e3415">bias correction (for <span class="inline-formula">CO<sub>2</sub></span> and <span class="inline-formula">CH<sub>4</sub></span> only).</p></li></ol><p id="d1e3402-3"> Note that, in contrast to v1.0, there is no longer a filter on the derived bias applied after the bias correction.</p> <p id="d1e3441">The <span class="inline-formula">XCH<sub>4</sub></span> proxy product is computed during post-processing from </p><div class="disp-formula" content-type="numbered" id="Ch1.E1"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M165" display="block" overflow="scroll" dspmath="mathml"><mtable><mlabeledtr><mtd><mtext>(1)</mtext></mtd><mtd><mrow> <msup> <mrow class="chem"> <msub> <mi mathvariant="normal">XCH</mi> <mn mathvariant="normal">4</mn> </msub> </mrow> <mi mathvariant="normal">proxy</mi> </msup> <mo>=</mo> <msup> <mrow class="chem"> <msub> <mi mathvariant="normal">XCH</mi> <mn mathvariant="normal">4</mn> </msub> </mrow> <mi mathvariant="normal">retrieved</mi> </msup> <mstyle displaystyle="true"> <mfrac style="display"> <mrow> <msup> <mrow class="chem"> <msub> <mi mathvariant="normal">XCO</mi> <mn mathvariant="normal">2</mn> </msub> </mrow> <mrow> <mi mathvariant="normal">a</mi> <mspace width="0.125em" linebreak="nobreak"></mspace> <mspace width="0.125em" linebreak="nobreak"></mspace> <mi mathvariant="normal">priori</mi> </mrow> </msup> </mrow> <mrow> <msup> <mrow class="chem"> <msub> <mi mathvariant="normal">XCO</mi> <mn mathvariant="normal">2</mn> </msub> </mrow> <mi mathvariant="normal">retrieved</mi> </msup> </mrow> </mfrac> </mstyle> <mo>.</mo> </mrow></mtd></mlabeledtr></mtable></math><div><svg xmlns:svg="http://www.w3.org/2000/svg" width="416pt" height="35pt" class="hide-js svg-formula" dspmath="mathimg" md5hash="e5c2c04d6a273b79c71263ee49ea3b56"><image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-e_1.svg" width="100%" height="35pt" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-e_1.png"></image></svg></div></div><p id="d1e3441-3"> This means we normalise the retrieved full-physics <span class="inline-formula">XCH<sub>4</sub></span> by the retrieved full-physics <span class="inline-formula">XCO<sub>2</sub></span> (both without bias correction) and use as reference the a priori <span class="inline-formula">XCO<sub>2</sub></span>. Note that this is different to, for example, the SRON <span class="inline-formula">XCH<sub>4</sub></span> proxy product <span class="cit" id="xref_paren.73">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx70" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wu et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx70" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>, which is derived from a dedicated non-scattering retrieval using a different wavelength region (6045–6138 <span class="inline-formula">cm<sup>−1</sup></span>). The uncertainty of the proxy product is then determined via error propagation. The <span class="inline-formula">XCH<sub>4</sub></span> proxy product is then treated in post-processing as the other products.</p> <p id="d1e3583">The general advantage of proxy products <span class="cit" id="xref_paren.74">(see also <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx42" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Parker et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx42" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2011</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx43" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2020</a>; <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx55" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Schepers et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx55" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2012</a>)</span> is that they are less sensitive to light-path effects like scattering. They therefore usually have a larger coverage. However, they usually depend on a model reference, which is in our case SLIMCO2 (see Appendix <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A</a>). The uncertainty of the <span class="inline-formula">XCH<sub>4</sub></span> proxy product is also larger than for the full-physics product, because it includes the uncertainty of the derived <span class="inline-formula">XCO<sub>2</sub></span>.</p> <span class="tableCitations"></span><div class="table-wrap" id="Ch1.T3"><div class="caption"><p id="d1e3619"><strong class="caption-number">Table 3</strong>State vector elements and related retrieval settings. A priori values are also used as first guess. The “Fit windows” column lists the spectral windows (see Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T2" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2</a>) from which the element is determined; “each” means that a corresponding element is fitted in each fit window. A priori values labelled as “PP” are taken from pre-processing; “est.” denotes that they have been estimated from the background signal.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t03.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t03-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t03-web.png" data-width="2067" data-height="1790" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t03.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t03.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t03.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t03.xlsx" target="_blank">Download XLSX</a></p></div> <div class="sec"><h3 id="Ch1.S3.SS3.SSS1"><span class="label">3.3.1</span> Basic post-processing filters</h3> <p id="d1e4349">In contrast to v1.0, the basic filtering does not involve filtering based on external information, e.g. by using pre-described limits of scattering parameters or product uncertainties. This is no longer done as these fixed limits removed<span id="page3406"></span> too many possibly valid data points, especially in the case of GOSAT-2.</p> <p id="d1e4352">Therefore, the basic filtering now only includes the filtering for good convergence (<span class="inline-formula"><i>χ</i><sup>2</sup></span> smaller than 2) and a maximum residual-to-signal ratio (RSR) as a function of the noise-to-signal ratio (NSR). This is done in the same way as for v1.0 <span class="cit" id="xref_paren.75">(see <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> but with the updated noise model parameters mentioned above. This part of the basic filtering is common for all products.</p> <p id="d1e4371"><span id="page3407"></span>For GOSAT, the RSR filters for all fitting windows (1–6) are applied to all data products. In the case of GOSAT-2, for consistency, we also apply only the RSR filters for windows 1–6 to those products that are also available from GOSAT (i.e. <span class="inline-formula">XCO<sub>2</sub></span>, methane and water vapour products). For the other two GOSAT-2 products, i.e. <span class="inline-formula">XCO</span> and <span class="inline-formula">XN<sub>2</sub>O</span>, we only apply RSR filters from the NIR (windows 1 and 2, which contain the majority of the information related to scattering) and those windows where these gases are retrieved, namely window 8 for <span class="inline-formula">XCO</span> and window 7 for <span class="inline-formula">XN<sub>2</sub>O</span>. This is to avoid inadvertently filtering out a valid <span class="inline-formula">XCO<sub>2</sub></span> measurement due to, for example, a bad <span class="inline-formula">XN<sub>2</sub>O</span> fit (or vice versa).</p> <p id="d1e4452">In addition to this, we apply a filter on a maximum SZA of 75<span class="inline-formula"><sup>∘</sup></span>, because we cannot expect good data products at low solar illumination. This is a slightly higher limit than in v1.0, where all data above 70<span class="inline-formula"><sup>∘</sup></span> were already filtered out during pre-processing. This SZA filter is applied for all products except for water vapour, because requirements for water vapour are not as strict as, for example, for <span class="inline-formula">XCO<sub>2</sub></span>. This is why we do not apply this strict filter already in pre-processing (where we only limit the SZA to 90<span class="inline-formula"><sup>∘</sup></span>; see above).</p> <div class="fig" id="Ch1.F1"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f01-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f01" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f01-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f01-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f01-high-res.pdf" data-width="2067" data-height="1490"></a><div class="caption"><p id="d1e4496"><strong class="caption-number">Figure 1</strong>Number of GOSAT data for different products as a function of time (see Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a> for details on version numbers). <strong>(a)</strong> GOSAT <span class="inline-formula">XCO<sub>2</sub></span>; <strong>(b)</strong> GOSAT <span class="inline-formula">XCH<sub>4</sub></span>.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f01-high-res.pdf" target="_blank">Download</a></p></div> </div> <div class="sec"><h3 id="Ch1.S3.SS3.SSS2"><span class="label">3.3.2</span> Quality filtering</h3> <p id="d1e4543">The quality filtering is product-specific, but it follows the same strategy for each target gas. In general, we perform independent filtering for water and land surfaces. The final data product contains only the filtered data. The filtering out of low-quality data was done in v1.0 by a random forest filter. However, as explained in <span class="cit" id="xref_text.76"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>, the performance of this method was not ideal as it filtered out fewer data than expected, i.e. less data were filtered out than were marked as “bad” during the training of the random forest filter. Therefore, we replaced this filtering for v3.0 with a filter procedure that has already been successfully used in OCO-2 retrievals; details can be found in <span class="cit" id="xref_text.77"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx49" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Reuter et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx49" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx49" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">a</a>)</span>. This procedure is based on a minimisation of the local variance. This is done by computing, for a subset of the data, the variance of the difference between the retrieved quantity and its median on a 15<span class="inline-formula"><sup>∘</sup></span><span class="inline-formula">×</span>15<span class="inline-formula"><sup>∘</sup></span> grid. Based on this subset, we check which variables from a given list of the candidate variables perform best in reducing the local variance when removing data corresponding to the highest or lowest 1 % of each variable. This action defines a new upper or lower limit for this variable. We repeat this until a prescribed amount of data are removed. The output of this procedure is a list of “best” variables and their new filter limits. This subset has been generated from data of 2019 for GOSAT and GOSAT-2, to which the basic quality filter as described above has been applied. Note that – in contrast to v1.0 – this subset no longer depends on the reference database used in the bias correction. A general problem with this filtering method is that it tends to filter out values from regions with higher noise, which might result in reduced coverage at higher latitudes if too many data are to be filtered out. Therefore, we apply this filtering in two steps. First, using the variance filter method, we determine limits for only the scattering optical depth parameters contained in the state vector in order to filter out a set percentage (<span class="inline-formula"><i>P</i><sub><i>τ</i></sub></span>) of the data. After applying this filter, we further reduce the number of data by another percentage (<span class="inline-formula"><i>P</i><sub>V</sub></span>) using the variance filter method again but now for an extended list of possible filter candidates. This list of variables has been largely reduced compared to v1.0. It now only comprises results from the retrieval, namely the uncertainties (but not values) of the retrieved target species, <span class="inline-formula"><i>χ</i><sup>2</sup></span>, scattering parameters and their uncertainties, the polynomial coefficients and their uncertainties, wavelength shift/squeeze and their uncertainties, and surface roughness. We explicitly no longer include geolocation/viewing geometry parameters or surface elevation to avoid cases where data are filtered out due to, for example, a specific geographical region. The retrieved <span class="inline-formula">CO<sub>2</sub></span> gradient at the surface is also not used anymore, as this might result in filtering out scenes with too high <span class="inline-formula">CO<sub>2</sub></span> in the boundary layer close to a point source. However, because of the large number of fitting windows this still leaves a list of about 200 possible parameters. To reduce this to a reasonable number, we run this variance filter twice: first with the full list and then with only the 10 best parameters. This number (10 parameters) is only an upper limit, which has been chosen by checking that adding more parameters does not further reduce the variance significantly. Depending on the relevance of individual quantities, even fewer parameters are needed in some cases.</p> <div class="fig" id="Ch1.F2"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f02-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f02" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f02-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f02-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f02-high-res.pdf" data-width="2067" data-height="1490"></a><div class="caption"><p id="d1e4634"><strong class="caption-number">Figure 2</strong>Number of FOCAL GOSAT and GOSAT-2 data as a function of time. <strong>(a)</strong> GOSAT FOCAL <span class="inline-formula">XH<sub>2</sub>O</span> and <span class="inline-formula"><i>δ</i>D</span>; <strong>(b)</strong> GOSAT-2 FOCAL products.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f02-high-res.pdf" target="_blank">Download</a></p></div> <p id="d1e4672">The choice of the number of data to be filtered out is – as always – a trade-off between the remaining number of data points and data quality. For the v3.0 data, we determined suitable numbers for <span class="inline-formula"><i>P</i><sub><i>τ</i></sub></span> and <span class="inline-formula"><i>P</i><sub>V</sub></span> by looking at the resulting data quality (maps and validation) for different settings. As with the SZA filter, the optical depth filter is not applied for each product. We use the same values for GOSAT and GOSAT-2; these are listed in Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T4" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">4</a>. The final set of selected filter variables and their limits is specific to each product, surface and instrument. They are given in Appendix A in Tables <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.T7" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A1</a> to <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.T18" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A12</a>.</p> <span class="tableCitations"></span><div class="table-wrap" id="Ch1.T4"><div class="caption"><p id="d1e4707"><strong class="caption-number">Table 4</strong>Filter settings for all products; “–” denotes that no limit is applied.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t04.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t04-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t04-web.png" data-width="1033" data-height="1335" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t04.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t04.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t04.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t04.xlsx" target="_blank">Download XLSX</a></p></div> <p id="d1e5211">Note that the minimisation of the variance is done for the whole test data set, i.e. a year of global data. Small, local sinks or enhancements should have no impact here, as long as there is no clear correlation between, for example, a filter variable and the retrieved value or the geolocation. This is why we only use a very restricted list of possible variables.</p> </div> <div class="sec"><h3 id="Ch1.S3.SS3.SSS3"><span class="label">3.3.3</span> Bias correction</h3> <p id="d1e5222">After filtering data as described above, we apply a bias correction to <span class="inline-formula">XCO<sub>2</sub></span> and the <span class="inline-formula">XCH<sub>4</sub></span> full-physics and proxy products. The overall procedure is the same as described in detail in <span class="cit" id="xref_text.78"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>. The bias correction is based on a random forest regression using, as for v1.0, the 10 most relevant parameters and a random forest database as input. These have been determined as described in <span class="cit" id="xref_text.79"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>, using as input the variance-filtered test subset of data as mentioned above and a reference database giving the “true” <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span>. This reference database has been generated from a subset of daily SLIMCO2 and SLIMCH4 data (see Appendix <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A</a>) for 2019, which agree within <span class="inline-formula">±0.5</span> <span class="inline-formula">ppm</span> for <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">±10</span> <span class="inline-formula">ppb</span> for <span class="inline-formula">XCH<sub>4</sub></span> with corresponding TCCON data. The best parameters have been chosen from essentially the same list of candidate variables used in the variance filter but now extended with surface elevation and type, solar zenith angle, viewing zenith angle, continuum signal, and flags for<span id="page3409"></span> quality and instrument gain. The final choice of bias correction parameters and their relevance is shown in Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F23" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A7</a> for GOSAT and Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F24" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A8</a> for GOSAT-2 (see Appendix <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S2" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">B</a>).</p> <p id="d1e5343">We also perform a correction of the retrieved <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span> uncertainties (<span class="inline-formula">Δ<i>X</i><sub>retr</sub></span>) via a linear function: </p><div class="disp-formula" content-type="numbered" id="Ch1.E2"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M278" display="block" overflow="scroll" dspmath="mathml"><mtable><mlabeledtr><mtd><mtext>(2)</mtext></mtd><mtd><mrow> <mi mathvariant="normal">Δ</mi> <mi>X</mi> <mo>=</mo> <msub> <mi>a</mi> <mi>c</mi> </msub> <mo>+</mo> <msub> <mi>b</mi> <mi>c</mi> </msub> <mspace linebreak="nobreak" width="0.25em"></mspace> <mi mathvariant="normal">Δ</mi> <msub> <mi>X</mi> <mi mathvariant="normal">retr</mi> </msub> <mo>.</mo> </mrow></mtd></mlabeledtr></mtable></math><div><svg xmlns:svg="http://www.w3.org/2000/svg" width="416pt" height="13pt" class="hide-js svg-formula" dspmath="mathimg" md5hash="d9d6df3a2ee19304edc90c20cb55a267"><image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-e_2.svg" width="100%" height="13pt" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-e_2.png"></image></svg></div></div><p id="d1e5343-3"> <span class="inline-formula">Δ<i>X</i></span> is the corrected uncertainty with <span class="inline-formula"><i>X</i></span> being either <span class="inline-formula">XCO<sub>2</sub></span> or <span class="inline-formula">XCH<sub>4</sub></span>. The coefficients <span class="inline-formula"><i>a</i><sub><i>c</i></sub></span> and <span class="inline-formula"><i>b</i><sub><i>c</i></sub></span> of this function (see Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T5" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">5</a>) are determined in a similar way as described in <span class="cit" id="xref_text.80"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> by comparing the scatter of the data relative to a truth with the retrieved uncertainty, but instead of TCCON data we now use data from the SLIMCO2/SLIMCH4 reference database as true values.</p> <span class="tableCitations"></span><div class="table-wrap" id="Ch1.T5"><div class="caption"><p id="d1e5486"><strong class="caption-number">Table 5</strong>Coefficients of linear uncertainty correction.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t05.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t05-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t05-web.png" data-width="1033" data-height="1136" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t05.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t05.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t05.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t05.xlsx" target="_blank">Download XLSX</a></p></div> </div> </div></div><span class="section3-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div class="sec" id="section4"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section4 .co-arrow-open,.section4-content" data-show="#section4 .co-arrow-closed,.section4-mobile-bottom-border"><div id="Ch1.S4" class="h1"><span class="label">4</span> Results<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section4-content show-no-js hide-on-mobile-soft"><p id="d1e5872">All GOSAT data (from 2009) and GOSAT-2 data (from 2019) until the end of 2020 have been processed. Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">1</a> and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F2" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2</a> show the final number of valid FOCAL data as a function of time for the different products. The numbers are different for each product because of the individual filtering (see above). For comparison, the numbers for the v1.0 <span class="inline-formula">XCO<sub>2</sub></span> products are also shown. Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">1</a>a compares the number of yearly GOSAT FOCAL <span class="inline-formula">XCO<sub>2</sub></span> data with other available GOSAT data products from SRON, the University of Leicester (UoL), NIES and the NASA ACOS v9 product. A similar comparison is shown in Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">1</a>b for <span class="inline-formula">XCH<sub>4</sub></span> full-physics and proxy products. The resulting amount of data for the GOSAT FOCAL water vapour products is shown in Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F2" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2</a>a.</p><p id="d1e5919">The yield of valid FOCAL products was improved in v3.0 compared to v1.0. The number of valid FOCAL <span class="inline-formula">XCO<sub>2</sub></span> and methane results exceeds those of all other GOSAT data sets. Note that the increase in data yield from v1.0 to v3.0 is actually larger over water (about 60 % for 2019) than over land surfaces (about 30 % for 2019). The main reason for this increase is the improved post-processing quality filtering procedure and – especially for water vapour – also relaxations in the latitudinal and solar zenith angle filtering during pre-processing.</p><p id="d1e5933">In general, the number of GOSAT data increases for all products with time, with typically more data after 2015. As discussed in <span class="cit" id="xref_text.81"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>, this is related to optimised GOSAT operations especially resulting in more data over water.</p><p id="d1e5939">In principle, GOSAT-2 should provide more valid data than GOSAT, because GOSAT-2 uses an “intelligent pointing” procedure to avoid cloudy scenes. However, although the total number of GOSAT-2 FOCAL products (see Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F2" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2</a>b) was also improved, it is still lower than for GOSAT. This is because a larger fraction of data are already removed during the basic filtering due to larger residuals/less convergence. This hints at possible issues with the radiometric calibration or an incomplete instrument model used by FOCAL, neglecting important instrument features, e.g. currently unconsidered effects of remaining polarisation sensitivities of the instrument.</p><div class="sec"><h2 id="Ch1.S4.SS1"><span class="label">4.1</span> Global maps</h2> <p id="d1e5952">For each of the different data products, an example map comprising a mean for April 2019, gridded to 5<span class="inline-formula"><sup>∘</sup></span><span class="inline-formula">×</span> 5<span class="inline-formula"><sup>∘</sup></span>, is shown in Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F3" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">3</a> to <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F8" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">8</a> for GOSAT and GOSAT-2. In all maps, grid points that were only based on a single measurement have been omitted to avoid outliers. The spatial patterns of <span class="inline-formula">XCO<sub>2</sub></span>, methane, water vapour and <span class="inline-formula"><i>δ</i>D</span> look very similar for GOSAT<span id="page3410"></span> and GOSAT-2. GOSAT-2 data show in general fewer gaps over the oceans but with smaller latitudinal coverage. The latter is due to the currently applied RSR filtering for GOSAT-2, which especially removes data over water surfaces. Note that over the year the spatial range of valid data varies according to solar illumination conditions.</p> <div class="fig" id="Ch1.F3"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f03-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f03" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f03-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f03-thumb.png" data-width="2067" data-height="2877"></a><div class="caption"><p id="d1e6007"><strong class="caption-number">Figure 3</strong>Maps of gridded <span class="inline-formula">XCO<sub>2</sub></span> data for April 2019: <strong>(a)</strong> GOSAT; <strong>(b)</strong> GOSAT-2.</p></div><p class="downloads"></p></div> <p id="d1e6033">The <span class="inline-formula">XCO<sub>2</sub></span> data show higher values in the Northern Hemisphere than in the Southern Hemisphere as expected during springtime. This is because plants absorb more <span class="inline-formula">XCO<sub>2</sub></span> during growing season (i.e. hemispheric summer and autumn).</p> <p id="d1e6059">For methane, the known source regions in the USA, Africa and Asia are clearly visible, as well as the inter-hemispheric gradient. The spatial coverage of the proxy product is much larger than for the full-physics product, especially at higher latitudes. This is due to the relaxed filtering for the proxy product.</p> <div class="fig" id="Ch1.F4"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f04-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f04" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f04-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f04-thumb.png" data-width="2067" data-height="2877"></a><div class="caption"><p id="d1e6064"><strong class="caption-number">Figure 4</strong>Maps of gridded <span class="inline-formula">XCH<sub>4</sub></span> data for April 2019: <strong>(a)</strong> GOSAT; <strong>(b)</strong> GOSAT-2.</p></div><p class="downloads"></p></div> <p id="d1e6090">Water vapour (<span class="inline-formula">XH<sub>2</sub>O</span>) also shows the expected behaviour: large values in the tropics and lower values at higher latitudes. The observed spatial distribution of <span class="inline-formula"><i>δ</i>D</span> is in line with the maps shown in <span class="cit" id="xref_text.82"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx17" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Frankenberg et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx17" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2013</a>)</span>. All <span class="inline-formula"><i>δ</i>D</span> values are in the expected range (about 0 to <span class="inline-formula">−300</span> <span class="inline-formula">‰</span>); they also decrease from the tropics to higher northern and southern latitudes. This is because water vapour generated in the tropics by strong evaporation is transported to higher latitudes, during which the heavier <span class="inline-formula">HDO</span> decreases more rapidly via precipitation than <span class="inline-formula">H<sub>2</sub>O</span>.</p> <p id="d1e6169">For GOSAT-2, there are also data for carbon monoxide (<span class="inline-formula">XCO</span>) and <span class="inline-formula">XN<sub>2</sub>O</span>. In the <span class="inline-formula">XCO</span> map the expected source regions in China, Indonesia and Africa (fossil fuel combustion, biomass burning) are apparent over the otherwise quite smooth and constant background. The transport of <span class="inline-formula">XCO</span> from the equatorial African fire regions to the west over the Atlantic Ocean due to the trade winds is clearly visible, as is some transport from Asia to the Pacific.</p> <p id="d1e6209">The <span class="inline-formula">XN<sub>2</sub>O</span> product shows an overall decrease of the background <span class="inline-formula">XN<sub>2</sub>O</span> from the tropics to higher latitudes on the order of 15 <span class="inline-formula">ppb</span>. Such gradients were also observed by the IASI (Infrared Atmospheric Sounding Interferometer) instrument on Metop <span class="cit" id="xref_paren.83">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Barret et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>; however, we see larger differences. This could be related to the sampling of the <span class="inline-formula">XN<sub>2</sub>O</span> data.</p><div class="fig" id="Ch1.F5"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f05-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f05" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f05-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f05-thumb.png" data-width="2067" data-height="2877"></a><div class="caption"><p id="d1e6265"><strong class="caption-number">Figure 5</strong>Maps of gridded <span class="inline-formula">XCH<sub>4</sub></span> Proxy data for April 2019: <strong>(a)</strong> GOSAT; <strong>(b)</strong> GOSAT-2.</p></div><p class="downloads"></p></div> <div class="fig" id="Ch1.F6"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f06-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f06" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f06-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f06-thumb.png" data-width="2067" data-height="2865"></a><div class="caption"><p id="d1e6293"><strong class="caption-number">Figure 6</strong>Maps of gridded <span class="inline-formula">XH<sub>2</sub>O</span> data for April 2019: <strong>(a)</strong> GOSAT; <strong>(b)</strong> GOSAT-2.</p></div><p class="downloads"></p></div> <div class="fig" id="Ch1.F7"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f07-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f07" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f07-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f07-thumb.png" data-width="2067" data-height="2877"></a><div class="caption"><p id="d1e6323"><strong class="caption-number">Figure 7</strong>Maps of gridded <span class="inline-formula"><i>δ</i>D</span> data for April 2019: <strong>(a)</strong> GOSAT; <strong>(b)</strong> GOSAT-2.</p></div><p class="downloads"></p></div> <div class="fig" id="Ch1.F8"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f08-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f08" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f08-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f08-thumb.png" data-width="2067" data-height="2877"></a><div class="caption"><p id="d1e6350"><strong class="caption-number">Figure 8</strong>Maps of gridded GOSAT-2 data for April 2019: <strong>(a)</strong> <span class="inline-formula">XCO</span>; <strong>(b)</strong> <span class="inline-formula">XN<sub>2</sub>O</span>.</p></div><p class="downloads"></p></div> <p id="d1e6387">Furthermore, the IASI data shown in <span class="cit" id="xref_text.84"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Barret et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span> refer to the mid-troposphere over the ocean only, whereas the GOSAT-2 FOCAL data are total column averages over all surfaces. The latitudinal <span class="inline-formula">XN<sub>2</sub>O</span> gradient can, in principle, be explained by the variation of the tropopause height. As most of the <span class="inline-formula">XN<sub>2</sub>O</span> is contained (and well mixed) in the troposphere, the total column average is larger in the tropics (where the tropopause is high) than at higher latitudes. We also see increased <span class="inline-formula">XN<sub>2</sub>O</span> over central Africa. This is also visible in IASI data and probably related to convection <span class="cit" id="xref_paren.85">(see <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx52" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Ricaud et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx52" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2009</a>)</span>.</p> </div><span id="page3411"></span><div class="sec"><h2 id="Ch1.S4.SS2"><span class="label">4.2</span> Time series</h2> <p id="d1e6445">Time series of all GOSAT FOCAL data products for different latitudinal regions are depicted in Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F9" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">9</a>. These plots show the expected temporal behaviour: a seasonal cycle is visible in all data sets; amplitudes and/or phase differ for northern and southern latitudes with usually more variability in the north.</p> <p id="d1e6450">The GOSAT FOCAL <span class="inline-formula">XCO<sub>2</sub></span> results are shown in Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F9" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">9</a>a. The overall increase of <span class="inline-formula">XCO<sub>2</sub></span> from around 380 <span class="inline-formula">ppm</span> in 2009 to about 415 <span class="inline-formula">ppm</span> in 2020 is clearly visible, as well as an overlaying seasonal variation, which is most pronounced in the Northern Hemisphere with a minimum in summer due to vegetational growth. In the Southern Hemisphere, the seasonality of <span class="inline-formula">XCO<sub>2</sub></span> is shifted by 6 months but much lower since there are less land masses than in the north. The global variation is very similar to the tropical one.</p> <p id="d1e6505">The methane full-physics and proxy products show a similar temporal variation with increasing <span class="inline-formula">XCH<sub>4</sub></span> due to larger anthropogenic contributions (about 10 <span class="inline-formula">ppb</span> per year, which is in line with recent annual changes from NOAA ground-based measurements; see <span class="uri"><a href="https://gml.noaa.gov/ccgg/trends_ch4/" target="_blank">https://gml.noaa.gov/ccgg/trends_ch4/</a></span>, last access: 11 January 2022). Small differences between the average <span class="inline-formula">XCH<sub>4</sub></span> full-physics and the proxy products can be explained by the broader spatial coverage of the proxy product.</p> <p id="d1e6541"><span id="page3412"></span>For water vapour (<span class="inline-formula">XH<sub>2</sub>O</span>), the seasonal cycles in the Northern Hemisphere and Southern Hemisphere are shifted by about 6 months, in line with the seasonal shift of the intertropical convergence zone (ITCZ). On the global scale, these seasonal variations largely average out. Some change in the seasonal cycle of <span class="inline-formula">XH<sub>2</sub>O</span> is seen after 2015. This is probably related to the increased number of GOSAT data (especially over ocean) after 2015 (see Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">1</a>), which changes the sampling. Taking this into account, no clear trend is visible in the GOSAT water vapour data from 2009 to 2020, although there is some indication for a slow increase with time. This is in line with results from other data sets <span class="cit" id="xref_paren.86">(see e.g. <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx5" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Borger et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx5" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2022</a>, and references therein)</span>.</p> <p id="d1e6580">Average values of <span class="inline-formula"><i>δ</i>D</span> vary between about <span class="inline-formula">−180</span> <span class="inline-formula">‰</span> and <span class="inline-formula">−120</span> <span class="inline-formula">‰</span>. As for water vapour, seasonal variations are small in the global average, but year-to-year variations in the seasonal cycle are larger for <span class="inline-formula"><i>δ</i>D</span>. Especially note that the peaks in July 2012 in the Southern Hemisphere and in December 2018 in the Northern Hemisphere are due to very few data in these regions in these months.</p> <p id="d1e6640">The GOSAT-2 time series (see Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F10" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">10</a>) show similar temporal variations to the GOSAT data, but of course, they only cover the years 2019 and 2020.</p> <div class="fig" id="Ch1.F9"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f09-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f09" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f09-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f09-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f09-high-res.pdf" data-width="2067" data-height="2123"></a><div class="caption"><p id="d1e6647"><strong class="caption-number">Figure 9</strong>GOSAT time series. NH = Northern Hemisphere (<span class="inline-formula">></span> 25<span class="inline-formula"><sup>∘</sup></span> N). TRO = tropics (25<span class="inline-formula"><sup>∘</sup></span> S–25<span class="inline-formula"><sup>∘</sup></span> N). SH = Southern Hemisphere (<span class="inline-formula"><</span> 25<span class="inline-formula"><sup>∘</sup></span> S). <strong>(a)</strong> <span class="inline-formula">XCO<sub>2</sub></span>; <strong>(b)</strong> <span class="inline-formula">XCH<sub>4</sub></span> full-physics product; <strong>(c)</strong> <span class="inline-formula">XCH<sub>4</sub></span> proxy product; <strong>(d)</strong> <span class="inline-formula">XH<sub>2</sub>O</span>; <strong>(e)</strong> <span class="inline-formula"><i>δ</i>D</span>.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f09-high-res.pdf" target="_blank">Download</a></p></div> <div class="fig" id="Ch1.F10"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f10-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f10" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f10-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f10-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f10-high-res.pdf" data-width="2067" data-height="3009"></a><div class="caption"><p id="d1e6781"><strong class="caption-number">Figure 10</strong>GOSAT-2 time series. NH = Northern Hemisphere (<span class="inline-formula">></span> 25<span class="inline-formula"><sup>∘</sup></span> N). TRO = tropics (25<span class="inline-formula"><sup>∘</sup></span> S–25<span class="inline-formula"><sup>∘</sup></span> N). SH = Southern Hemisphere (<span class="inline-formula"><</span> 25<span class="inline-formula"><sup>∘</sup></span> S). <strong>(a)</strong> <span class="inline-formula">XCO<sub>2</sub></span>; <strong>(b)</strong> <span class="inline-formula">XCH<sub>4</sub></span> full-physics product; <strong>(c)</strong> <span class="inline-formula">XCH<sub>4</sub></span> proxy product; <strong>(d)</strong> <span class="inline-formula">XH<sub>2</sub>O</span>; <strong>(e)</strong> <span class="inline-formula"><i>δ</i>D</span>; <strong>(f)</strong> <span class="inline-formula">XCO</span>; <strong>(g)</strong> <span class="inline-formula">XN<sub>2</sub>O</span>.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f10-high-res.pdf" target="_blank">Download</a></p></div> <div class="fig" id="Ch1.F11"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f11-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f11" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f11-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f11-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f11.png" data-width="1900" data-height="1780"></a><div class="caption"><p id="d1e6944"><strong class="caption-number">Figure 11</strong>Overview of comparison results between different GOSAT <span class="inline-formula">XCO<sub>2</sub></span> products and TCCON data: scatter and bias for different TCCON stations. Note that the mean station bias has been subtracted to better illustrate the local station differences. See Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a> for a summary of all TCCON validation results.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f11.png" target="_blank">Download</a></p></div> <div class="fig" id="Ch1.F12"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f12-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f12" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f12-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f12-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f12.png" data-width="1781" data-height="1800"></a><div class="caption"><p id="d1e6968"><strong class="caption-number">Figure 12</strong>Same as Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F11" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">11</a> but for GOSAT <span class="inline-formula">XCH<sub>4</sub></span> full-physics and proxy products.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f12.png" target="_blank">Download</a></p></div> <p id="d1e6990">Across different latitudes, GOSAT-2 <span class="inline-formula">XCO</span> shows similar values and seasonal variations, except in the Southern Hemisphere where <span class="inline-formula">XCO</span> is on average about 30 <span class="inline-formula">ppb</span> lower than in the Northern Hemisphere, probably because most sources are around the Equator or in the Northern Hemisphere extra-tropics.</p> <p id="d1e7017">The GOSAT-2 <span class="inline-formula">XN<sub>2</sub>O</span> also shows some seasonal variations of up to about 8 <span class="inline-formula">ppb</span> peak-to-peak. However, this seasonality is at least partly a sampling effect. The background <span class="inline-formula">XN<sub>2</sub>O</span>, as shown in Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F8" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">8</a>b, comprises larger values in the tropics than at higher latitudes. Because of the varying latitudinal coverage of GOSAT-2 ocean data throughout the year, the regions outside the tropics are not covered during all seasons, which introduces an apparent variation in the averages. This effect in principle applies to all data, but it is especially pronounced for <span class="inline-formula">XN<sub>2</sub>O</span>, for which other spatial variations are low. In the tropics, the <span class="inline-formula">XN<sub>2</sub>O</span> data are always high, and the variations are much smaller. In fact, we see a slight increase in <span class="inline-formula">XN<sub>2</sub>O</span> of about 1 <span class="inline-formula">ppb</span> per year, which is about what is expected from ground-based measurements (see growth rate plots on the NOAA Global Monitoring Laboratory website; <span class="uri"><a href="https://gml.noaa.gov/hats/combined/N2O.html" target="_blank">https://gml.noaa.gov/hats/combined/N2O.html</a></span>, last access: 30 June 2021). This result is also in line with IASI data <span class="cit" id="xref_paren.87">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Barret et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>.</p> </div><span id="page3413"></span><div class="sec"><h2 id="Ch1.S4.SS3"><span class="label">4.3</span> TCCON comparisons</h2> <p id="d1e7119">To assess the quality of the data, for each GOSAT and GOSAT-2 FOCAL product we perform a comparison with TCCON data using the same procedure as in <span class="cit" id="xref_text.88"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>; see also <span class="cit" id="xref_text.89"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx51" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Reuter et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx51" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2020</a>)</span> and <span class="cit" id="xref_text.90"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx47" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Reuter and Hilker</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx47" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2022</a>)</span> for details.</p> <p id="d1e7131">For most gases, we also use the same collocation criteria: a maximum time difference of 2 <span class="inline-formula">h</span>, a maximum spatial distance of 500 <span class="inline-formula">km</span> and a maximum surface elevation difference of 250 <span class="inline-formula">m</span> between satellite and ground-based measurement. However, for water vapour and carbon monoxide these limits are reduced to 1 <span class="inline-formula">h</span> time difference and 150 <span class="inline-formula">km</span> spatial distance to account for their higher variability. We only include stations with a minimum of 50 data points.</p> <p id="d1e7174">For <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span>, we also perform comparisons with other available GOSAT products from SRON, the University of Leicester, NASA (ACOS v9) and NIES.</p> <p id="d1e7199">From the comparisons, we derive the following main quantities <span class="cit" id="xref_paren.91">(related formulas are given in <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx47" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Reuter and Hilker</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx47" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2022</a>)</span>: </p><ul><li> <p id="d1e7209">The first is mean station bias, defined as the mean of all biases at each station; this can be interpreted as a global offset to all stations.</p></li><li> <p id="d1e7213">The second is station-to-station bias, defined as the standard deviation of the individual station biases. This can be interpreted as regional bias.</p></li><li> <p id="d1e7217">The third is mean scatter, defined as the square root of the mean of the variances at each station. This is a measure for the single sounding precision.</p></li><li> <p id="d1e7221">And the fourth is seasonal bias, defined as the standard deviation (rms) of the seasonal variation of the difference FOCAL–TCCON at each station. This is equivalent to a temporal bias.</p></li></ul><p id="d1e7199-3"> Figures <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F11" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">11</a> and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F12" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">12</a> show the results from the TCCON validation for all GOSAT <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span> (full-physics and proxy) products from the different retrievals. The validation for these products was performed using the same subset of stations for all data products of each gas, which allows for a direct comparison of the results. In addition, Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F13" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">13</a> and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F14" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">14</a> show the TCCON validation results (bias and scatter) for each of the FOCAL v3.0 GOSAT and GOSAT-2 products (including the FOCAL data from Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F11" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">11</a> and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F12" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">12</a>). We also use here the same subset of stations for the GOSAT-2 <span class="inline-formula">XCH<sub>4</sub></span> full-physics and proxy products. Example time series for the TCCON station Lamont (USA) are shown in Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F15" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">15</a> and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F16" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">16</a>. This station was selected as it provides good temporal coverage of TCCON data also for the GOSAT-2 time frame (2019–2020). All results of the comparisons are summarised in Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a>.</p> <span class="tableCitations"></span><div class="table-wrap" id="Ch1.T6"><div class="caption"><p id="d1e7282"><strong class="caption-number">Table 6</strong>Results from TCCON comparisons. <span class="inline-formula"><i>N</i><sub>stations</sub></span> denotes the number of TCCON stations involved in the comparison, <span class="inline-formula"><i>N</i><sub>data</sub></span> is the number of co-located data points. All products are full-physics products except for those marked as “Proxy”.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t06.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t06-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t06-web.png" data-width="2067" data-height="1917" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t06.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t06.xlsx"></a><div class="table-wrap-foot"><p id="d1e7307"><span class="inline-formula"><sup>∗</sup></span> <span class="inline-formula">XCH<sub>4</sub></span> Proxy validated together with full-physics product, i.e. for same subset of TCCON stations.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t06.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t06.xlsx" target="_blank">Download XLSX</a></p></div> <p id="d1e8415">The mean station bias is mainly given for reference, because it is usually not relevant for applications that are only interested in the spatial and temporal gradients of the gas (like for <span class="inline-formula">XCO<sub>2</sub></span>). The quantities station-to-station bias, seasonal bias and mean scatter are more important as they<span id="page3415"></span> describe the quality of regional and/or temporal gradients, which are, for example, needed to quantify potential sources and sinks. The seasonal bias is derived from a trend model fit; therefore, the corresponding values for GOSAT-2 are less reliable, because the time interval is only about 2 years. The number of stations and data points used in the comparison depend on the different products, the collocation criteria and the length of the time series. Therefore, there are many fewer collocations for GOSAT-2. The <span class="inline-formula">XCH<sub>4</sub></span> proxy products, as well as the <span class="inline-formula">XH<sub>2</sub>O</span> and <span class="inline-formula">XCO</span> products, have the largest number of collocations because of the relaxed filtering.</p> <div class="fig" id="Ch1.F13"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f13-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f13" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f13-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f13-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f13.png" data-width="1005" data-height="782"></a><div class="caption"><p id="d1e8463"><strong class="caption-number">Figure 13</strong>Bias of FOCAL data products for GOSAT (blue) and GOSAT-2 (orange) at different TCCON stations. Involved stations for each product are marked by a yellow background. Note that small biases (close to zero) may not be visible in the plot. The mean station bias has been subtracted to better illustrate the local station differences. See Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a> for a summary of all TCCON validation results.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f13.png" target="_blank">Download</a></p></div> <div class="fig" id="Ch1.F14"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f14-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f14" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f14-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f14-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f14.png" data-width="1005" data-height="782"></a><div class="caption"><p id="d1e8476"><strong class="caption-number">Figure 14</strong>Scatter of FOCAL data products for GOSAT (blue) and GOSAT-2 (orange) at different TCCON stations. Involved stations for each product are marked by a yellow background. See Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a> for a summary of all TCCON validation results.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f14.png" target="_blank">Download</a></p></div> <div class="sec"><h3 id="Ch1.S4.SS3.SSS1"><span class="label">4.3.1</span> <span class="inline-formula">XCO<sub>2</sub></span> results versus TCCON</h3> <p id="d1e8505">For GOSAT FOCAL v3.0, the <span class="inline-formula">XCO<sub>2</sub></span> station-to-station bias is 0.51 <span class="inline-formula">ppm</span>, and the mean scatter is 2.19 <span class="inline-formula">ppm</span>, as given by the pink numbers at the bottom of Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F11" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">11</a> and in Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a>.</p> <p id="d1e8539">While the bias is slightly reduced, the scatter is slightly larger than for v1.0 <span class="cit" id="xref_paren.92">(0.56 <span class="inline-formula">ppm</span>, 1.89 <span class="inline-formula">ppm</span>; see <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Noël et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx39" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>. This higher scatter is still acceptable, noting the increased number of data points, which always increases the scatter, and an estimated 1<span class="inline-formula"><i>σ</i></span> TCCON uncertainty of 0.4 <span class="inline-formula">ppm</span> for <span class="inline-formula">XCO<sub>2</sub></span> <span class="cit" id="xref_paren.93">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx71" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wunch et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx71" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2010</a>)</span>. Note that this relation between scatter and number of data points is due to the filtering, which is based on reducing the local variance by removing data points (see above). The FOCAL values are also in quite good agreement with those from the other data sets but still do not reach the low bias and scatter of the NASA ACOS v9 product (0.44 and 1.66 <span class="inline-formula">ppm</span>) as given in dark grey colour at the bottom of Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F11" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">11</a>.</p> <div class="fig" id="Ch1.F15"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f15-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f15" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f15-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f15-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f15.png" data-width="2067" data-height="1654"></a><div class="caption"><p id="d1e8605"><strong class="caption-number">Figure 15</strong>Example time series of TCCON and GOSAT FOCAL data at Lamont (station code oc). <strong>(a)</strong> <span class="inline-formula">XCO<sub>2</sub></span>; <strong>(b)</strong> <span class="inline-formula">XCH<sub>4</sub></span> full-physics product; <strong>(c)</strong> <span class="inline-formula">XCH<sub>4</sub></span> proxy product; <strong>(d)</strong> <span class="inline-formula">XH<sub>2</sub>O</span>; <strong>(e)</strong> <span class="inline-formula"><i>δ</i>D</span>.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f15.png" target="_blank">Download</a></p></div> <p id="d1e8687">The GOSAT-2 <span class="inline-formula">XCO<sub>2</sub></span> comparison results for v1.0 were considered less reliable because of the shortness of the time series (less than 1 year). For v3.0, we now have almost 2 years of data and, due to the updated product version, also a higher data yield, which results in almost 10 times more collocations with TCCON than in v1.0. As can be seen from Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a>, we now get a station-to-station bias of 0.91 <span class="inline-formula">ppm</span>, which is still slightly higher compared to GOSAT but lower than in v1.0 (1.14 <span class="inline-formula">ppm</span>), For GOSAT-2, the biases are typically negative for southern stations and positive for northern stations (see Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F13" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">13</a>). The derived mean scatter of 2.02 <span class="inline-formula">ppm</span> (see Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F14" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">14</a>) is somewhat lower than the v3.0 GOSAT value and slightly higher than the v1.0 scatter for GOSAT-2 (1.89 <span class="inline-formula">ppm</span>). As mentioned above, this is related to the different number of data points.</p> <p id="d1e8740"><span id="page3416"></span>The derived seasonal bias is low (0.33 <span class="inline-formula">ppm</span> for GOSAT, 0.62 <span class="inline-formula">ppm</span> for GOSAT-2; see Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a>). The seasonal variations of the TCCON data at Lamont are well reproduced by the GOSAT and GOSAT-2 FOCAL data with no apparent offset, but the satellite data show a larger scatter (see Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F15" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">15</a>a and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F16" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">16</a>a). The lower scatter of TCCON data is expected, because in general satellite instruments measure reflected sunlight as it passes twice through the atmosphere, while TCCON stations perform direct observation of the sun for which scattering is not relevant.</p> <div class="fig" id="Ch1.F16"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f16-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f16" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f16-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f16-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f16.png" data-width="2067" data-height="2211"></a><div class="caption"><p id="d1e8767"><strong class="caption-number">Figure 16</strong>Example time series of TCCON and GOSAT-2 FOCAL data at Lamont (station code oc). <strong>(a)</strong> <span class="inline-formula">XCO<sub>2</sub></span>; <strong>(b)</strong> <span class="inline-formula">XCH<sub>4</sub></span> full-physics product; <strong>(c)</strong> <span class="inline-formula">XCH<sub>4</sub></span> proxy product; <strong>(d)</strong> <span class="inline-formula">XH<sub>2</sub>O</span>; <strong>(e)</strong> <span class="inline-formula"><i>δ</i>D</span>; <strong>(f)</strong> <span class="inline-formula">XCO</span>; <strong>(g)</strong> <span class="inline-formula">XN<sub>2</sub>O</span>.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f16.png" target="_blank">Download</a></p></div> </div> <div class="sec"><h3 id="Ch1.S4.SS3.SSS2"><span class="label">4.3.2</span> <span class="inline-formula">XCH<sub>4</sub></span> results versus TCCON</h3> <p id="d1e8896">The FOCAL v3.0 full-physics <span class="inline-formula">XCH<sub>4</sub></span> product for GOSAT has a station-to-station bias of 4.3 <span class="inline-formula">ppb</span> (as given in pink at the bottom of Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F12" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">12</a>), which is similar to the estimated 1<span class="inline-formula"><i>σ</i></span> TCCON uncertainty from <span class="cit" id="xref_text.94"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx71" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wunch et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx71" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2010</a>)</span> of 3.5 <span class="inline-formula">ppb</span> and also compares well to the other data products. The value for the GOSAT FOCAL proxy product is 6.1 <span class="inline-formula">ppb</span>, which is about 1–2 <span class="inline-formula">ppb</span> higher than all other products but still in an acceptable range as it is better than the Copernicus systematic error threshold requirement of 10 <span class="inline-formula">ppb</span> and close to the breakthrough requirement of better than 5 <span class="inline-formula">ppb</span> <span class="cit" id="xref_paren.95">(see Table 3 in <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Buchwitz et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2021</a>)</span>. For GOSAT-2, FOCAL v3.0 has a station-to-station bias of 4.7 <span class="inline-formula">ppb</span> for the full-physics <span class="inline-formula">XCH<sub>4</sub></span> product and 6.2 <span class="inline-formula">ppb</span> for the proxy.</p> <p id="d1e9004">The mean scatter of the GOSAT and GOSAT-2 FOCAL <span class="inline-formula">XCH<sub>4</sub></span> product versus TCCON is around 12 <span class="inline-formula">ppb</span>, which is slightly lower than for the other data products. The seasonal bias for all GOSAT and GOSAT-2 products relative to TCCON is around 3 <span class="inline-formula">ppb</span> (Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a>). For both instruments, the temporal variations of the FOCAL full-physics and proxy <span class="inline-formula">XCH<sub>4</sub></span> products agree well with the Lamont TCCON data (see Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F15" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">15</a>b, c and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F16" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">16</a>b, c). In general, the FOCAL data are systematically lower by a few parts per billion (<span class="inline-formula">ppb</span>), which is in line with the observed mean station bias of around <span class="inline-formula">−3</span> to <span class="inline-formula">−6</span> <span class="inline-formula">ppb</span>; see Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a>.</p> </div> <div class="sec"><h3 id="Ch1.S4.SS3.SSS3"><span class="label">4.3.3</span> <span class="inline-formula">XH<sub>2</sub>O</span> results versus TCCON</h3> <p id="d1e9112">Since water vapour is highly variable, the comparison results depend strongly on the involved TCCON stations. Because of the less strict filter criteria for <span class="inline-formula">XH<sub>2</sub>O</span>, there are typically more data (and collocations) at higher latitudes than<span id="page3417"></span> for the other full-physics products. We get a similar mean scatter of about 300 <span class="inline-formula">ppm</span> for GOSAT and GOSAT-2 FOCAL <span class="inline-formula">XH<sub>2</sub>O</span>. The station-to-station bias is 116 <span class="inline-formula">ppm</span> for GOSAT and 152 <span class="inline-formula">ppm</span> for GOSAT-2, which is even lower than the TCCON uncertainty of 200 <span class="inline-formula">ppm</span> estimated by <span class="cit" id="xref_text.96"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx71" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wunch et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx71" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2010</a>)</span>. The seasonal bias for GOSAT-2 is 110 <span class="inline-formula">ppm</span>; for GOSAT, it is even smaller (66 <span class="inline-formula">ppm</span>); see Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a> for all values. The derived station-to-station biases and mean scatter values are in line with results derived for the OCO-2 FOCAL product <span class="cit" id="xref_paren.97">(206 and 293 ppm, respectively; see <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx49" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Reuter et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx49" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2017</a><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx49" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">a</a>)</span>. As also mentioned there, these high values can at least partly be attributed to the large natural variability of water vapour. This variability can also be seen in the time series at Lamont (Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F15" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">15</a>d and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F16" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">16</a>d), which show the same seasonal variations of around 4000 <span class="inline-formula">ppm</span> peak-to-peak for all data sets.</p> </div> <div class="sec"><h3 id="Ch1.S4.SS3.SSS4"><span class="label">4.3.4</span> <span class="inline-formula"><i>δ</i>D</span> results versus TCCON</h3> <p id="d1e9231">For <span class="inline-formula"><i>δ</i>D</span>, we get station-to-station biases of only 8.6 <span class="inline-formula">‰</span> for both instruments; the mean scatter is about 32 <span class="inline-formula">‰</span> for GOSAT and GOSAT-2. The seasonal bias for GOSAT is 6 <span class="inline-formula">‰</span>; the GOSAT-2 value is 13 <span class="inline-formula">‰</span> (Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a>). The mean station bias is quite large (around <span class="inline-formula">−83</span> <span class="inline-formula">‰</span> for GOSAT and GOSAT-2). This is slightly larger than corresponding values between about <span class="inline-formula">−20</span> <span class="inline-formula">‰</span> and <span class="inline-formula">−70</span> <span class="inline-formula">‰</span> derived from a GOSAT–TCCON comparison performed by <span class="cit" id="xref_text.98"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx4" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Boesch et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx4" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2013</a>)</span> for data between April 2009 and June 2011. Note that there is no uncertainty estimate available for the TCCON <span class="inline-formula"><i>δ</i>D</span> data, so all numbers given here should be treated with caution. The Lamont time series (Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F15" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">15</a>e and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F16" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">16</a>e) show a systematic offset between TCCON on GOSAT/GOSAT-2 in line with the mean station bias, but the seasonality is well reproduced, although the satellite data show a larger scatter.</p> </div> <span id="page3419"></span><div class="sec"><h3 id="Ch1.S4.SS3.SSS5"><span class="label">4.3.5</span> <span class="inline-formula">XCO</span> results versus TCCON</h3> <p id="d1e9368">The TCCON comparison for <span class="inline-formula">XCO</span> reveals a station-to-station bias of 4.3 <span class="inline-formula">ppb</span>, a mean scatter of 7.7 <span class="inline-formula">ppb</span> and a seasonal bias of 2.8 <span class="inline-formula">ppb</span> (Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a>). In fact, the <span class="inline-formula">XCO</span> bias and scatter vary strongly between TCCON stations (see Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F13" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">13</a> and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F14" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">14</a>), but the derived values agree quite well with the TCCON uncertainty for carbon monoxide of 2 <span class="inline-formula">ppb</span>. The data at Lamont (Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F16" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">16</a>f) show that the temporal variation of <span class="inline-formula">XCO</span> is well captured by the FOCAL product, but there is a systematic offset in line with the mean station bias of about 15 <span class="inline-formula">ppb</span>.</p> </div> <div class="sec"><h3 id="Ch1.S4.SS3.SSS6"><span class="label">4.3.6</span> <span class="inline-formula">XN<sub>2</sub>O</span> results versus TCCON</h3> <p id="d1e9466">The FOCAL <span class="inline-formula">XN<sub>2</sub>O</span> is a new data product that is so far not available from other groups performing retrievals on GOSAT-2 trace gas measurements. For <span class="inline-formula">XN<sub>2</sub>O</span>, we get from the TCCON comparison a station-to-station bias of 1.6 <span class="inline-formula">ppb</span> and a mean scatter of 4.0 <span class="inline-formula">ppb</span> (Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F13" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">13</a> and <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F14" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">14</a>). The seasonal bias is 1.6 <span class="inline-formula">ppb</span> (Table <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.T6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">6</a>). Since the corresponding 1<span class="inline-formula"><i>σ</i></span> TCCON uncertainty from <span class="cit" id="xref_text.99"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx71" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Wunch et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx71" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2010</a>)</span> is 1.5 <span class="inline-formula">ppb</span>, we consider this to be reasonable agreement. The values for <span class="inline-formula">XN<sub>2</sub>O</span> are similar to the expected local <span class="inline-formula">XN<sub>2</sub>O</span> variability of a few parts per billion (<span class="inline-formula">ppb</span>) <span class="cit" id="xref_paren.100">(see e.g. <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx18" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">García et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx18" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2018</a>)</span>, but it should be considered that the total column average has a larger variability than surface data due to variations in tropopause height. This can be seen from Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#Ch1.F16" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">16</a>g: both TCCON and GOSAT-2 observe total column seasonal variations with peak-to-peak differences of about 8 <span class="inline-formula">ppb</span>, which is in line with the time series results. There is no visible bias between TCCON and GOSAT-2, but the scatter of the GOSAT-2 data is larger.</p> </div> </div></div><span class="section4-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div class="sec conclusions" id="section5"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section5 .co-arrow-open,.section5-content" data-show="#section5 .co-arrow-closed,.section5-mobile-bottom-border"><div id="Ch1.S5" class="h1"><span class="label">5</span> Conclusions<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section5-content show-no-js hide-on-mobile-soft"><p id="d1e9605">An updated version (v3.0) of the FOCAL retrieval algorithm has been applied to GOSAT and GOSAT-2 measurements in the NIR and SWIR spectral regions. This results in a variety of trace gas products, all derived within one retrieval and at comparably low computational costs. For both GOSAT instruments, we determine full-physics products for carbon dioxide, methane, water vapour and <span class="inline-formula"><i>δ</i>D</span> as well as a proxy methane product. For GOSAT-2, also carbon monoxide and a nitrous oxide product are retrieved.</p><p id="d1e9618">Overall, the yield of valid data is improved in GOSAT and GOSAT-2 FOCAL v3.0. The number of <span class="inline-formula">XCO<sub>2</sub></span> full-physics data has increased by about 50 % for GOSAT and has even<span id="page3420"></span> doubled for GOSAT-2. This is mainly due to relaxations in the filtering of data and improved post-processing. The proxy methane, carbon monoxide and <span class="inline-formula">XH<sub>2</sub>O</span> products even have about 2 times more data than the full-physics products.</p><p id="d1e9645">The new GOSAT and GOSAT-2 products have been compared with ground-based TCCON data to get a first quality assessment. All FOCAL data agree with TCCON within the uncertainties of both data sets.</p><p id="d1e9648">The FOCAL <span class="inline-formula">XCO<sub>2</sub></span> data product is not only in line with TCCON but also with many other satellite data sets. A near-real-time version of this data set will be used in the Copernicus Atmospheric Monitoring Service (CAMS) as input for meteorological models. The FOCAL <span class="inline-formula">XCH<sub>4</sub></span> products fulfil the corresponding requirements of the EU/ESA Copernicus Earth observation programme. The FOCAL data sets also provide useful input for ensemble studies, which have shown that additional information about, for example, sources and sinks of greenhouse gases can be obtained by combination of different data sets <span class="cit" id="xref_paren.101">(see, for example, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx48" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Reuter et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx48" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2013</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx51" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2020</a>)</span>.</p><p id="d1e9679">The spatial distribution of all gases and their temporal variation look reasonable. We have presented the first results for a GOSAT-2 <span class="inline-formula">XN<sub>2</sub>O</span> product. We observe an <span class="inline-formula">XN<sub>2</sub>O</span> gradient between the tropics and higher latitudes of about 15 <span class="inline-formula">ppb</span> which can be explained by variations in the tropopause height. A similar gradient has been seen in IASI data.</p><p id="d1e9716">The accuracy of the GOSAT-2 FOCAL <span class="inline-formula">XN<sub>2</sub>O</span> is in the order of a few parts per billion (<span class="inline-formula">ppb</span>) for a single sounding. We<span id="page3421"></span> expect this to be improved by averaging of data such that, for example, monthly or annually gridded products can provide interesting information about <span class="inline-formula">XN<sub>2</sub>O</span>, especially since there are not many global satellite measurements available for this species.</p></div><span class="section5-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div class="app sec" id="section6"> <div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section6 .co-arrow-open,.section6-content" data-show="#section6 .co-arrow-closed,.section6-mobile-bottom-border"><div id="App1.Ch1.S1" class="h1"><span>Appendix A:</span> SLIMCO2 and SLIMCH4<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section6-content show-no-js hide-on-mobile-soft"><p id="d1e9764">The Simple cLImatological Model for atmospheric <span class="inline-formula">CO<sub>2</sub></span> or <span class="inline-formula">CH<sub>4</sub></span> (SLIMCO2 or SLIMCH4) has been developed to provide estimates of dry-air mole fraction profiles and column averages of atmospheric <span class="inline-formula">CO<sub>2</sub></span> or <span class="inline-formula">CH<sub>4</sub></span> with reasonable accuracy at minimum computational costs. A key application of SLIMCO2 or SLIMCH4 is to compute <span class="inline-formula">CO<sub>2</sub></span> or <span class="inline-formula">CH<sub>4</sub></span> a priori information for remote sensing algorithms, which is why it also provides estimates of the corresponding error covariance matrix which can be used, for example, by optimal estimation frameworks.</p><div class="fig" id="App1.Ch1.S1.F17"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f17-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f17" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f17-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f17-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f17.png" data-width="2067" data-height="2473"></a><div class="caption"><p id="d1e9836"><strong class="caption-number">Figure A1</strong>Global growth rates for <span class="inline-formula">CO<sub>2</sub></span> <strong>(a)</strong> and <span class="inline-formula">CH<sub>4</sub></span> <strong>(b)</strong>.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f17.png" target="_blank">Download</a></p></div><div class="fig" id="App1.Ch1.S1.F18"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f18-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f18" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f18-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f18-thumb.png" data-width="2067" data-height="1886"></a><div class="caption"><p id="d1e9875"><strong class="caption-number">Figure A2</strong>Example maps of SLIMCO2 <strong>(a)</strong> and SLIMCH4 <strong>(b)</strong> data. Panels <strong>(c)</strong> and <strong>(d)</strong> show corresponding data from the underlying models (CT2019B, TM5). The differences between the SLIM results and these model data are shown in panels <strong>(e)</strong> and <strong>(f)</strong>.</p></div><p class="downloads"></p></div><div class="fig" id="App1.Ch1.S1.F19"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f19-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f19" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f19-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f19-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f19.png" data-width="2067" data-height="771"></a><div class="caption"><p id="d1e9906"><strong class="caption-number">Figure A3</strong>Scatter plot of the data shown in Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F18" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A2</a>. <strong>(a)</strong> SLIMCO2 data vs. CT2019B; <strong>(b)</strong> SLIMCH4 vs. TM5. Symbol <span class="inline-formula"><i>σ</i></span> corresponds to the standard deviation of the difference, <span class="inline-formula"><i>δ</i></span> corresponds to the average bias and <span class="inline-formula"><i>ρ</i></span> is the Pearson correlation coefficient.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f19.png" target="_blank">Download</a></p></div><div class="fig" id="App1.Ch1.S1.F20"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f20-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f20" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f20-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f20-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f20.png" data-width="2067" data-height="1681"></a><div class="caption"><p id="d1e9947"><strong class="caption-number">Figure A4</strong>Error covariance matrices for SLIMCO2 <strong>(a)</strong> and SLIMCH4 <strong>(c)</strong> and corresponding error correlation matrices <strong>(b, d)</strong>.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f20.png" target="_blank">Download</a></p></div><p id="d1e9965">The climatology database of SLIMCO2 v2021 has been derived from 16 years (2003–2018) of <span class="inline-formula">CO<sub>2</sub></span> mole fraction data of NOAA's CarbonTracker model version CT2019B <span class="cit" id="xref_text.102"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx29" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Jacobson et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx29" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2020</a>)</span>. It has the same 3<span class="inline-formula"><sup>∘</sup></span> <span class="inline-formula">×</span> 2<span class="inline-formula"><sup>∘</sup></span> spatial resolution as the used global CarbonTracker model fields. Temporally, it covers 1 year sampled in 36 time steps, corresponding to a grid resolution of about 10 d. The climatology database of SLIMCH4 v2021 has been derived from 13 years (2000–2012) of TM5–4DVAR <span class="inline-formula">CH<sub>4</sub></span> mole fraction data <span class="cit" id="xref_paren.103">(<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx2" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Bergamaschi et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx2" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2013</a>)</span> with a spatial resolution of 6<span class="inline-formula"><sup>∘</sup></span> <span class="inline-formula">×</span> 4<span class="inline-formula"><sup>∘</sup></span>. Temporally, it is sampled in 36 time steps, just as with the climatology database of SLIMCO2 v2021. Both databases feature a height grid with 20 layers. The height gridding is done in a way that each layer consists of the same number of dry-air particles so that the column average can simply be computed by averaging the mole-fraction profile. When reading the climatology database, SLIM allows for either nearest neighbour or trilinear interpolation in longitude, latitude and day of year. Additionally, SLIM is able to convert the height gridding to the one that is used, e.g. for the FOCAL OCO-2 <span class="inline-formula">XCO<sub>2</sub></span> retrieval using five height layers for <span class="inline-formula">CO<sub>2</sub></span>.</p><p id="d1e10070">First, we computed the global mean XGAS (<span class="inline-formula">XCO<sub>2</sub></span> or <span class="inline-formula">XCH<sub>4</sub></span>) from the corresponding model for each 1 January (00:00 UTC) in the covered time period. In the next step, we went through all model time steps of the analysed period and subtracted the global mean XGAS, assuming linear growth within the years. Finally, we created the climatology databases by incrementally computing the average and standard deviation of the gases mole fraction of all growth-corrected model time steps falling into the 10 d temporal grid cells of the database. In this way, the created databases basically consist of growth-removed seasonal cycle anomalies.</p><div class="fig" id="App1.Ch1.S1.F21"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f21-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f21" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f21-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f21-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f21.png" data-width="2067" data-height="4336"></a><div class="caption"><p id="d1e10097"><strong class="caption-number">Figure A5</strong>Overview of TCCON validation results for SLIMCO2 <strong>(a)</strong> and SLIMCH4 <strong>(b)</strong>. The mean station bias has been subtracted to better illustrate the local station differences.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f21.png" target="_blank">Download</a></p></div><div class="fig" id="App1.Ch1.S1.F22"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f22-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f22" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f22-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f22-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f22.png" data-width="2067" data-height="2238"></a><div class="caption"><p id="d1e10115"><strong class="caption-number">Figure A6</strong>Time series of <span class="inline-formula">XCO<sub>2</sub></span> <strong>(a)</strong> and <span class="inline-formula">XCH<sub>4</sub></span> <strong>(b)</strong> from TCCON and SLIM at Lamont (station code oc).</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f22.png" target="_blank">Download</a></p></div><div class="fig" id="App1.Ch1.S1.F23"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f23-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f23" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f23-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f23-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f23-high-res.pdf" data-width="2067" data-height="3119"></a><div class="caption"><p id="d1e10154"><strong class="caption-number">Figure A7</strong>Variables selected for the GOSAT random forest bias correction and their relevance. <strong>(a, b)</strong> <span class="inline-formula">XCO<sub>2</sub></span>; <strong>(c, d)</strong> <span class="inline-formula">XCH<sub>4</sub></span>; <strong>(e, f)</strong> <span class="inline-formula">XCH<sub>4</sub></span> Proxy. Left and right columns are for land and water surfaces, respectively.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f23-high-res.pdf" target="_blank">Download</a></p></div><div class="fig" id="App1.Ch1.S1.F24"><a target="_blank" class="figure-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f24-web.png"><img alt="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f24" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f24-web.png" src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f24-thumb.png" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f24-high-res.pdf" data-width="2067" data-height="3083"></a><div class="caption"><p id="d1e10208"><strong class="caption-number">Figure A8</strong>Same as Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F23" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A7</a> but for GOSAT-2.</p></div><p class="downloads"><a class="triangle journal-contentLinkColor figure-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-f24-high-res.pdf" target="_blank">Download</a></p></div><p id="d1e10219">In addition to the created 4D data fields, the database contains a table of annual growth rates obtained from NOAA (<span class="uri"><a href="https://gml.noaa.gov/ccgg/trends/gr.html" target="_blank">https://gml.noaa.gov/ccgg/trends/gr.html</a></span>, last access: 3 July 2021). Currently, the implemented table covers the time periods 1959–2020 for <span class="inline-formula">CO<sub>2</sub></span> and 1984–2020 for <span class="inline-formula">CH<sub>4</sub></span>, but it can be extended if needed to improve the quality of SLIM estimates in years before or after these periods. Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F17" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A1</a> shows the NOAA annual mean growth rates for <span class="inline-formula">CO<sub>2</sub></span> and <span class="inline-formula">CH<sub>4</sub></span> computed from global marine surface data as stored in the database. As visible in the figure, the NOAA growth rate agrees well with the growth computed from the model data as described above.</p><p id="d1e10272">In the following, we describe how SLIM uses its database to estimate the <span class="inline-formula">CO<sub>2</sub></span> or <span class="inline-formula">CH<sub>4</sub></span> atmospheric dry-air mole fraction for a given longitude, latitude and time. The database has been generated as follows. First, SLIM computes an estimate of the global average mole fraction by linear interpolation in the accumulated growth rates database. Note that extrapolation to dates outside of the spanned period is done by assuming a 10-year average growth rate (dashed lines in Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F17" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A1</a>). This global average is added to the mole fraction anomaly interpolated from the corresponding 4D database field for the given longitude, latitude and day of year.</p><p id="d1e10300"><span id="page3423"></span>Figure <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F18" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A2</a> shows examples of a global <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span> map as read from the models (panels c and d) and in panels (a) and (b) for the corresponding maps of SLIM XGAS values. Since the SLIM layers are defined such that they all contain the same number of dry-air particles, the SLIM XGAS values can be computed as mean of all layer values. As one can also see in the difference maps (panels e and f), the large-scale patterns such as north–south gradient are well reproduced, and differences are mainly due the specific synoptic situation in the model field, which usually changes from year to year and which, therefore, cannot be reproduced by a simple climatology. For the example of <span class="inline-formula">CO<sub>2</sub></span>, the largest natural surface fluxes occur during the northern hemispheric growing season. Therefore, the largest deviations between CT2019B and SLIMCO2 occur in the Northern Hemisphere in Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F18" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A2</a>e.</p><p id="d1e10340">By comparing 1 million randomly selected profiles in the period 2003–2018, we computed that the SLIMCO2 <span class="inline-formula">XCO<sub>2</sub></span> is on average 0.1 <span class="inline-formula">ppm</span> lower than the corresponding CarbonTracker values, with a standard deviation of 0.57 <span class="inline-formula">ppm</span> and a correlation coefficient of 0.998 (see Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F19" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A3</a>a). The corresponding experiment for SLIMCH4 results in a mean difference of 3 <span class="inline-formula">ppb</span>, a standard deviation of the difference of 7.2 <span class="inline-formula">ppb</span> and a correlation coefficient of 0.989 (see Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F19" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A3</a>b).</p><p id="d1e10391">The error covariance matrix for the 5-layered SLIMCO2 profiles shown in Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F20" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A4</a>a shows the largest uncertainties in the lowermost layer (approx. 1000–800 <span class="inline-formula">hPa</span>), which is influenced strongest by the surface fluxes and the smallest uncertainties in the uppermost layer (approx. 200–0 <span class="inline-formula">hPa</span>) including the stratosphere. The largest error correlations exist between layers 1–4, whilst the uncertainties of layer 5 are relatively independent (Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F20" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A4</a>b). For <span class="inline-formula">CH<sub>4</sub></span>, the correlation structure is similar (Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F20" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A4</a>d), but the largest uncertainties are observed in the stratosphere (Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F20" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A4</a>c).</p><p id="d1e10430">Also the comparison of SLIM with corresponding TCCON XGAS measurements show good overall agreement (Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F21" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A5</a> and <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F22" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A6</a>). Analysed in the same way as done in the validation study by <span class="cit" id="xref_text.104"><a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx51" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Reuter et al.</a> (<a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx51" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2020</a>)</span>, we find <span class="inline-formula">CO<sub>2</sub></span> biases with a station-to-station standard deviation of 0.57 <span class="inline-formula">ppm</span> and an average scatter of 1.14 <span class="inline-formula">ppm</span> with respect to TCCON (Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F21" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A5</a>a). For <span class="inline-formula">CH<sub>4</sub></span>, we find biases with a station-to-station standard deviation of 7.5 <span class="inline-formula">ppb</span> and an average scatter of 10.6 <span class="inline-formula">ppb</span> (Fig. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F21" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A5</a>b). Especially for <span class="inline-formula">XCO<sub>2</sub></span>, these values are similar to values found for comparisons of satellite retrieval data products with TCCON <span class="cit" id="xref_paren.105">(e.g. <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx51" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Reuter et al.</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#bib1.bibx51" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">2020</a>)</span>.</p><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T7"><div class="caption"><p id="d1e10519"><strong class="caption-number">Table A1</strong><span class="inline-formula">XCO<sub>2</sub></span> filter variables and limits for GOSAT. “–” means that no limit is applied. Except for the solar zenith angle limits, the variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t07.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t07-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t07-web.png" data-width="2067" data-height="974" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t07.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t07.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t07.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t07.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T8"><div class="caption"><p id="d1e11605"><strong class="caption-number">Table A2</strong><span class="inline-formula">XCH<sub>4</sub></span> filter variables and limits for GOSAT. “–” means that no limit is applied. Except for the solar zenith angle limits, the variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t08.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t08-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t08-web.png" data-width="2067" data-height="1013" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t08.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t08.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t08.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t08.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T9"><div class="caption"><p id="d1e12481"><strong class="caption-number">Table A3</strong><span class="inline-formula">XCH<sub>4</sub></span> Proxy filter variables and limits for GOSAT. “–” means that no limit is applied. Except for the solar zenith angle limits, the variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t09.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t09-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t09-web.png" data-width="2067" data-height="889" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t09.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t09.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t09.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t09.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T10"><div class="caption"><p id="d1e13081"><strong class="caption-number">Table A4</strong><span class="inline-formula">XH<sub>2</sub>O</span> filter variables and limits for GOSAT. “–” means that no limit is applied. The variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t10.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t10-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t10-web.png" data-width="2067" data-height="655" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t10.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t10.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t10.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t10.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T11"><div class="caption"><p id="d1e13357"><strong class="caption-number">Table A5</strong><span class="inline-formula"><i>δ</i>D</span> filter variables and limits for GOSAT. “–” means that no limit is applied. Except for the solar zenith angle limits, the variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t11.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t11-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t11-web.png" data-width="2067" data-height="748" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t11.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t11.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t11.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t11.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T12"><div class="caption"><p id="d1e13900"><strong class="caption-number">Table A6</strong><span class="inline-formula">XCO<sub>2</sub></span> filter variables and limits for GOSAT-2. “–” means that no limit is applied. Except for the solar zenith angle limits, the variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t12.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t12-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t12-web.png" data-width="2067" data-height="990" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t12.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t12.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t12.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t12.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T13"><div class="caption"><p id="d1e14756"><strong class="caption-number">Table A7</strong><span class="inline-formula">XCH<sub>4</sub></span> filter variables and limits for GOSAT-2. “–” means that no limit is applied. Except for the solar zenith angle limits, the variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t13.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t13-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t13-web.png" data-width="2067" data-height="980" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t13.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t13.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t13.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t13.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T14"><div class="caption"><p id="d1e15594"><strong class="caption-number">Table A8</strong><span class="inline-formula">XCH<sub>4</sub></span> Proxy filter variables and limits for GOSAT-2. “–” means that no limit is applied. Except for the solar zenith angle limits, the variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t14.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t14-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t14-web.png" data-width="2067" data-height="916" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t14.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t14.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t14.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t14.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T15"><div class="caption"><p id="d1e16216"><strong class="caption-number">Table A9</strong><span class="inline-formula">XH<sub>2</sub>O</span> filter variables and limits for GOSAT-2. “–” means that no limit is applied. The variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t15.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t15-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t15-web.png" data-width="2067" data-height="679" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t15.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t15.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t15.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t15.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T16"><div class="caption"><p id="d1e16568"><strong class="caption-number">Table A10</strong><span class="inline-formula"><i>δ</i>D</span> filter variables and limits for GOSAT-2. “–” means that no limit is applied. Except for the solar zenith angle limits, the variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t16.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t16-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t16-web.png" data-width="2067" data-height="750" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t16.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t16.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t16.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t16.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T17"><div class="caption"><p id="d1e17076"><strong class="caption-number">Table A11</strong><span class="inline-formula">XCO</span> filter variables and limits for GOSAT-2. “–” means that no limit is applied. Except for the solar zenith angle limits, the variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t17.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t17-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t17-web.png" data-width="2067" data-height="736" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t17.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t17.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t17.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t17.xlsx" target="_blank">Download XLSX</a></p></div><span class="tableCitations"></span><div class="table-wrap" id="App1.Ch1.S1.T18"><div class="caption"><p id="d1e17585"><strong class="caption-number">Table A12</strong><span class="inline-formula">XN<sub>2</sub>O</span> filter variables and limits for GOSAT-2. “–” means that no limit is applied. Except for the solar zenith angle limits, the variables are ordered by their relevance, i.e. by the number of data filtered out.</p></div><a class="table-link" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t18.png" target="_blank"><img src="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t18-thumb.png" target="_blank" data-webversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t18-web.png" data-width="2067" data-height="1026" data-printversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t18.png" data-csvversion="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t18.xlsx"></a><p class="downloads"><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t18.png" target="_blank">Download Print Version</a><span class="hide-on-mobile download-separator"> | </span><a class="triangle journal-contentLinkColor table-download" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022-t18.xlsx" target="_blank">Download XLSX</a></p></div></div><span class="section6-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div class="app sec" id="section7"> <div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section7 .co-arrow-open,.section7-content" data-show="#section7 .co-arrow-closed,.section7-mobile-bottom-border"><div id="App1.Ch1.S2" class="h1"><span>Appendix B:</span> Filter variables and bias correction parameters<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section7-content show-no-js hide-on-mobile-soft"><p id="d1e18311">Tables <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.T7" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A1</a> to <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.T18" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A12</a> show the filter settings for the various GOSAT and GOSAT-2 products. Figs. <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F23" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A7</a> and <a href="https://amt.copernicus.org/articles/15/3401/2022/#App1.Ch1.S1.F24" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">A8</a> show the bias correction parameters and their relevance for GOSAT and GOSAT-2.</p></div><span class="section7-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div id="section8" class="sec"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section8 .co-arrow-open,.section8-content" data-show="#section8 .co-arrow-closed,.section8-mobile-bottom-border"><div class="h1"><span class="section-number"> </span>Data availability<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section8-content show-no-js hide-on-mobile-soft"><p id="d1e18326">The GOSAT and GOSAT-2 FOCAL v3.0 data sets are available on request from the authors.</p></div><span class="section8-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div id="section9" class="sec"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section9 .co-arrow-open,.section9-content" data-show="#section9 .co-arrow-closed,.section9-mobile-bottom-border"><div class="h1"><span class="section-number"> </span>Author contributions<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section9-content show-no-js hide-on-mobile-soft"><p id="d1e18332">SN adapted the FOCAL method to GOSAT and GOSAT-2, generated the updated FOCAL data products and performed the validation. MR developed the FOCAL method and provided the <span class="inline-formula">XCO<sub>2</sub></span> and <span class="inline-formula">XCH<sub>4</sub></span> reference databases and the TCCON validation tools. JPB provided the used Python implementation for the SLIM <span class="inline-formula">XCO<sub>2</sub></span> and methane climatology. MH provided the original Python implementation of FOCAL (OCO-2 version). ADN and RJP provided the UoL data, and YY provided the NIES GOSAT data products. The following co-authors provided TCCON data: MB, NMD, DGF, DWTG, FH, RK, CL, YO, IM, JN, HO, CP, DFP, MR, CR, CR, MKS, KS, KS, RS, YT, VAV, MV and TW. All authors provided support in writing the paper.</p></div><span class="section9-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div id="section10" class="sec"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section10 .co-arrow-open,.section10-content" data-show="#section10 .co-arrow-closed,.section10-mobile-bottom-border"><div class="h1"><span class="section-number"> </span>Competing interests<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section10-content show-no-js hide-on-mobile-soft"><p id="d1e18371">At least one of the (co-)authors is a member of the editorial board of <i>Atmospheric Measurement Techniques</i>.</p></div><span class="section10-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div id="section11" class="sec"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section11 .co-arrow-open,.section11-content" data-show="#section11 .co-arrow-closed,.section11-mobile-bottom-border"><div class="h1"><span class="section-number"> </span>Disclaimer<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section11-content show-no-js hide-on-mobile-soft"><p id="d1e18380">Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></div><span class="section11-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div class="ack sec" id="section12"> <div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section12 .co-arrow-open,.section12-content" data-show="#section12 .co-arrow-closed,.section12-mobile-bottom-border"><div class="h1"><span class="section-number"> </span>Acknowledgements<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section12-content show-no-js hide-on-mobile-soft"><p id="d1e18386">GOSAT and GOSAT-2 spectral data have been provided by JAXA and NIES. CarbonTracker CT2019B and CT-NRT.v2020-1 results were provided by NOAA ESRL, Boulder, Colorado, USA, from the website at <span class="uri"><a href="http://carbontracker.noaa.gov" target="_blank">http://carbontracker.noaa.gov</a></span> (last access: 2 June 2022). ABSCO cross sections for <span class="inline-formula">CO<sub>2</sub></span> were provided by NASA and the ACOS/OCO-2 team. GMTED2010 topography data were provided by the U.S. Geological Survey (USGS) and the National Geospatial-Intelligence Agency (NGA). We thank the European Centre for Medium-Range Weather Forecasts (ECMWF) for providing us with analysed meteorological fields (ERA5 data).</p><p id="d1e18402">The GOSAT ACOS v9 Level 2 <span class="inline-formula">XCO<sub>2</sub></span> product from the NASA/OCO-2 team has been obtained from <span class="uri"><a href="https://oco2.gesdisc.eosdis.nasa.gov/data/GOSAT_TANSO_Level2/ACOS_L2_Lite_FP.9r/" target="_blank">https://oco2.gesdisc.eosdis.nasa.gov/data/GOSAT_TANSO_Level2/ACOS_L2_Lite_FP.9r/</a></span>, <a href="https://doi.org/10.5067/VWSABTO7ZII4">https://doi.org/10.5067/VWSABTO7ZII4</a> (last access: 16 October 2020). The UoL and SRON GOSAT data products have been obtained from the Copernicus Climate Data Store (<span class="uri"><a href="https://cds.climate.copernicus.eu/" target="_blank">https://cds.climate.copernicus.eu/</a></span>, last assess: 15 October 2020). GOSAT Level 2 data from NIES have been provided by the GOSAT Data Archive Service (GDAS; <span class="uri"><a href="https://data2.gosat.nies.go.jp/" target="_blank">https://data2.gosat.nies.go.jp/</a></span>, last access: 17 January 2022).</p><p id="d1e18427">RJP is funded via the UK National Centre for Earth Observation (NE/N018079/1). This research used the ALICE High Performance Computing Facility at the University of Leicester for the UoL GOSAT retrievals.</p><p id="d1e18429">The Paris TCCON site has received funding from Sorbonne Université, the French research centre CNRS, the French space agency CNES and Région Île-de-France. The Réunion station is operated by the Royal Belgian Institute for Space Aeronomy with financial support since 2014 by the EU project ICOS-Inwire and the ministerial decree for ICOS (FR/35/IC1 to FR/35/IC6) as well as local activities supported by LACy/UMR8105 – Université de La Réunion. The TCCON stations at Rikubetsu, Tsukuba and Burgos are supported in part by the GOSAT series project. Local support for Burgos is provided by the Energy Development Corporation (EDC, Philippines). The Eureka measurements were made at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change (CANDAC), primarily supported by the Natural Sciences and Engineering Research Council of Canada, Environment and Climate Change Canada, and the Canadian Space Agency. The Anmyeondo TCCON station is funded by the Korea Meteorological Administration research and development programme “Development of Monitoring and Analysis Techniques for Atmospheric Composition in Korea” under grant KMA2018-00522. The TCCON Nicosia site has received support from the European Unions’ Horizon 2020 research and innovation programme under grant agreement no. 856612 (EMME-CARE), the Cyprus Government, and by the University of Bremen. NMD is supported by an Australian Research Council (ARC) Future Fellowship (FT180100327). The Darwin and Wollongong TCCON sites have been supported by a series of ARC grants, including DP160100598, DP140100552, DP110103118, DP0879468 and LE0668470, and NASA grants NAG5-12247 and NNG05-GD07G.</p><p id="d1e18431">Large parts of the calculations reported here were performed on high-performance computing (HPC) facilities of the IUP, University of Bremen, funded under DFG/FUGG grant INST 144/379-1 and INST 144/493-1. The work was supported by the Copernicus Atmosphere Monitoring Service (CAMS) via project CAMS2-52b.</p><p id="d1e18433">This work has received funding from JAXA (GOSAT and GOSAT-2 support, contracts 19RT000692 and JX-PSPC-527269), EUMETSAT (FOCAL-CO2M study, contract EUM/CO/19/4600002372/RL), ESA (GHG-CCI+ project, contract 4000126450/19/I-NB), and the state and the University of Bremen.</p></div><span class="section12-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div id="section13" class="sec"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section13 .co-arrow-open,.section13-content" data-show="#section13 .co-arrow-closed,.section13-mobile-bottom-border"><div class="h1"><span class="section-number"> </span>Financial support<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section13-content show-no-js hide-on-mobile-soft"><p id="d1e18438">This research has been supported by the Japan Aerospace Exploration Agency (grant nos. 19RT000692 and JX-PSPC-527269), the European Organization for the Exploitation of Meteorological Satellites (grant no. EUM/CO/19/4600002372/RL) and the European Space Agency (grant no. 4000126450/19/I-NB).<br><br>The article processing charges for this open-access publication were covered by the University of Bremen.</p></div><span class="section13-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> <div id="section14" class="sec"><div class="grid-container no-margin header-element"><span class="grid-100 mobile-grid-100 tablet-grid-100 grid-parent more-less-mobile" data-hide="#section14 .co-arrow-open,.section14-content" data-show="#section14 .co-arrow-closed,.section14-mobile-bottom-border"><div class="h1"><span class="section-number"> </span>Review statement<span class="hide-on-desktop hide-on-tablet triangleWrapper"> <i class="co-arrow-closed"></i><i class="co-arrow-open" style="display:none"></i></span></div></span></div> <div class="section14-content show-no-js hide-on-mobile-soft"><p id="d1e18449">This paper was edited by Alexander Kokhanovsky and reviewed by T. E. 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Tech., 6, 1533–1547, <a href="https://doi.org/10.5194/amt-6-1533-2013">https://doi.org/10.5194/amt-6-1533-2013</a>, 2013. <a href="https://amt.copernicus.org/articles/15/3401/2022/#xref_paren.7" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">a</a>, <a href="https://amt.copernicus.org/articles/15/3401/2022/#xref_paren.66" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">b</a></span></p></div><span class="section15-mobile-bottom-border mobile-bottom-border hide-on-desktop hide-on-tablet"></span></div> </div>  <div class="pswp" tabindex="-1" role="dialog" aria-hidden="true" >  <div class="pswp__bg"></div>  <div class="pswp__scroll-wrap">  <div class="pswp__container"> <div class="pswp__item"></div> <div class="pswp__item"></div> <div class="pswp__item"></div> </div>  <div class="pswp__ui pswp__ui--hidden"> <div class="pswp__top-bar">  <div class="pswp__counter"></div> <button class="pswp__button pswp__button--close" title="Close 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href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.xml">Full-text XML</a> </li> </ul> </div> <div class="content"> <ul class="additional_info no-bullets no-styling"> <li><a class="triangle" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.bib">BibTeX</a></li> <li><a class="triangle" href="https://amt.copernicus.org/articles/15/3401/2022/amt-15-3401-2022.ris">EndNote</a></li> </ul> </div> </div> <div class="widget dark-border"> <div class="legend journal-contentLinkColor">Short summary</div> <div class="content hide-js shortSummaryFull">We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products. In addition to an increased number of XCO<sub>2</sub> data, v3 also includes products for XCH<sub>4</sub> (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN<sub>2</sub>O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN<sub>2</sub>O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.</div> <div style="display: none" class="content show-js shortSummaryShorten">We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products. In addition to an...</div> <div class="content"> <a href="#" class="more-less show-js triangle" data-hide=".shortSummaryFull" data-show=".shortSummaryShorten" data-toggleCaption='Hide'>Read more</a> </div> </div> <div class="widget dark-border hide-on-mobile hide-on-tablet p-0" id="share"> <div class="legend journal-contentLinkColor">Share</div> <div class="row p-0"> <div class="col-auto pl-0"> <a class="share-one-line" href="https://www.mendeley.com/import/?url=https%3A%2F%2Famt.copernicus.org%2Farticles%2F15%2F3401%2F2022%2F" title="Mendeley" target="_blank"> <img src="https://www.atmospheric-measurement-techniques.net/mendeley.png" alt="Mendeley"/> </a> </div> <div class="col-auto"> <a class="share-one-line" href="https://www.reddit.com/submit?url=https%3A%2F%2Famt.copernicus.org%2Farticles%2F15%2F3401%2F2022%2F" title="Reddit" target="_blank"> <img src="https://www.atmospheric-measurement-techniques.net/reddit.png" alt="Reddit"> </a> </div> <div class="col-auto"> <a 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title="LinkedIn" target="_blank"> <img src="https://www.atmospheric-measurement-techniques.net/linkedin.png" alt="LinkedIn"> </a> </div> <div class="col pr-0 mobile-native-share"> <a href="#" data-title="Atmospheric Measurement Techniques" data-text="*Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm* Stefan Noël et al." data-url="https://amt.copernicus.org/articles/15/3401/2022/" class="mobile-native-share share-one-line last"><i class="co-mobile-share display-none"></i></a> </div> </div> </div> <div class="ajax-content" data-src="https://editor.copernicus.org/similarArticles.php?article=101234&journal=400&isSecondStage=1&ajax=true"> </div> </div> <div class="auto-fixed-top px-1 mb-3 articleNavigation" data-fixet-top-target="#section1"> <button class="btn btn-success mb-3 btn-block" id="mathjax-turn"><i class="fal fa-function"></i> Turn MathJax on</button> <div class="widget dark-border m-0"> <div class="legend journal-contentLinkColor">Sections</div> <div class="content"> <ul class="toc-styling p-0"> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#abstract" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Abstract</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section1" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Introduction</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section2" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Input data</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section3" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Retrieval algorithm</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section4" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Results</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section5" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Conclusions</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section6" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title"><span>Appendix A:</span> SLIMCO2 and SLIMCH4</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section7" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title"><span>Appendix B:</span> Filter variables and bias correction parameters</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section8" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Data availability</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section9" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Author contributions</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section10" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Competing interests</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section11" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Disclaimer</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section12" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Acknowledgements</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section13" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Financial support</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section14" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">Review statement</a> </li> <li> <a href="https://amt.copernicus.org/articles/15/3401/2022/#section15" class="scrollto" data-fixed-element=".auto-fixed-top-forced.article-title">References</a> </li> </ul> </div> </div> </div> </div> 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