Evaluation of CORDEX-Africa Model Data Reliability and Bias Correction for Climate Change Impact Assessment: Upper Tekeze River Basin, Tigray (Ethiopia)

<!DOCTYPE html> <html lang="en" xml:lang="en"> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title> Evaluation of CORDEX-Africa Model Data Reliability and Bias Correction for Climate Change Impact Assessment: Upper Tekeze River Basin, Tigray (Ethiopia) | Green and Low-Carbon Economy </title> <link rel="icon" href="https://ojs.bonviewpress.com/public/journals/6/favicon_en_US.png"> <meta name="generator" content="Open Journal Systems 3.4.0.7"> <meta name="gs_meta_revision" content="1.1"/> <meta name="citation_journal_title" content="Green and Low-Carbon Economy"/> <meta name="citation_journal_abbrev" content="GLCE"/> <meta name="citation_issn" content="2972-3787"/> <meta name="citation_author" content="Ghrmawit Haile Gebrehiwot"/> <meta name="citation_author_institution" content="Center for Environmental Sciences, Addis Ababa University, Ethiopia"/> <meta name="citation_author" content="Kassahun Ture Bekitie"/> <meta name="citation_author_institution" content="Center for Environmental Sciences, Addis Ababa University, Ethiopia"/> <meta name="citation_author" content="Fikru Abiko"/> <meta name="citation_author_institution" content="College of Natural and Computational Sciences, Wolkite University, Ethiopia"/> <meta name="citation_author" content="Weldemariam Seifu"/> <meta name="citation_author_institution" content="College of Agriculture and Natural Resources, Salale University, Ethiopia"/> <meta name="citation_author" content="Haftu Brhane Gebremichael"/> <meta name="citation_author_institution" content="College of Natural and Computational Sciences, Haramaya University, Ethiopia"/> <meta name="citation_title" content="Evaluation of CORDEX-Africa Model Data Reliability and Bias Correction for Climate Change Impact Assessment: Upper Tekeze River Basin, Tigray (Ethiopia)"/> <meta name="citation_language" content="en"/> <meta name="citation_date" content="2024/01/23"/> <meta name="citation_doi" content="10.47852/bonviewGLCE42021893"/> <meta name="citation_abstract_html_url" content="https://ojs.bonviewpress.com/index.php/GLCE/article/view/1893"/> <meta name="citation_abstract" xml:lang="en" content="Model simulation evaluation is crucial for selecting the best regional climate models, as their performance may vary across different locations or variables. This research aims to examine and correct potential biases in the CORDEX ensemble climate dataset over the period of 1987-2005 so as to establish trust in utilizing the CORDEX ensemble forecasts for climate change impact assessment focusing on the UTRB. The Pearson correlation coefficient is employed to assess the degree of correlation between CORDEX and observation data, and the applicability of the CORDEX ensemble data for the UTRB. The statistical analysis reveals a significant correlation between the monthly mean rainfall and temperature in the CORDEX-Africa ensemble simulation and the corresponding observation data for most of the 18 stations. The finding suggests that the CORDEX-Africa ensemble dataset holds promise for future climate projection in the UTRB. The statistical approaches of bias, RMSE, and MAE are employed to assess the adequacy of the CORDEX ensemble model in reproducing observed data. Various bias correction approaches are employed to enhance the accuracy of rainfall and temperature datasets, addressing discrepancies from over and under simulation. The reliability evaluation results indicate that the CORDEX-Africa ensemble precipitation and temperature data set has undergone bias adjustment in order to accurately reproduce the observed gridded dataset for the same period. This adjustment was performed using various methodologies across the 18 stations. Following the bias modifications, the CORDEX ensemble's precipitation and temperature dataset exhibited a high degree of concordance with the grid observation dataset across all 18 observation stations, for the corresponding time. The approaches utilized in this work possess the potential for practical applicability in generating dependable climate data that may be employed in evaluating and forecasting the consequences of climate change using globally accessible data resources. 聽 Received: 17 October 2023 | Revised: 25 December 2023 | Accepted: 5 January 2024聽聽 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. 聽 Data Availability Statement The data used to have the findings of this study are submitted as an additional file. 聽 Author Contribution Statement Ghrmawit Haile Gebrehiwot: Conceptualization, Methodology, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Writing - Review &amp; Editing, Visualization, Project administration. Kassahun Ture Bekitie: Supervision, Funding acquisition. Fikru Abiko:聽Validation, Formal analysis, Writing - Review &amp; Editing. Weldemariam Seifu: Writing - Review &amp; Editing. Haftu Brhane Gebremichael:聽Writing - Review &amp; Editing 聽 Supplementary Information Supplementary file 聽"/> <meta name="citation_keywords" xml:lang="en" content="CORDEX-Africa"/> <meta name="citation_keywords" xml:lang="en" content="climate data"/> <meta name="citation_keywords" xml:lang="en" content="climate projection"/> <meta name="citation_keywords" xml:lang="en" content="performance evaluation"/> <meta name="citation_keywords" xml:lang="en" content="bias refinement"/> <meta name="citation_pdf_url" content="https://ojs.bonviewpress.com/index.php/GLCE/article/download/1893/781"/> <link rel="schema.DC" href="http://purl.org/dc/elements/1.1/" /> <meta name="DC.Creator.PersonalName" content="Ghrmawit Haile Gebrehiwot"/> <meta name="DC.Creator.PersonalName" content="Kassahun Ture Bekitie"/> <meta name="DC.Creator.PersonalName" content="Fikru Abiko"/> <meta name="DC.Creator.PersonalName" content="Weldemariam Seifu"/> <meta name="DC.Creator.PersonalName" content="Haftu Brhane Gebremichael"/> <meta name="DC.Date.created" scheme="ISO8601" content="2024-01-23"/> <meta name="DC.Date.dateSubmitted" scheme="ISO8601" content="2023-10-17"/> <meta name="DC.Date.issued" scheme="ISO8601" content="2023-02-15"/> <meta name="DC.Date.modified" scheme="ISO8601" content="2024-11-05"/> <meta name="DC.Description" xml:lang="en" content="Model simulation evaluation is crucial for selecting the best regional climate models, as their performance may vary across different locations or variables. This research aims to examine and correct potential biases in the CORDEX ensemble climate dataset over the period of 1987-2005 so as to establish trust in utilizing the CORDEX ensemble forecasts for climate change impact assessment focusing on the UTRB. The Pearson correlation coefficient is employed to assess the degree of correlation between CORDEX and observation data, and the applicability of the CORDEX ensemble data for the UTRB. The statistical analysis reveals a significant correlation between the monthly mean rainfall and temperature in the CORDEX-Africa ensemble simulation and the corresponding observation data for most of the 18 stations. The finding suggests that the CORDEX-Africa ensemble dataset holds promise for future climate projection in the UTRB. The statistical approaches of bias, RMSE, and MAE are employed to assess the adequacy of the CORDEX ensemble model in reproducing observed data. Various bias correction approaches are employed to enhance the accuracy of rainfall and temperature datasets, addressing discrepancies from over and under simulation. The reliability evaluation results indicate that the CORDEX-Africa ensemble precipitation and temperature data set has undergone bias adjustment in order to accurately reproduce the observed gridded dataset for the same period. This adjustment was performed using various methodologies across the 18 stations. Following the bias modifications, the CORDEX ensemble's precipitation and temperature dataset exhibited a high degree of concordance with the grid observation dataset across all 18 observation stations, for the corresponding time. The approaches utilized in this work possess the potential for practical applicability in generating dependable climate data that may be employed in evaluating and forecasting the consequences of climate change using globally accessible data resources. 聽 Received: 17 October 2023 | Revised: 25 December 2023 | Accepted: 5 January 2024聽聽 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. 聽 Data Availability Statement The data used to have the findings of this study are submitted as an additional file. 聽 Author Contribution Statement Ghrmawit Haile Gebrehiwot: Conceptualization, Methodology, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Writing - Review &amp; Editing, Visualization, Project administration. Kassahun Ture Bekitie: Supervision, Funding acquisition. Fikru Abiko:聽Validation, Formal analysis, Writing - Review &amp; Editing. Weldemariam Seifu: Writing - Review &amp; Editing. 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name="DC.Subject" xml:lang="en" content="climate projection"/> <meta name="DC.Subject" xml:lang="en" content="performance evaluation"/> <meta name="DC.Subject" xml:lang="en" content="bias refinement"/> <meta name="DC.Title" content="Evaluation of CORDEX-Africa Model Data Reliability and Bias Correction for Climate Change Impact Assessment: Upper Tekeze River Basin, Tigray (Ethiopia)"/> <meta name="DC.Type" content="Text.Serial.Journal"/> <meta name="DC.Type.articleType" content="Research Articles"/> <link rel="stylesheet" href="https://ojs.bonviewpress.com/index.php/GLCE/$$$call$$$/page/page/css?name=stylesheet" type="text/css" /><link rel="stylesheet" href="https://ojs.bonviewpress.com/index.php/GLCE/$$$call$$$/page/page/css?name=font" type="text/css" /><link rel="stylesheet" href="https://ojs.bonviewpress.com/lib/pkp/styles/fontawesome/fontawesome.css?v=3.4.0.7" type="text/css" /><style type="text/css">.pkp_structure_head { background: center / cover no-repeat 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Online First </a> <span class="separator">/</span> </li> <li class="current" aria-current="page"> <span aria-current="page"> Research Articles </span> </li> </ol> </nav> <article class="obj_article_details"> <h1 class="page_title"> Evaluation of CORDEX-Africa Model Data Reliability and Bias Correction for Climate Change Impact Assessment: Upper Tekeze River Basin, Tigray (Ethiopia) </h1> <div class="row"> <div class="main_entry"> <section class="item authors"> <h2 class="pkp_screen_reader">Authors</h2> <ul class="authors"> <li> <span class="name"> Ghrmawit Haile Gebrehiwot </span> <span class="affiliation"> Center for Environmental Sciences, Addis Ababa University, Ethiopia </span> <span class="orcid"> <svg class="orcid_icon" viewBox="0 0 256 256" aria-hidden="true"> <style type="text/css"> .st0{fill:#A6CE39;} .st1{fill:#FFFFFF;} </style> <path class="st0" d="M256,128c0,70.7-57.3,128-128,128C57.3,256,0,198.7,0,128C0,57.3,57.3,0,128,0C198.7,0,256,57.3,256,128z"/> <g> <path class="st1" d="M86.3,186.2H70.9V79.1h15.4v48.4V186.2z"/> <path class="st1" d="M108.9,79.1h41.6c39.6,0,57,28.3,57,53.6c0,27.5-21.5,53.6-56.8,53.6h-41.8V79.1z M124.3,172.4h24.5 c34.9,0,42.9-26.5,42.9-39.7c0-21.5-13.7-39.7-43.7-39.7h-23.7V172.4z"/> <path class="st1" d="M88.7,56.8c0,5.5-4.5,10.1-10.1,10.1c-5.6,0-10.1-4.6-10.1-10.1c0-5.6,4.5-10.1,10.1-10.1 C84.2,46.7,88.7,51.3,88.7,56.8z"/> </g> </svg> <a href="https://orcid.org/0000-0001-9358-812X" target="_blank"> https://orcid.org/0000-0001-9358-812X </a> </span> </li> <li> <span class="name"> Kassahun Ture Bekitie </span> <span class="affiliation"> Center for Environmental Sciences, Addis Ababa University, Ethiopia </span> </li> <li> <span class="name"> Fikru Abiko </span> <span class="affiliation"> College of Natural and Computational Sciences, Wolkite University, Ethiopia </span> </li> <li> <span class="name"> Weldemariam Seifu </span> <span class="affiliation"> College of Agriculture and Natural Resources, Salale University, Ethiopia </span> </li> <li> <span class="name"> Haftu Brhane Gebremichael </span> <span class="affiliation"> College of Natural and Computational Sciences, Haramaya University, Ethiopia </span> </li> </ul> </section> <section class="item doi"> <h2 class="label"> DOI: </h2> <span class="value"> <a href="https://doi.org/10.47852/bonviewGLCE42021893"> https://doi.org/10.47852/bonviewGLCE42021893 </a> </span> </section> <section class="item keywords"> <h2 class="label"> Keywords: </h2> <span class="value"> CORDEX-Africa, climate data, climate projection, performance evaluation, bias refinement </span> </section> <section class="item abstract"> <h2 class="label">Abstract</h2> <p>Model simulation evaluation is crucial for selecting the best regional climate models, as their performance may vary across different locations or variables. This research aims to examine and correct potential biases in the CORDEX ensemble climate dataset over the period of 1987-2005 so as to establish trust in utilizing the CORDEX ensemble forecasts for climate change impact assessment focusing on the UTRB. The Pearson correlation coefficient is employed to assess the degree of correlation between CORDEX and observation data, and the applicability of the CORDEX ensemble data for the UTRB. The statistical analysis reveals a significant correlation between the monthly mean rainfall and temperature in the CORDEX-Africa ensemble simulation and the corresponding observation data for most of the 18 stations. The finding suggests that the CORDEX-Africa ensemble dataset holds promise for future climate projection in the UTRB. The statistical approaches of bias, RMSE, and MAE are employed to assess the adequacy of the CORDEX ensemble model in reproducing observed data. Various bias correction approaches are employed to enhance the accuracy of rainfall and temperature datasets, addressing discrepancies from over and under simulation. The reliability evaluation results indicate that the CORDEX-Africa ensemble precipitation and temperature data set has undergone bias adjustment in order to accurately reproduce the observed gridded dataset for the same period. This adjustment was performed using various methodologies across the 18 stations. Following the bias modifications, the CORDEX ensemble's precipitation and temperature dataset exhibited a high degree of concordance with the grid observation dataset across all 18 observation stations, for the corresponding time. The approaches utilized in this work possess the potential for practical applicability in generating dependable climate data that may be employed in evaluating and forecasting the consequences of climate change using globally accessible data resources.</p> <p>聽</p> <p><strong>Received:</strong> 17 October 2023 | <strong>Revised: </strong>25 December 2023 | <strong>Accepted: </strong>5 January 2024聽</p> <p>聽</p> <p><strong>Conflicts of Interest</strong></p> <p>The authors declare that they have no conflicts of interest to this work.</p> <p>聽</p> <p><strong>Data Availability Statement </strong></p> <p>The data used to have the findings of this study are submitted as an additional file.</p> <p>聽</p> <p><strong>Author Contribution Statement</strong></p> <p><strong>Ghrmawit Haile Gebrehiwot</strong><strong>: </strong>Conceptualization, Methodology, Formal analysis, Investigation, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization, Project administration. <strong>Kassahun Ture Bekitie: </strong>Supervision, Funding acquisition. <strong>Fikru Abiko</strong><strong>:</strong>聽Validation, Formal analysis, Writing - Review & Editing. <strong>Weldemariam Seifu</strong><strong>: </strong>Writing - Review & Editing. <strong>Haftu Brhane Gebremichael</strong><strong>:</strong>聽Writing - Review & Editing</p> <p>聽</p> <p><strong>Supplementary Information</strong></p> <p><a href="https://ojs.bonviewpress.com/index.php/GLCE/libraryFiles/downloadPublic/116">Supplementary file</a></p> <p>聽</p> </section> <br /><div class="separator"></div><div class="item abstract" id="trendmd-suggestions"></div><script defer src='//js.trendmd.com/trendmd.min.js' data-trendmdconfig='{"journal_id":"87934", "element":"#trendmd-suggestions"}'></script> </div> <div class="entry_details"> <div class="item cover_image"> <div class="sub_item"> <a href="https://ojs.bonviewpress.com/index.php/GLCE/issue/view/onlinefirst"> <img src="https://ojs.bonviewpress.com/public/journals/6/cover_issue_24_en_US.png" alt=""> </a> </div> </div> <div class="item galleys"> <h2 class="pkp_screen_reader"> Downloads </h2> <ul class="value galleys_links"> <li> <a class="obj_galley_link pdf" href="https://ojs.bonviewpress.com/index.php/GLCE/article/view/1893/781"> PDF </a> </li> </ul> </div> <div class="item galleys"> <h3 class="pkp_screen_reader"> Additional Files </h3> <ul class="value supplementary_galleys_links"> <li> <a class="obj_galley_link_supplementary file" href="https://ojs.bonviewpress.com/index.php/GLCE/article/view/1893/861"> Supplementary file </a> </li> </ul> </div> <div class="item published"> <section class="sub_item"> <h2 class="label"> Published </h2> <div class="value"> <span>2024-01-23</span> </div> </section> </div> <div class="item issue"> <section class="sub_item"> <h2 class="label"> Issue </h2> <div class="value"> <a class="title" href="https://ojs.bonviewpress.com/index.php/GLCE/issue/view/onlinefirst"> Online First </a> </div> </section> <section class="sub_item"> <h2 class="label"> Section </h2> <div class="value"> Research Articles </div> </section> </div> <div class="item copyright"> <h2 class="label"> License </h2> <p>Copyright (c) 2024 Authors</p> <a rel="license" href="https://creativecommons.org/licenses/by/4.0/"><img alt="Creative Commons License" src="//i.creativecommons.org/l/by/4.0/88x31.png" /></a><p>This work is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.</p> </div> <div class="item citation"> <section class="sub_item citation_display"> <h2 class="label"> How to Cite </h2> <div class="value"> <div id="citationOutput" role="region" aria-live="polite"> <div class="csl-bib-body"> <div class="csl-entry">Gebrehiwot, G. H., Bekitie, K. T. ., Abiko, F., Seifu, W., & Gebremichael, H. B. (2024). 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Evaluation of CORDEX-Africa Model Data Reliability and Bias Correction for Climate Change Impact Assessment: Upper Tekeze River Basin, Tigray (Ethiopia) | Green and Low-Carbon Economy