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class='inst-article-grid-view-container'> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172191648.87143037/v1"> <div class="blog-card__title"> Pan-Atlantic North American cold spells and European wind extremes in CMIP6 historica... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Richard Leeding" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABIFBMVEWPpK+OpK+Oo66QpbCSprGRprGRprCGnKh/l6OAmKSAl6SC maWGnamQpa+Moq2HnqmOo6+QpK+InqqqucLAzNK4xcy7yM6ywMicrriDmqaN oq63xMuis7yJn6t+lqPZ4OT////y9PaTp7Khs7x+lqLT29+ru8OYq7WZrLbO 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model simulations as compared to reanalysis. By leveraging a weather regime perspective, we identify five dynamical pathways for cold spells in three regions of North America. Three of the pathways also engender European wind extremes. The pathways are: (i) A wave train producing central and eastern Canada cold spells, culminating in Scandinavian blocking. (ii) A persistent Atlantic low producing eastern Canada cold spells and wind extremes in the British Isles. (iii) A quasi-stationary wave-2 pattern producing central Canada cold spells and Scandinavian blocking. (iv) An Arctic high producing eastern United States cold spells and wind extremes in Iberia. (v) A wave train producing eastern United States cold spells, culminating in an Atlantic low and wind extremes in Iberia. Models represent well both the frequency and evolution of the pathways compared to reanalysis. However, they under-represent the frequency of pathways (i) and (iii) associated with Scandinavian blocking. The models perform very well in replicating mean surface temperature anomalies during cold spells, though they perform less well on European wind extremes. Typically, the models capture the region and timing of wind extremes associated with Atlantic lows, albeit with some under-representation of occurrence frequency, but fail to adequately capture the wind extremes associated with Arctic highs. This is linked to deficits in how the models reproduce the evolution of the dynamical pathways in the East Atlantic. </div> </a> </div> </div> </div> <div class="blog-card"> <a href="/doi/full/10.22541/essoar.172222596.60330977/v1"> <div class="blog-card__image-container"> <img onerror="$(this).closest('a').remove()" height="200" class="blog-card__image-tag" loading="lazy" src="https://d197for5662m48.cloudfront.net/users/314693/articles/1209493-accurate-column-moist-static-energy-budget-in-climate-models-part-1-conservation-equation-formulation-methodology-and-primary-results-demonstrated-using-giss-modele3/master/file/figures/fig1_map_mean_stdev_fmse_cmip_residual_mod2/fig1_map_mean_stdev_fmse_cmip_residual_mod2.png?1722225960" /> </div> </a> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172222596.60330977/v1"> <div class="blog-card__title"> Accurate Column Moist Static Energy Budget in Climate Models. Part 1: Conservation Eq... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Kuniaki Inoue" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABIFBMVEWbzl+bzl6azV6czmGdz2KSyVGPyE2ZzVuRyU+Ox0uYzFuZ zVyPyEyUylSbzmCWy1iy2YS83pSz2obC4Z6g0Gi/35mr1nqWy1f1+u////+o 1HWLxkbF4qL4+/SQyE2p1Xbd7smMxkedz2OOyEvu9+Wp1HWFwz2y2YX8/fqV y1eq1XfY7MHv9+aazV2g0GeTylKVy1ao1HTZ7MLw+Ojz+eyx2YKNx0if0Gbx +Oju9+Th8M+BwTaez2Tw9+f9/vyz2YWNx0mPyEvO57CczmKYzFqBwTXJ5Kng 8M6UylXu9uSn1HPr9d+r1XjY68D0+e6Vy1Wl03Cj0m3c7si73pOez2WXzFmu 133P57LN5rCczmCQyU6TylOMxkiazl6ez2MAAAD/LicrAAAAAWJLR0Rfc9FR LQAAAAd0SU1FB+gLFRAYGKuFBowAAAE3SURBVDgR3cFpVhNBGAXQ973uACFJ qQjG1yVgqoEwSUKDAjKFUVRmUVDQ/S9DOIcfFWAF3Itnx3DHAMNTeAvgPTzG JAWJNAXShHiIRKmnF0Bfub9SrTkauhB48fJV2ovSwOtBDr2pO6IL4apvldX9 Ow2PjOp9I9AQI1w+pvGJpianGtOa8YGGGOHyWSUfpLlWe16FDzTECFde0OCi Pn5aKmUqfKAhRrh8WSv6vLqWtDIVPtAQI1y+Lm1os7NUylT4QEOMcFtj2t6R 6ru1eRU+0BAjXL6uub19fWkcZCp8oCFGuPyrvtXK3zW0d6gjH2iIEa56rPGT diqdnum8EWiIEWj/2L/4Gfp+XTYrV82D30Q3En86/WBy7a8rNy3Hv3iIaQDB 5F+CkBCP8RbAe3iCGe4YYHhu/gN8oB99WYu7NgAAACV0RVh0ZGF0ZTpjcmVh dGUAMjAyNC0xMS0yMVQxNjoyMzoxOCswMDowMOkYPSoAAAAldEVYdGRhdGU6 bW9kaWZ5ADIwMjQtMTEtMjFUMTY6MjM6MTgrMDA6MDCYRYWWAAAAIHRFWHRz b2Z0d2FyZQBodHRwczovL2ltYWdlbWFnaWNrLm9yZ7zPHZ0AAAAYdEVYdFRo dW1iOjpEb2N1bWVudDo6UGFnZXMAMaf/uy8AAAAYdEVYdFRodW1iOjpJbWFn ZTo6SGVpZ2h0ADYwMHrevbUAAAAXdEVYdFRodW1iOjpJbWFnZTo6V2lkdGgA NjAw6S/t6AAAABl0RVh0VGh1bWI6Ok1pbWV0eXBlAGltYWdlL3BuZz+yVk4A AAAXdEVYdFRodW1iOjpNVGltZQAxNzMyMjA2MTk4uhzacQAAABN0RVh0VGh1 bWI6OlNpemUAMTE2MDVCQlfOgAUAAAA8dEVYdFRodW1iOjpVUkkAZmlsZTov L3RtcC9sZXR0ZXJfYXZhdGFycy8yL0tJLzE1NV8yMDZfOTUvNjAwLnBuZzQU tCkAAAAASUVORK5CYII= " /> </div> <div class="blog-card__second-avatar"> <img alt="Maxwell Kelley" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABblBMVEX+2hD+2g/+2Q/+2hH+2hX+2hT+2hP+2hL92Qr91gD91QD9 1wD92Q792Aj+2xj+5Vr92Qn91wL+4UH+5mL+4Dj+52X92AP+2hb+52T+4Dr/ ///+63791AD+2xb92Af92Qz+87L90QD+4Dv+8q7++uL+64L+3zT++uD92Q/+ 52j+8ab+3zX+8KP+9Lv+7Y/90gD+983+3zP+2xf++dr+/ff+8q3+4DX+8qr9 zQD+7pT+9Lj90wD+3zL+6XX+8ar92AX+3CP+6nz+/v3+87T+63/+4Dn++dn+ 3zD+6nr+75n+7pP+8q/+9sr+++v+4EH+7Yz+3Sb+5FX+9cL92Qv+8aj+++j+ 8KL90AD+2xz+4T7+8af+3B7+7Yr+7pH9zgD+75r+9b/+3iv+8J791wH+/PD+ 4kX+3i/+8aT+8KH++Nj+87D+3B3+64D++dj+2xv+7Ib+4kj92AT+6XH+7IX+ 40r92Q3+6G3+64T92AkAAABBjNF5AAAAAWJLR0R5odzU0AAAAAd0SU1FB+gL FRAXDDbHzj4AAAG5SURBVDgR3cELXwxRHAbg9/+ePTM7c7qyrF6zMi5ZVnKr sIjIyjWK3MkiRCKXPr5pq1/foefBTmKGDjMDzFAwwzYWDAC3wFjAFrpSyREA fSmiK0UE45InNhhdOUnLjqALaYjLaXBdUXeagMQ6unJPb2+pz9H179pdCT17 Knurwe/r7QYIwOjDgLQ/q7kDg9LB/JAOZ0iP6GjiaQCMPgxJx5J6NT0uncgb Opllwzo1EoMoGH1o6LTOJGezc+c1mo9p/MJFXWrGINYZfbisK7qaTVzT9ckb +ZhuTulWUo6JDqMPLd2e1kTzjrzu5hXdu68HzZ4ubDD60NLDGT3K9XhWc/mA NKknyaAjOow+tPR0XsPP9NzrRT4lvXyl181aHR1GH1oaf/NW75QuaC4f0/v5 9gd9TGt1rDP68EmLIzPSdN7QYj6kz2lYkEJ/TANg9KGh0Sz5oqGsoq/5gEaz peY3fQ8AUaDrXv6x8rM99at9YHn1d7K0utKO/rT//lvuc0TB6Pqy4OJ2Wndr WYjWsuCIeprNgoYOulpERiXQ1SK6WkQQ1SqILdwEboKRdWKbGWAGwAwwQ8EM O8d/s/M3R1C/yAMAAAAldEVYdGRhdGU6Y3JlYXRlADIwMjQtMTEtMjFUMTY6 MjM6MTIrMDA6MDBNaGJkAAAAJXRFWHRkYXRlOm1vZGlmeQAyMDI0LTExLTIx VDE2OjIzOjEyKzAwOjAwPDXa2AAAACB0RVh0c29mdHdhcmUAaHR0cHM6Ly9p bWFnZW1hZ2ljay5vcme8zx2dAAAAGHRFWHRUaHVtYjo6RG9jdW1lbnQ6OlBh Z2VzADGn/7svAAAAGHRFWHRUaHVtYjo6SW1hZ2U6OkhlaWdodAA2MDB63r21 AAAAF3RFWHRUaHVtYjo6SW1hZ2U6OldpZHRoADYwMOkv7egAAAAZdEVYdFRo dW1iOjpNaW1ldHlwZQBpbWFnZS9wbmc/slZOAAAAF3RFWHRUaHVtYjo6TVRp bWUAMTczMjIwNjE5MlrJM28AAAATdEVYdFRodW1iOjpTaXplADE4MzEwQkIG VvszAAAAPHRFWHRUaHVtYjo6VVJJAGZpbGU6Ly90bXAvbGV0dGVyX2F2YXRh cnMvMi9NSy8yNTRfMjE4XzE2LzYwMC5wbmdS9P06AAAAAElFTkSuQmCC " /> </div> </div> <div> <div class="blog-card__authors-text"> <div class="blog-card-author-list" style="width: 100%;"> <a href="/users/314693"><p class="blog-card__owner">Kuniaki Inoue</p></a> <p class='blog-card__remaining-text'>and 4 more</p> </div> </div> <time datetime="2024-07-29" class="blog-card__date">July 29, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172222596.60330977/v1"> <div class='blog-card__preview-content'> This paper addresses the challenges in computing the column moist static energy (MSE) budget in climate models. Residuals from such computations often match other major budget terms in magnitude, obscuring their contributions. This study introduces a methodology for accurately computing the column MSE budget in climate models, demonstrated using the GISS ModelE3. Multiple factors leading to significant residuals are identified, with the failure of the continuous calculus’s chain rule upon discretization being the most critical. This failure causes the potential temperature equation to diverge from the enthalpy equation in discretized models. Consequently, in models using potential temperature as a prognostic variable, the MSE budget equation is fundamentally not upheld, requiring a tailored strategy to close the budget. This study introduces the “process increment method’ for accurately computing the column MSE flux divergence. This method calculates the difference in the sum of column internal energy, geopotential, and latent heats before and after applying the dynamics scheme. Furthermore, the calculated column flux divergence is decomposed into its advective components. These computations enable precise MSE budget analysis. The most crucial finding is that vertical interpolation into pressure coordinates can introduce errors substantial enough to reverse the sign of vertical MSE advection in the warm pool regions. In ModelE3, accurately computed values show MSE import via vertical circulations, while values in pressure coordinates indicate export. This discrepancy may prompt a reevaluation of vertical advection as an exporting mechanism and underscores the importance of precise MSE budget calculations. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172191667.76089480/v1"> <div class="blog-card__title"> Tidally-Driven Intra-Seasonal Oscillations in the Thermosphere from TIEGCM-ICON and C... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Federico Gasperini" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABQVBMVEVblflalflalPhalPlfl/ldlvlel/lWkfhFh/hGh/hEhvhO 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class='blog-card__remaining-text'>and 5 more</p> </div> </div> <time datetime="2024-07-25" class="blog-card__date">July 25, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172191667.76089480/v1"> <div class='blog-card__preview-content'> Recent evidence has revealed that strong coupling between the lower atmosphere and the thermosphere ($>$100 km) occurs on intra-seasonal (IS) timescales ($\sim$30-90 days). The Madden-Julian Oscillation (MJO), a primary source of IS variability in tropical tropospheric convection and circulation, can influence the generation and propagation characteristics of atmospheric tides and has been proposed as a significant driver of thermospheric IS oscillations (ISOs). Despite this progress, the limited availability of satellite observations in the ‘thermospheric gap’ region (ca. 100-300 km) and the inability of numerical models to accurately characterize this region have hindered a comprehensive understanding of this connection and the fundamental processes involved. In this study, an Ionospheric Connection Explorer (ICON)-adapted version of the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM), incorporating lower boundary tides derived from MIGHTI observations, is utilized to characterize and quantify the impact of the upward-propagating tidal spectrum on thermospheric ISOs and to elucidate connections to the MJO. Thermospheric zonal and diurnal mean zonal winds are shown to exhibit prominent ($\sim$20 m/s) tidally-driven ISOs throughout 2020-2021, largest at low latitudes ($\pm$30$^\circ$) near $\sim$110-150 km altitude. Correlation analyses demonstrate a robust (r$>$0.6) connection between the thermospheric ISOs, tides, and the tropospheric MJO, moreover, Hovm\”oller diagrams indicate eastward tidal propagation consistent with the MJO and concurrent SABER observations. This study demonstrates that vertically propagating tides play a crucial role in linking IS variability from the lower atmosphere to the thermosphere, with the MJO identified as a primary contributor to this significant whole-atmosphere teleconnection. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172202788.81317674/v1"> <div class="blog-card__title"> Internal ocean-atmosphere variability in kilometer-scale radiative-convective equilib... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Adam B Sokol" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABdFBMVEXiX1HiXlDiX1DhXlDiYFLiYlTiYVTiY1XhWkzfUEDhW0zi X1LiYVPfUULeSTnfUEHhWUvohHnhWkvmem7uoZnuoprnfHHeTD3gWErdRjb1 ysX////zv7nhXE7fUkP31dH54N3hW03gWUriY1bwrqf0wr3gV0nwr6j0xcDe SjrsmpHyubPqjYTeSzvjZVj31dLcPi3gWEnfUkL87+754d7gVUbiYFPdRzf7 7OrjZVf20MzeSzzhXU/fU0TkbWD1ycTZMR/308/iYlXgV0j42NX64+HsmZDg VEXdRTXxs6zXIxDlcGPvq6TiZFbphXv20c399vXgVkf99fT1zMj1yMPeTT3f T0DfTj/dSDj20s7eTj788fD+/f388vH9+Pf31tPfTz/bPSzgVkjdQzPkbF/b OinbOCfldGjzwLvZMB765ePrkon43Nnka17lcGTlcWXwsarngHTwr6neTT7o g3jrlIrgVUffUUHeSDneTDzhXE0AAABm7d51AAAAAWJLR0R7T9K1/AAAAAd0 SU1FB+gLFRAXC6ijW50AAAGBSURBVDgR3cEJQxJRFAbQ7873ZobgzeCGRTem DNOw1EhjNCGLLFstScnM0mxfbd9+fcRiav/Ac7B/iTj4n5AUAA6bBHvRuIYA CM/3PRB70CQOJFMEjQ3CMA1D7MJUl+32ekCTCHv7Mv0HDxk6+Id0s4f1SNZH LjqqDcfSA4bYJjTHc6rak8iHg3qia2hYT4YuBR1CvzCip/T06FhhXJNnimcn Js8RRAdRiqc01sl4OhzW8yyEM1GZELQJbeWCzl68pNXLDOZUr1yN5i0FHUL/ 2nV1b9zUW/Ht5MzCHdW7/mKJgjaiHNR09t6STizn6un7K9GgPgg9Ei1Cd7Vb H9bWao+0t/54PVveeKJrmzkQLWT16ZI+e7784qW+ev1GM1H6rb4btSBaWFp8 r7VVYxGoljen9K8PFUtBC83Q1sdPFUszv/B5a+PL10zm2/cflkSb0BTjiiFo grjoov5z5ddvS+xAk7cEQC9vCNf3qyliJ4cNANggbBLsJmhyBIA0YH/5A6UA McvxidzxAAAAJXRFWHRkYXRlOmNyZWF0ZQAyMDI0LTExLTIxVDE2OjIzOjA4 KzAwOjAwJbI9tAAAACV0RVh0ZGF0ZTptb2RpZnkAMjAyNC0xMS0yMVQxNjoy MzowOCswMDowMFTvhQgAAAAgdEVYdHNvZnR3YXJlAGh0dHBzOi8vaW1hZ2Vt YWdpY2sub3JnvM8dnQAAABh0RVh0VGh1bWI6OkRvY3VtZW50OjpQYWdlcwAx p/+7LwAAABh0RVh0VGh1bWI6OkltYWdlOjpIZWlnaHQANjAwet69tQAAABd0 RVh0VGh1bWI6OkltYWdlOjpXaWR0aAA2MDDpL+3oAAAAGXRFWHRUaHVtYjo6 TWltZXR5cGUAaW1hZ2UvcG5nP7JWTgAAABd0RVh0VGh1bWI6Ok1UaW1lADE3 MzIyMDYxODijB+swAAAAE3RFWHRUaHVtYjo6U2l6ZQAyNDg4M0JCSOLhFwAA ADt0RVh0VGh1bWI6OlVSSQBmaWxlOi8vdG1wL2xldHRlcl9hdmF0YXJzLzIv QVMvMjI2Xzk1XzgxLzYwMC5wbmedVoJxAAAAAElFTkSuQmCC " /> </div> <div class="blog-card__second-avatar"> <img alt="Vlad A. Munteanu" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABWVBMVEWzm92ymty0nd20nN2zmt2znN2ymt2xmNyqj9msktqymdyu ldqqj9ixmdyqkNm2n97NvejDseSuldvEsuS+qeHDsOSvldvKuefKuue1nt7/ //+vltu4od+liNbk3PO1nd2ojdjRwurArOOmitff1PDMvOipjti2oN7PwOnb 0O+bfNLk2/PSxOvx7fm+quK8p+Hp4vWni9fu6Pe9qOGhg9Xl3vP49vz28/ut k9q7puDz8PmrkNn6+f2sk9r18vqsktnTxevf1fC+qeKnjNfXyu3JuOaggtTO vunSxevi2vLh2PGlidetlNrj2/LHtua4ot/m3/ScfdLw6/iwmNuojNji2fLn 4PTCruPZze7v6vfj2vKfgdTRw+qmi9ft5/abe9Kwl9u/q+Lc0e+hhNXs5vbo 4PTl3PPArOL18fqrkdnl3fOulNrZzu7FsuXYzO3BreOwmNypj9gAAABIf12k AAAAAWJLR0RyNg4NWAAAAAd0SU1FB+gLFRAXGVsaKtUAAAGKSURBVDgR5cF5 X9JwAAbw59mPMWfM0TKKh3SjQy0LWtMa1TSjk+iG7oPugzR7//80Dvv0Hvx+ sY8wB4BTyDGHPYRlWABhLNiWYREgLAvEBOHMuCAJd2b2QMkFSXhzcw6IEcLx ywcDAMGhsjdfPlwB4dhHjlYdEDnC8STUrOCYtLAomRrCqC4ddw2RI8MTJ3Vq aTla0ekzq9LZKETpnNRwDTFC4zZ1Pq5GF5SsrevipchKW7qshmuIEYJXrmo2 C7WxGa/rmppBtKW6rruGGCkybN/QzVu3dae0dFctde51df+BkswQYzTdh3r0 +In8p72+vGdaeK7khZLMEGMEog2lehn7cV9hQ61Xet1RkhlirMAweqMtrUTL cV/Nt3qnxferSjJDTNCu+JK8QTXu6MPaR6n5qa8kNcQEaeLP+hJbVvurvsWJ vv/o/VQjM8QU7eH8r2ZgY7i94w+69d/D2vaOPwCxhwjaFZBIe7vAny6Q9nbB Av6hXbUJ0IQgLEOaEMR/mCsCzIFT2Ef+Ao/8M9r3nX5rAAAAJXRFWHRkYXRl OmNyZWF0ZQAyMDI0LTExLTIxVDE2OjIzOjI1KzAwOjAwBkBbCQAAACV0RVh0 ZGF0ZTptb2RpZnkAMjAyNC0xMS0yMVQxNjoyMzoyNSswMDowMHcd47UAAAAg dEVYdHNvZnR3YXJlAGh0dHBzOi8vaW1hZ2VtYWdpY2sub3JnvM8dnQAAABh0 RVh0VGh1bWI6OkRvY3VtZW50OjpQYWdlcwAxp/+7LwAAABh0RVh0VGh1bWI6 OkltYWdlOjpIZWlnaHQANjAwet69tQAAABd0RVh0VGh1bWI6OkltYWdlOjpX aWR0aAA2MDDpL+3oAAAAGXRFWHRUaHVtYjo6TWltZXR5cGUAaW1hZ2UvcG5n P7JWTgAAABd0RVh0VGh1bWI6Ok1UaW1lADE3MzIyMDYyMDUXKaPcAAAAE3RF WHRUaHVtYjo6U2l6ZQAyMDQxMkJCaklrvQAAAD10RVh0VGh1bWI6OlVSSQBm aWxlOi8vdG1wL2xldHRlcl9hdmF0YXJzLzIvVk0vMTc5XzE1NV8yMjEvNjAw LnBuZyTtHTkAAAAASUVORK5CYII= " /> </div> </div> <div> <div class="blog-card__authors-text"> <div class="blog-card-author-list" style="width: 100%;"> <a href="/users/518950"><p class="blog-card__owner">Adam B. Sokol</p></a> <p class='blog-card__remaining-text'>and 3 more</p> </div> </div> <time datetime="2024-07-26" class="blog-card__date">July 26, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172202788.81317674/v1"> <div class='blog-card__preview-content'> We describe internal, low-frequency variability in a 21-year simulation with a cloud-resolving model. The model domain is the length of the equatorial Pacific and includes a mixed-layer ocean, which permits coherent cycles of sea surface temperature (SST), atmospheric convection, and the convectively coupled circulation. The warming phase of the cycle is associated with near-uniform SST, less organized convection, and sparse low cloud cover, while the cooling phase exhibits strong SST gradients, highly organized convection, and enhanced low cloudiness. Both phases are quasi-stable but, on long timescales, are ultimately susceptible to instabilities resulting in rapid phase transitions. The internal cycle is leveraged to understand the factors controlling the strength and structure of the tropical overturning circulation and the stratification of the tropical troposphere. The overturning circulation is strongly modulated by convective organization, with SST playing a lesser role. When convection is highly organized, the circulation is weaker and more bottom-heavy. Alternatively, tropospheric stratification depends on both convective organization and SST, depending on the vertical level. SST-driven variability dominates aloft while organization-driven variability dominates at lower levels. A similar pattern is found in ERA5 reanalysis of the equatorial Pacific. The relationship between convective organization and stratification is explicated using a simple entraining plume model. The results highlight the importance of convective organization for tropical variability and lay a foundation for future work using coupled, idealized models that explicitly resolve convection. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172166412.27583900/v1"> <div class="blog-card__title"> The Disparities Between Locally Developed Warm-sector Short- and Long-term Heavy Prec... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Haisheng Liu" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc 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circulation backgrounds and divergence-vorticity configurations of locally developed warm-sector short- and long-term heavy precipitation events (SHPEs & LHPEs) are compared in this work. Results show that double LLJs accompany the evolution of both types of rainstorms but SHPEs are mainly located in the negative relative vorticity (RV) area to the right of the synoptic-related LLJ, while LHPEs are located in the positive RV area to the left side of LLJ. When triggering, both types of rainstorms maintain the structure of bottom convergence and lower-middle layer (875-700 hPa) divergence. Then, in the lower-middle layer of the SHPE, the negative RH encourages the transition from divergence to convergence, which prevents convection from continuing, but the LHPE always retains its prior structure, allowing it to endure longer. This work provides new insights into the evolution of rainstorms with different durations, which can aid in the accurate forecasting of warm-sector rainstorms. </div> </a> </div> </div> </div> <div class="blog-card"> <a href="/doi/full/10.22541/essoar.172132844.44344974/v1"> <div class="blog-card__image-container"> <img onerror="$(this).closest('a').remove()" height="200" class="blog-card__image-tag" loading="lazy" src="https://d197for5662m48.cloudfront.net/users/531487/articles/1197105-south-american-intraseasonal-oscillation-eof-and-neural-network-approaches/master/file/figures/Fig1_EOF_SOM_OLR_wet_1980_2018_OLR_chi_conv_ZCAS_novo_era5/Fig1_EOF_SOM_OLR_wet_1980_2018_OLR_chi_conv_ZCAS_novo_era5.png?1732714979" /> </div> </a> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172132844.44344974/v1"> <div class="blog-card__title"> South American Intraseasonal Oscillation: EOF and Neural Network Approaches </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Camila Sapucci" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABUFBMVEW7Zcq7ZMq6ZMm8aMu8acu7Z8q8Z8q0VcSxT8KyUcO2W8a7 Zsq0V8WxUMK1WMW2WsbLitfYp+DVoN7AcM64X8eyUsPIgtTXpeDGftK4YMj7 9/z////etOW6Y8m1Wcbx4PTu2vK1V8W5Ysm0VsX58frRmNu5Yci/bs3x4fTO kNiqP7zjwOnivui4X8i4Xsfiv+mzU8TNj9jgueeqP72vSsDBc87w3vP47/mw TcGwTMG3XMf69fvu2fGxTsLHgNO9asu5YMivS8Hnyey1WcXlxevDeNC3Xce0 VsS6ZcnDedC3XsfNjtjt1/HjwenDd9CzVcTguufnyuyzU8PQlNrcseSqQL2w TsK+bc39+v3r0/CtRr/37fjMi9fOktmsRL737vnUn97Wo9/s1fC6ZMrCd9D4 8Pr+/v6+bMzSmdzXpuDWpN/LitbYpuDQldq8Z8sAAAC+TZGAAAAAAWJLR0Rv VQhhgQAAAAd0SU1FB+gLFRAXC6ijW50AAAF2SURBVDgR3cFnW9NQGAbg531y 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These indices are constructed using two distinct approaches: the linear Empirical Orthogonal Functions (EOF) method and the unsupervised machine-learning Self-Organizing Maps (SOM) technique. Both methods are applied to Outgoing Longwave Radiation (OLR) and precipitation-filtered anomalies in the 30-90-day band over the South American domain. Results demonstrate that regional indices provide valuable insights into intraseasonal South American rainfall variability, including phase and strength, compared to global indices of the Madden-Julian Oscillation (MJO). Despite being computed using only the South American domain, the regional indices capture the tropical-tropical MJO teleconnection through the zonal wavenumber-1 structure. The diversity in amplitude and evolution of precipitation, primarily influenced by tropical-extratropical teleconnections through Rossby wave trains, is more evident when using the non-linear SOM index. The regional indices also accurately measure the impacts of intraseasonal variability on extreme precipitation events over South America. Case studies, such as the 2013/2014 summer drought episode, highlight this ability, when a deficient rainy season severely affected the Southeast Region of Brazil, impacting agricultural production and hydroelectric power generation. During this episode, the regional indices show agreement between drought periods and suppressed precipitation phases, while global indices indicate an inactive MJO phase. These findings underscore the effectiveness of regional indices in capturing intraseasonal variability, offering significant implications for extreme weather prediction and their impacts on South American water resources and socio-economic activities. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172132456.65321288/v1"> <div class="blog-card__title"> Adjustments to climate perturbations -mechanisms, implications, observational constra... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Johannes Quaas" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABUFBMVEVSvIlRvIhRvIlRu4hUvIpUvYtWvYxVvYtGt4FEtn9Gt4A7 s3k6s3lDtn5TvIpMuYVrxZpyyJ9OuoY5snhlw5aV1reY17lxyJ5LuYQ9tHrz +vf///9NuoY8s3q24s3a8OVFt4BNuoVTvIno9u9Qu4czsHSh2r/U7uFgwZNd wJCy4crJ6to3sXfp9vBIuII/tHw9s3otrXDf8uk+tHtlw5XD59Y2sXZZvo5Z v46Q1LOP07I4sneBzqmz4ctWvYud2bxUvYqEz6uR1LSf2b1Pu4fn9e5nxJfB 59U3sXZYvo2O07Lb8ebP7N5BtX1JuIMyr3Pt+PNCtn4rrW59zKaH0K3c8ec6 snio3cTD6Naj28DX7+NRu4lkw5XC59X9/v2T1bWb2LuS1LRux5yc2LyL0rDT 7uHW7+NXvoxMuoVDtn80sHS75NFoxJhAtX1PuocAAAByus1DAAAAAWJLR0Rv VQhhgQAAAAd0SU1FB+gLFRAXHVx37swAAAFoSURBVDgR3cFXWxNBAAXQO3uH WcOsQ4yowetqWMSCZBO7GA0rxoIYNRbsvWD//49GAhKRz3c9B/8tYyJsiX0A V0XYAu0ISFrnYhB/ILGtRCAe9cn2EIhNDDBW3lEhd47v2r3HVwPxOyJM7FVl X7pffQdqkxkjDCNCOqWD04d0+MjRGR2bjUkMI4KvK69JjWbt+AmNj1pigyER fF0nT+n0mbPnkjmdTx0NfiGJ4OtqXdDFVjtO5zSfOBqsI4oRZGlds5c002q3 /YIuJ44GAyQ6aRNx84omrura9cVFf0ML3tFggKhg6Wb31u07ynPJ98buLqlc Kog1RNaY0r3p+3rQXX6oR538sZ74AGLNU8a9sn56VrP+ufpepI2YxDpD2y1e vnpd6Vl0kjdv373Xh5XJjNjAouqX048FCfvJtz5/0dfcEkMYnHMZASJ2K51v 1VIgMYQDANiH8N0Sm0QmwqooAgHir0jiH/IDbJwqZt1p8gwAAAAldEVYdGRh dGU6Y3JlYXRlADIwMjQtMTEtMjFUMTY6MjM6MjkrMDA6MDDB4DF9AAAAJXRF WHRkYXRlOm1vZGlmeQAyMDI0LTExLTIxVDE2OjIzOjI5KzAwOjAwsL2JwQAA ACB0RVh0c29mdHdhcmUAaHR0cHM6Ly9pbWFnZW1hZ2ljay5vcme8zx2dAAAA GHRFWHRUaHVtYjo6RG9jdW1lbnQ6OlBhZ2VzADGn/7svAAAAGHRFWHRUaHVt Yjo6SW1hZ2U6OkhlaWdodAA2MDB63r21AAAAF3RFWHRUaHVtYjo6SW1hZ2U6 OldpZHRoADYwMOkv7egAAAAZdEVYdFRodW1iOjpNaW1ldHlwZQBpbWFnZS9w bmc/slZOAAAAF3RFWHRUaHVtYjo6TVRpbWUAMTczMjIwNjIwOR6f7/cAAAAT dEVYdFRodW1iOjpTaXplADIwNzQ0QkIeup3tAAAAPHRFWHRUaHVtYjo6VVJJ AGZpbGU6Ly90bXAvbGV0dGVyX2F2YXRhcnMvMi9KUS84Ml8xODhfMTM3LzYw MC5wbmdqRB6lAAAAAElFTkSuQmCC " /> </div> <div class="blog-card__second-avatar"> </div> </div> <div> <div class="blog-card__authors-text"> <div class="blog-card-author-list" style="width: 100%;"> <a href="/users/527489"><p class="blog-card__owner">Johannes Quaas</p></a> <p class='blog-card__remaining-text'>and 28 more</p> </div> </div> <time datetime="2024-07-18" class="blog-card__date">July 18, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172132456.65321288/v1"> <div class='blog-card__preview-content'> Since the 5th Assessment Report of the Intergovernmental Panel on Climate Change (AR5) an extended concept of the energetic analysis of climate change including forcings, feedbacks and adjustment processes has become widely adopted. Adjustments are defined as processes that occur in response to the introduction of a climate forcing agent, but that are independent of global-mean surface temperature changes. Most considered are the adjustments that impact the Earth energy budget and strengthen or weaken the instantaneous radiative forcing due to the forcing agent. Some adjustment mechanisms also impact other aspects of climate not related to the Earth radiation budget. Since AR5 and a following description by Sherwood et al. (2015), much research on adjustments has been performed and is reviewed here. We classify the adjustment mechanisms into six main categories, and discuss methods of quantifying these adjustments in terms of their potentials, shortcomings and practicality. We furthermore describe aspects of adjustments that act beyond the energetic framework, and we propose new ideas to observe adjustments or to make use of observations to constrain their representation in models. Altogether, the problem of adjustments is now on a robust scientific footing, and better quantification and observational constraint is possible. This allows for improvements in understanding and quantifying climate change. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172118399.99348437/v1"> <div class="blog-card__title"> Improving prediction of marine low clouds using cloud droplet number concentration in... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="YANG CAO" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABKVBMVEW8qqS7qaO8qqO9rKa9q6W8q6W5p6Gzn5i3o524pZ+1oZuy npeznpi3pJ65p6DBsavVysbHuLS3pJ24pZ7Csq3Gt7K0oJnLvbnYzsrWy8fB saz///+4pp+8qqX5+PfKvLi+rKf49vbi29i+rKaxnJXVysfe1tPOwb3n4d6w mpP08fDXzcm6qKK+raft6OfQxMC0n5m9q6b7+vq6p6Gwm5T29POxnZbKvLfo 4+GrlY2ynZb18vHQw7/Vycbh2daznpfd1NHPwr60oJrHuLPx7ey7qKLl39zE tK+2o5y7qqTMv7ve1dK/rqi5pqD39fTf1tO1oZrDs67DtK66qKH28/K0oZrM v7rk3dr18/L59/e1opvp5OL9/f3k3dvSxsK7qaK2o53RxMAAAAA8aepMAAAA AWJLR0RiK7kdPAAAAAd0SU1FB+gLFRAXN4fMJxoAAAFFSURBVDgR5cENI1NR HMfx769z7k53Z4vCWv1LeUpyJ3ajlKI8TSUT0iN5/2/CDdvkLfh8uFZUAP1z Q2f4j3BeoMQh4Z1LJC4RpXATiTSkJJRjpeoRXeJWX//tOzAw2D9USmt36/fu RyE6RMmZ8eBhGLZH8fGIFUYDiAvS2PiEPQnlSXs6VX5m01ljxp7PzokOoXLT 8hfz1lh4aa8Ws9fYm+AlLkguLtnbPnu3XFux9x8aSb66moPoEIRmc83Ws7hh my0vVQeQ6NrSXO2j2afxzwsbttnyYnsbRI8gfrH1tBF3bLI9luS7X/dAdAkq +5bm7uCbHS4SZPOzCaJLEL5bKUftH7b0M/tlE8GJHkEYtjwnqbrfVvizDKJH kB7Vs2Pk/1ZP6tNDlWPEZRLtIIR8VouxlSCukHcIEM45j7hKBQo6x/VyClXf IXOxyUM0AAAAJXRFWHRkYXRlOmNyZWF0ZQAyMDI0LTExLTIxVDE2OjIzOjIz KzAwOjAwZZBuMwAAACV0RVh0ZGF0ZTptb2RpZnkAMjAyNC0xMS0yMVQxNjoy MzoyMyswMDowMBTN1o8AAAAgdEVYdHNvZnR3YXJlAGh0dHBzOi8vaW1hZ2Vt YWdpY2sub3JnvM8dnQAAABh0RVh0VGh1bWI6OkRvY3VtZW50OjpQYWdlcwAx p/+7LwAAABh0RVh0VGh1bWI6OkltYWdlOjpIZWlnaHQANjAwet69tQAAABd0 RVh0VGh1bWI6OkltYWdlOjpXaWR0aAA2MDDpL+3oAAAAGXRFWHRUaHVtYjo6 TWltZXR5cGUAaW1hZ2UvcG5nP7JWTgAAABd0RVh0VGh1bWI6Ok1UaW1lADE3 MzIyMDYyMDP+SgbpAAAAE3RFWHRUaHVtYjo6U2l6ZQAyMTIwNUJCk6Y8WAAA AD10RVh0VGh1bWI6OlVSSQBmaWxlOi8vdG1wL2xldHRlcl9hdmF0YXJzLzIv WUMvMTg4XzE3MF8xNjQvNjAwLnBuZ3y+kmgAAAAASUVORK5CYII= " /> </div> <div class="blog-card__second-avatar"> <img alt="Yannian Zhu" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABGlBMVEW8qqS7qaO9q6W9q6a9rKa1oZq0oJq0oJm2opy4pZ+ynpez n5iznpjRxcHQxMC6p6G6qKLSxsLMv7rDs67ZzsvUyMTUycXVysbFtrHq5OL/ ///Vyse/rqiynZbZz8zf1tS8q6W4pZ79/f22opu5p6G3pJ21opvIubTEtbDG t7LAr6nJu7b5+Pe7qqSxnJXf19TTyMSpkorZz8u2o523o52slo7w7Ou0n5m3 pJ76+PiumZL+/v62o5yxnZbb0c7f1tOwm5S+rKba0M3p5OLWy8e1oZvDs635 9/f8/Py7qKL49vXWy8jg2NXb0s+/rajTx8PIurXv6+rUyMW6qKG5pqD7+vnK vLfHuLPCsazr5uTFtbDe1tPLvrkAAABsSFQ1AAAAAWJLR0Rdnd8wAQAAAAd0 SU1FB+gLFRAXF7yiB9IAAAE1SURBVDgR5cGJOgJRGAbg75sOdeZMGsoMf01C KEuWLNkbSvZ95/6vA0+Wwy14X/wrfAeANlgIJwGCUA5UF4gfBHt6CYLJlHaN MZ5xNUh8Ish0X8aHn+kfyOYGgyAMckMaxCfCSQ5L3i1ERRlJS1fOKOILS6O+ jI2XJ0QmS1OV6vSMzGofxJc5qtq8LCwuSS5iqr68sirVtQSJb0SmIesbm7Ll l0qF7R3ZbcaEhVS1PdmXVqTotA+kYwjCRviNQ+mkjgAmjyXbdjgHGxnXTiSo xVTNUzmLzh0QNlKZC1kwiYS5lKuVej2lQdiozLUMmvjm9k7up6uVh8cyCAuV aUnLK3hF6XqKFGEh9PPLs3b0UDHMh2Gw9NoAYSGhIw1Cu8bzPONugcQvRAyC UF0O8Qc/gD/wn7wBeo4fpFFi/v8AAAAldEVYdGRhdGU6Y3JlYXRlADIwMjQt MTEtMjFUMTY6MjM6MjIrMDA6MDDD52WHAAAAJXRFWHRkYXRlOm1vZGlmeQAy MDI0LTExLTIxVDE2OjIzOjIyKzAwOjAwsrrdOwAAACB0RVh0c29mdHdhcmUA aHR0cHM6Ly9pbWFnZW1hZ2ljay5vcme8zx2dAAAAGHRFWHRUaHVtYjo6RG9j dW1lbnQ6OlBhZ2VzADGn/7svAAAAGHRFWHRUaHVtYjo6SW1hZ2U6OkhlaWdo dAA2MDB63r21AAAAF3RFWHRUaHVtYjo6SW1hZ2U6OldpZHRoADYwMOkv7egA AAAZdEVYdFRodW1iOjpNaW1ldHlwZQBpbWFnZS9wbmc/slZOAAAAF3RFWHRU aHVtYjo6TVRpbWUAMTczMjIwNjIwMolNNn8AAAATdEVYdFRodW1iOjpTaXpl ADE2NTM4QkIXBvbQAAAAPXRFWHRUaHVtYjo6VVJJAGZpbGU6Ly90bXAvbGV0 dGVyX2F2YXRhcnMvMi9ZWi8xODhfMTcwXzE2NC82MDAucG5njXIKbAAAAABJ RU5ErkJggg== " /> </div> </div> <div> <div class="blog-card__authors-text"> <div class="blog-card-author-list" style="width: 100%;"> <a href="/users/802039"><p class="blog-card__owner">Yang Cao</p></a> <p class='blog-card__remaining-text'>and 12 more</p> </div> </div> <time datetime="2024-07-17" class="blog-card__date">July 17, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172118399.99348437/v1"> <div class='blog-card__preview-content'> Marine low clouds significantly cool the climate, but predicting these clouds remains challenging: the response of these clouds to various factors is highly non-linear. Previous studies usually overlook the effects of cloud droplet number concentration (Nd) and the non-local information of the target grids. To address these challenges, we introduce a convolutional neural network model (CNNMet-Nd) that uses both local and non-local information and includes Nd as a cloud-controlling factor to enhance the predictive ability of cloud cover, albedo, and cloud radiative effects (CRE) for global marine low clouds. CNNMet-Nd demonstrates superior performance, explaining over 70% of the variance in these three cloud variables for instantaneous scenes of 1°×1°, a notable improvement over past efforts. CNNMet-Nd also accurately replicates geographical patterns of trends in marine low clouds from 2003 to 2022. In contrast, a similar convolutional neural network model without Nd input (CNNMet) fails to predict global mean cloud properties effectively, underscoring the critical role of Nd. Further comparisons with an artificial neural network (ANNMet-Nd) model, which uses the same inputs but without considering spatial dependence, show CNNMet-Nd’s superior performance with R2 values for cloud cover, albedo, and CRE being 0.16, 0.11, and 0.18 higher, respectively. This highlights the importance of incorporating non-local information into low cloud predictions to enhance climate model parameterizations. </div> </a> </div> </div> </div> <div class="blog-card"> <a href="/doi/full/10.22541/essoar.172118429.98705077/v1"> <div class="blog-card__image-container"> <img onerror="$(this).closest('a').remove()" height="200" class="blog-card__image-tag" loading="lazy" src="https://d197for5662m48.cloudfront.net/images/tagdashboard/banner/large-243fcdb05f224a75295a129767fd9215.jpg" /> </div> </a> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172118429.98705077/v1"> <div class="blog-card__title"> Lightning Observations with the Horus Polarimetric Phased Array Radar </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Vitor Goede" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABKVBMVEWzm92ymtyymt20nN20nd2znN21nd2sktqqj9mwmNyvltup jtiulNqrkdmojdiwl9vGtOXNvui1nt65pODPwOnArOPEseTTxevRw+q+quKz mt2pjdje0/D////WyeynjNfp4vXQweqmitf28/vr5PaxmdytlNq3oN708Pqx mNyuldumi9fu6ffXyu3j2vLYzO2ojNjx7fm4od/Htubk2/Ohg9XArOLu6Peh hNWtk9r9/f7Ov+nRwurj2/LCruOihNWrkNnz8PqnjNj+/v7WyuzOvum/quK9 qOGni9fr5fbb0O+qkNnWyu3Lu+jCsOS7puDCr+Tt5/f59/z49/y8p+Hw6/ij htWggtT7+f3m3/TUx+yvldu4ot/QwuqymdzEsuTSxevNvegAAAAPl1Q1AAAA AWJLR0RiK7kdPAAAAAd0SU1FB+gLFRAXNB7FdqAAAAFaSURBVDgR5cEJQtNA AAXQ/5OZJJNJJlKhZfFbQYpaN3AvIFREKCjgvq/3v4TBtihegfdwlrAGIGIt 4h84hbEBAVpjSZgkiUH8FRFp5kAi9wUsyhBSC2IsIqpzE40KyM9PTlV51mxN zwQHzmIoopm7oIvtxLQvaX7BXFZtMe2AGGG8dEVXM3utKxXXb+hmxVu6vWwY YYiwcyu6k5d3de/+Az18VKU9rS4RxNAsk7Cm9Sw81sbmvNZ9oyj7XRLECG0e 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src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABTVBMVEWVcs+Vcc+Ucc+Ucc6Vc8+XddCWc8+WdM+Qa8yGXsiHYMiH X8iKY8qLZcqMZsuhg9TDr+S7peC9p+GulNqFXceTb86QbM2IYcmpjdjBrePB rOOmidaRbc2IYMm8puD////Ux+uKZMqTcM6NZ8vp4vXl3fO1nd3WyeykhtXc 0e/ZzO2HYMnRwurSw+qRbM3TxOu2nt7Oveh8UcSNaMt9U8Tn3/SjhdWAV8X0 8PqEXMeEW8ePasz49vvk3POcfNKxmNzMvOh3S8HVx+zazu6GX8iMZ8uUcM6F XMeZd9DYy+2CWcbo4fTq4/W4od/Xyu2xl9vj2vL18vqymdzKuefPwOn7+v3h 1/GDWsaJYsl/VcXy7vmXdNDd0u/bz+7x7fi/quLi2PLUxuv+/v6ZeNGPa8yi g9TEseS+qeGtk9qXdM+OacvCruOOacyUcs4AAAAt/efOAAAAAWJLR0RuIg9R FwAAAAd0SU1FB+gLFRAXGVsaKtUAAAF+SURBVDgR3cF5XxJRFAbg98w75zK3 ASltulnBiSi1ghrFNimtlLBss9Wyfbfl+/8bNvBL/Qg+D/YXEcGICPaKWAAg /EewC2MdcCRAlFRLIHaIGCf+QFpOFGSMivdjLib+o0uqBw+NT+jhDPGRcHTy 2PH0REyMCLVWt20nG6ey5mkbOFPJQAwJNUzZtM6ctXPnQ8vaF5K2XfTKCAWh htxm5zrzl+zylat2baHbvX6jEoMoCDXk1k4Xw5LdvHXblrMVH3p3SEFBqCG3 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class="blog-card__owner">Vitor Goede</p></a> <p class='blog-card__remaining-text'>and 7 more</p> </div> </div> <time datetime="2024-07-17" class="blog-card__date">July 17, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172118429.98705077/v1"> <div class='blog-card__preview-content'> A document by Vitor Goede. Click on the document to view its contents. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172280726.68759267/v1"> <div class="blog-card__title"> Impacts of Seastate-Dependent Sea Spray Heat Fluxes on Tropical Cyclone Structure and... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Benjamin Witten Barr" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABcVBMVEXyYJHyX5HyX5DxX5DyYZLyZJTyZJPyY5PyYpLyYZHxV4vw SoLwS4PwS4LwTYPwUofxXY/xXpDwTYTwUIXzdqD3psH2mbj2nLr2lbX0eaLx VorwUYbxXI72mrn3nrz1hKryZ5b3ob7////0eqPwT4X5uc73psLzcJz3pcH9 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href="/doi/full/10.22541/essoar.172280726.68759267/v1"> <div class='blog-card__preview-content'> Air-sea sensible and latent heat fluxes are fundamental to tropical cyclone (TC) energetics, but the impacts of seastate-dependent sea spray heat fluxes on TC structure and intensity are poorly understood. We explore these impacts herein by implementing a recently-developed parameterization for air-sea heat fluxes with seastate-dependent spray physics into a fully coupled atmosphere-wave-ocean model, the Unified Wave INterface–Coupled Model. We conduct model experiments with and without spray for four TCs covering wide ranges of intensity and structure. The effects of spray on model TCs in the open ocean can be summarized in three stages. 1) Spray evaporative cooling dominates in boundary layers (BLs) of tropical storms and weak hurricanes (i.e., with 10-m windspeeds ≲ 30–40 m s-1 and relatively small waves), which hinders intensification. 2) Further TC intensification increases spray generation, producing positive spray sensible heat fluxes (i.e., warming) under the eyewall. This warming is favorable for intensification, but inefficiency caused by cooler BL inflow continues to inhibit eyewall deep convection, and spray continues to oppose intensification overall. 3) Further increase of spray production from continued TC intensification (i.e., past Category 3) ultimately allows spray to promote intensification by warming the BL and enhancing eyewall deep convection. Spray’s tendency to oppose intensification of weak TCs is consistent with the relatively rare occurrence of major hurricanes. However, if a TC intensifies beyond stage 2, spray can support rapid intensification. We also find that enhanced spray generation by wave dissipation in the coastal zone may strengthen landfalling TCs. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172097919.97430863/v2"> <div class="blog-card__title"> External Drivers and Mesoscale Self-Organization of Shallow Cold Pools in the Trade-W... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Pouriya Alinaghi" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABa1BMVEX/imD/iV//i2H/jGP/jGL/i2L/iWD/g1f/f1H/gFL/f1L/ 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class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172097919.97430863/v2"> <div class='blog-card__preview-content'> Recent observations of the trade-wind regions highlight the covariability between cold-pool properties and mesoscale cloud organization. Given the covariability of organization with cloud cover and albedo, this suggests a potential impact of cold pools on the cloud radiative effect (CRE). To explore this, we use an ensemble of 103 large-domain, high-resolution, large-eddy simulations and investigate how the variability in cold pools is determined by large-scale external cloud-controlling factors (CCFs) and shaped by processes within the mesoscale. It is demonstrated that the size and frequency of occurrence of cold pools are strongly influenced by the near-surface horizontal wind speed and large-scale subsidence. The temporal evolution of cold pools is strongly correlated with the diurnality in radiation. Even without external variability, we find a strong intermittent behaviour in the evolution of cold pools, governed by a complex interplay between cold pools and clouds which expresses itself in the form of shallow squall lines. These squall lines result from precipitating downdrafts, cold pool outflows and the resulting gust fronts, reinforcing parent clouds. Cold pools influence the CRE of trade cumuli, but only when they exist during the day. This emphasizes the importance of the synchronization between cold-pool events and the diurnal cycle of insolation for the dependence of the CRE on cold pools. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172072997.78731343/v1"> <div class="blog-card__title"> Improving tropical cyclone rapid intensification forecasts with satellite measurement... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Ryan" width="24" height="24" class="user-profile-pic" src="https://d197for5662m48.cloudfront.net/images/user/800146/profile_image/thumbnail-9f6c431256feb0fba54dbedc26dba7f6.jpeg" /> </div> <div class="blog-card__second-avatar"> <img alt="Hui Su" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABWVBMVEVF0OJE0OJEz+FI0OJJ0eJH0OJG0OJK0eI2zN8wyt5Bz+FA zuEvyt44zOA8zeAtyt4ryd1t2uiE4OuH4Oxn2Ocuyt6W5O6A3+s9zuAyy9/k +Pr///9f1uY3zN9L0eI1zN9i1+bN8veM4e0xy95Ez+Ityd7X9fha1eVM0ePF 8PYfxtxX1OTz/P1u2ug/zuEsyd7Z9flW1OQzy98xy99b1eXI8fYXxNp43eqh 5/AEv9chx9yg5/Bg1uZS0+Qqyd3H8PZZ1eX6/f5o2ecryd4+zuCL4ez8/v6o 6fFQ0uPE8PW67fTC7/VL0eOp6fH+/v5Cz+EYxNsWxNo6zeBs2uhP0uNd1uU7 zeAUw9qy6/MHwNin6PHW9PhY1OXG8PYVxNqN4u00y99T0+T1/P1U0+Tj+PrM 8vej5/CS4+5+3uqc5u8+zuFO0uOf5vB13OmT4+6P4u1U1OQ5zeAAAAD9dEWF AAAAAWJLR0RyNg4NWAAAAAd0SU1FB+gLFRAXDUHA/qgAAAGGSURBVDgR3cHp dtJQFAbQ7343J0EDSRWj4oEGFWxplaRoHUsccGjrjLbO1nke3/+P4F24qI/Q vbGzGIwZjBlj8B+OAOAI6GAbWg8E4QlB3ws8n5hCorRrN4iwXAFtFM+UQ0v8 YwyiPXu90A+D6r5IElvdf+BgzRIThCSHtN6YTZt6OKkd0bHmUcsWHELax3Su Mt+oa2dhUY/PpSdU0fUJh5As16WenDyly6fP6Nlzcv6CrlSEcAjJcu1n3WJR Ly5c0stXyoO4dhUkHELiXJ1OXLumev3GaiLEBCHtXNfWb653tFPcivu376hW E0vCISTL9e69+L7oWjGs9QbJA9WHkRAOIVmuG9HqZlOXHz3WpcQ+eaorJUuD vwhpP9PnjSDd0BcvtzTnq9dv9O1QCIeQ5J3WS7NpU99n5Q869jGxJJwWsPnp 83xXvnz99n3oF/2tHz9/xQAx0SJ6gxD0u0Xqt+wwm8l+2xYxhTYAQQSWoHiB JySmcQQAR0AH2xmDMWMwYozBzvIHydQuhOQhDOgAAAAldEVYdGRhdGU6Y3Jl YXRlADIwMjQtMTEtMjFUMTY6MjM6MTMrMDA6MDDrH2nQAAAAJXRFWHRkYXRl Om1vZGlmeQAyMDI0LTExLTIxVDE2OjIzOjEzKzAwOjAwmkLRbAAAACB0RVh0 c29mdHdhcmUAaHR0cHM6Ly9pbWFnZW1hZ2ljay5vcme8zx2dAAAAGHRFWHRU aHVtYjo6RG9jdW1lbnQ6OlBhZ2VzADGn/7svAAAAGHRFWHRUaHVtYjo6SW1h Z2U6OkhlaWdodAA2MDB63r21AAAAF3RFWHRUaHVtYjo6SW1hZ2U6OldpZHRo ADYwMOkv7egAAAAZdEVYdFRodW1iOjpNaW1ldHlwZQBpbWFnZS9wbmc/slZO AAAAF3RFWHRUaHVtYjo6TVRpbWUAMTczMjIwNjE5My3OA/kAAAATdEVYdFRo dW1iOjpTaXplADE3NDE4QkJLM8ROAAAAPHRFWHRUaHVtYjo6VVJJAGZpbGU6 Ly90bXAvbGV0dGVyX2F2YXRhcnMvMi9IUy82OV8yMDhfMjI2LzYwMC5wbmer lgL0AAAAAElFTkSuQmCC " /> </div> </div> <div> <div class="blog-card__authors-text"> <div class="blog-card-author-list" style="width: 100%;"> <a href="/users/800146"><p class="blog-card__owner">Ryan Eusebi</p></a> <p class='blog-card__remaining-text'>and 10 more</p> </div> </div> <time datetime="2024-07-11" class="blog-card__date">July 11, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172072997.78731343/v1"> <div class='blog-card__preview-content'> Forecasting rapid intensification (RI) of tropical cyclones (TC) is a mission known for large errors. One under-researched factor that affects TC intensification is sea surface salinity (SSS), which is an important proxy for density stratification in certain ocean regions and can affect the surface enthalpy flux under a strengthening hurricane. To investigate the effects of SSS on TC RI, we use a previously built statistical model consisting of a variety of machine learning (ML) methods. A calibrator was trained on top of the ML models to correct probability forecasts. The ML model performance is improved with the addition of SSS in the Eastern North Pacific and the Caribbean subregion of the North Atlantic. Limited improvement is found in the Western North Pacific. In the Indian Ocean, SSS is also notably correlated with RI occurrence, but the TC samples are not sufficient to train ML models. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172106457.79163812/v1"> <div class="blog-card__title"> Multi-Site Fire Danger Prediction Using a Spatially Coherent Convolutional Neural Net... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Óscar Mirones" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABpFBMVEX/qAD/pwD/qAH/qgT/qgX/qQT/qQP/qQL/pQD/nQD/nAD/ 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hijQd7161F15/ERP+57pedYlvWi+1KvUEAWyal+r8KZSe6t3Se29PnR81KfU EG2s2qnpz9NT8Zeer9++R+7HTxf8+v3HecQ/LEc2sZFPRIkD6hYIkjpIzKBn jPEIeiWfLBsSJZ+YxTZwBpjD3PEXpUc67vgZztIAAAAldEVYdGRhdGU6Y3Jl YXRlADIwMjQtMTEtMjFUMTY6MjM6MTUrMDA6MDCIz1zqAAAAJXRFWHRkYXRl Om1vZGlmeQAyMDI0LTExLTIxVDE2OjIzOjE1KzAwOjAw+ZLkVgAAACB0RVh0 c29mdHdhcmUAaHR0cHM6Ly9pbWFnZW1hZ2ljay5vcme8zx2dAAAAGHRFWHRU aHVtYjo6RG9jdW1lbnQ6OlBhZ2VzADGn/7svAAAAGHRFWHRUaHVtYjo6SW1h Z2U6OkhlaWdodAA2MDB63r21AAAAF3RFWHRUaHVtYjo6SW1hZ2U6OldpZHRo ADYwMOkv7egAAAAZdEVYdFRodW1iOjpNaW1ldHlwZQBpbWFnZS9wbmc/slZO AAAAF3RFWHRUaHVtYjo6TVRpbWUAMTczMjIwNjE5NcStpswAAAATdEVYdFRo dW1iOjpTaXplADE4OTgwQkIx7qwYAAAAO3RFWHRUaHVtYjo6VVJJAGZpbGU6 Ly90bXAvbGV0dGVyX2F2YXRhcnMvMi9PTS8yNTVfMTY4XzAvNjAwLnBuZ58n /+oAAAAASUVORK5CYII= " /> </div> <div class="blog-card__second-avatar"> <img alt="Jorge Baño-Medina" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABUFBMVEVSvIlRvIhRvIlRu4hTvIlVvYtUvIpWvYxWvYtUvYpMuYVC tX5Ft4A6sng8s3o7s3k+tHtEtn9NuoVbv496y6RcwJBCtn53yqKd2byQ1LOU 1baH0K1oxJhHt4FSu4iX1rj///+b2LsiqWjC59Xy+fZJuINTvIqR1LOV1re1 4syZ17ljwpSu38jG6dg6snmR1LS2482Czqoyr3NAtXwwrnHs+PKW1re24s19 zKYmq2uBzqm55M/4/Pr0+/je8ug0sHVNuoaS1LS448/Z8OXG6NjY8OST1bVG t4E4sndKuYNZvo49tHszsHRKuINOuoZBtX31+/hvx50jqWmFz6sqrG7j9OxM uYSM0rDH6djp9vBpxZktrW+z4ctiwpTr9/Ha8Oay4cpAtX295dJqxZmAzaib 2LpIuIKf2b2V1raP07Jux5xBtX5Dtn5Pu4dUvYsAAACcOBXZAAAAAWJLR0Rv VQhhgQAAAAd0SU1FB+gLFRAXECLGknEAAAFWSURBVDgR3cFpWxJRGAbg58wz Zw6C4xkEU9x6GczIElQU963NMpNoQcsltbTF5f9/FLzkclB/gfeNB0op5eB+ ihG4B13t0jPGxNpA3EXEE3Gv3e+wQZIecRvRmUp3PeruyfT29ScGPA6ihaKx jyUb5qRhSD8ZJlooGvtU8uEzGUk9fyGjBU0iStHYouTDMRmfKE3KVDAMIoKk sUUph9MyM1uYk5yvSdxgnbFFKYfzsrAosrS84hIRdDVidlXy4Ut59Tr3Rt4G mkQTibV379c/ZCQfTks69DcW5OMmiGsOdaX3U7U0kZHy5zH5srH59Zuw5hLX HMaCLdkOOr/Lj51dGUntZWW/AhBNBBM/pe7g0B7JlV/JNhJNim7t8Hf2uGpx 0v1n9e+//2unHhFFlyXfT3pw231rO87ONdGK0MZcEPSMMTEN4hbFK2AT7nCU QoNSynHwwFwCFvUn4E8L6UAAAAAldEVYdGRhdGU6Y3JlYXRlADIwMjQtMTEt MjFUMTY6MjM6MTYrMDA6MDC5J0Z3AAAAJXRFWHRkYXRlOm1vZGlmeQAyMDI0 LTExLTIxVDE2OjIzOjE2KzAwOjAwyHr+ywAAACB0RVh0c29mdHdhcmUAaHR0 cHM6Ly9pbWFnZW1hZ2ljay5vcme8zx2dAAAAGHRFWHRUaHVtYjo6RG9jdW1l bnQ6OlBhZ2VzADGn/7svAAAAGHRFWHRUaHVtYjo6SW1hZ2U6OkhlaWdodAA2 MDB63r21AAAAF3RFWHRUaHVtYjo6SW1hZ2U6OldpZHRoADYwMOkv7egAAAAZ dEVYdFRodW1iOjpNaW1ldHlwZQBpbWFnZS9wbmc/slZOAAAAF3RFWHRUaHVt Yjo6TVRpbWUAMTczMjIwNjE5Nl2k93YAAAATdEVYdFRodW1iOjpTaXplADE1 MjkzQkJAWlfrAAAAPHRFWHRUaHVtYjo6VVJJAGZpbGU6Ly90bXAvbGV0dGVy X2F2YXRhcnMvMi9KQi84Ml8xODhfMTM3LzYwMC5wbmclK/hKAAAAAElFTkSu QmCC " /> </div> </div> <div> <div class="blog-card__authors-text"> <div class="blog-card-author-list" style="width: 100%;"> <a href="/users/697444"><p class="blog-card__owner">Óscar Mirones</p></a> <p class='blog-card__remaining-text'>and 3 more</p> </div> </div> <time datetime="2024-07-15" class="blog-card__date">July 15, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172106457.79163812/v1"> <div class='blog-card__preview-content'> Weather stations can represent local weather variability and extremes more reliably than gridded products and are therefore better suited for local climate impact applications like calculation of the Fire Weather Index (FWI), a multivariate index for wildfire danger assessment. However, the prediction at multiple sites poses the challenge of preserving spatial consistency across locations, requiring a suitable multi-site approach. This study evaluates the potential of Convolutional Neural Networks (CNNs) for statistical downscaling (SD) of FWI predictions across the Iberian Peninsula. We compare our CNN-Multi-Gaussian (CNN-MG) model against Generalized Linear Models (GLMs) and a benchmark single-site CNN approach. Our evaluation focuses on predictive accuracy, distributional congruence, spatial coherence and extreme events reproducibility using daily FWI data from 29 locations in Spain. The CNN-MG model, which integrates the covariance structure of the predictands, outperformed other methods in representing FWI distributions across both single and multisite scales. Moreover, our model provides greater physical interpretability via eXplainable Artificial Intelligence (XAI) techniques, while also emphasizing simplicity and ease of training. </div> </a> </div> </div> </div> <div class="blog-card"> <a href="/doi/full/10.22541/essoar.172072794.43697556/v1"> <div class="blog-card__image-container"> <img onerror="$(this).closest('a').remove()" height="200" class="blog-card__image-tag" loading="lazy" src="https://d197for5662m48.cloudfront.net/users/800632/articles/1182535-summer-mesoscale-convective-systems-in-convection-permitting-simulation-using-wrf-over-east-china/master/file/figures/Fig05-2_MCS_rainfall_pdf_6_districts/Fig05-2_MCS_rainfall_pdf_6_districts.png?1720727943" /> </div> </a> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172072794.43697556/v1"> <div class="blog-card__title"> Summer mesoscale convective systems in convection-permitting simulation using WRF ove... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Yutong Lu" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAAA+VBMVEW8qqS7qaO8qaO9rKa8q6W9q6W8qaS4pZ+zn5i4pZ63pJ25 p6C5pqC4pp/Gt7LVysbEtK+3pJ7HuLPWy8fBsKu/rqjVysfCsqz///+1opu6 qKHTx8TWy8ivmpLf19TSxsK1oZrYzsvb0s6nkIjUyMT6+fiynpe2o52xnZbU ycWxnJXd1dLPwr60n5nUyMW6p6H18/L5+Pj+/v60oJqynZbZz8vQxL+znpj9 /f22opy6qKK+rKa0oJm+raf8+/u3o527qKLRxcGtl5C2o5z7+/rZz8zFtbDX zcnNv7u7qaK5p6HFtrHa0M3VycbZzsvAsKq8qqO9q6YAAABxOTBdAAAAAWJL R0RSDWAtkAAAAAd0SU1FB+gLFRAXCt+kawsAAAEUSURBVDgR5cGJVoJAGAbQ 72skRiFIzfpttTJq2mgnQYtW25f3f5nKTucw9Ajei7HCHwB/TeAfQlUI0FGA 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class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABqlBMVEVSvIlRvIlRu4hVvYtTvIpTvIlWvYtUvIpPuodCtn5JuINL uYQ+tHs/tXxPu4c9tHtHt4FPuoZ4yqNkw5VFt4BhwpOJ0a+Ez6tQu4dOuoZ6 y6SM0rBvx5xEtn9txpz////K6tsjqWmW1reL0rA8s3pewJHF6Nc4sndWvYxR vIhUvYtpxZnB59SP07Lb8eY6snii28C95dI3sXfC59UiqWiQ1LPw+fRdwJFA tXzz+vf7/fzA5tQ3sXYjqWiO07Ke2b2t38c7s3ltxpuo3cSM0rF2yqLQ7d81 sXXJ6tpgwZK+5tNUvYpqxZnB59V0yaBsxptNuoZKuYQ5snhXvo1Gt4BpxZif 2r0vrnFvx51hwZNZv45EtoB2yqE9s3plw5Ykqmm14swep2XN69z+/v7h8+sx r3K+5dJGt4Fmw5bq9/FMuYXH6dkprG2K0q+v4Ml1yaGk28ErrW675NG14s3U 7uJFtoC3485Dtn/x+fVcwJDE6NY4sXdyyJ+a2Lqc2Lt9zaY+tHyq3sV1yaBK uIN7zKWU1bZNuoVav46n3cN7y6VAtX1XvoxXvYwAAAD4X97fAAAAAWJLR0SN Gwzi1QAAAAd0SU1FB+gLFRAXGVsaKtUAAAGeSURBVDgR3cELX0thAAbw5zzn bEczDEOl4zHG3ncrsxLFUcmIZmjKXe5yyf2S+y1y/dC2tVE/36D/H0uS46DO cfAfNqCKNViMcD1Goi4IEG7UJxYhlrXE/OXxFStBEi2rEhES/xCr/TVrk+vW 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ODhfMTM3LzYwMC5wbmdZtIhrAAAAAElFTkSuQmCC " /> </div> </div> <div> <div class="blog-card__authors-text"> <div class="blog-card-author-list" style="width: 100%;"> <a href="/users/800632"><p class="blog-card__owner">Yutong Lu</p></a> <p class='blog-card__remaining-text'>and 4 more</p> </div> </div> <time datetime="2024-07-11" class="blog-card__date">July 11, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172072794.43697556/v1"> <div class='blog-card__preview-content'> Mesoscale convective systems (MCSs) are active in East China during the summer, causing significant precipitation and extreme weather. Increasing MCS frequency and intensity with climate change highlights the need for better simulation and forecasting. Traditional global and regional models with coarse resolution unable to explicitly resolve convection fail to represent MCSs and their precipitation accurately. This study conducted a 22-year (2000–2021) JJA simulation at a convection-permitting resolution (4 km grid spacing) using the WRF model (WRF-CPM) over East China. The WRF-CPM model’s ability to reproduce MCSs was evaluated against satellite infrared-retrieved cloud top temperature, IMERG V06 precipitation, and global reanalysis data ERA5. Results show that WRF-CPM captures the observed MCS frequency and precipitation patterns but overestimates them in most areas. The model also accurately simulates the eastward propagation of MCSs, albeit at a slightly faster speed and longer duration. MCSs in WRF-CPM exhibit realistic life cycles in terms of cloud top temperature, convective core area, and precipitation. WRF-CPM tends to overestimate rainfall frequency over 20 mm/h while underestimates rainfall per MCS, possibly due to an overestimated number and area. The model captures the diurnal cycle of MCSs well in most of East China, though it shows a 2-hour delay in southeast China and fails to reproduce the midnight peak to the east of Tibetan Plateau, probably because of model’s limited ability to represent thermal diurnal variation over complex topography. WRF-CPM captures the shear effect on MCS precipitation, indicating increased precipitation with stronger shear and higher total column water vapor. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172072645.54448834/v1"> <div class="blog-card__title"> Distribution, Mixing, and Transformation of a Loop Current Ring Waters: The Case of G... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Mathieu Gentil" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABgFBMVEX+2hD+2g/+2Q/92Q/+2hP+2hX+2hT+2hL+2hH+2xb+2hb9 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2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172072645.54448834/v1"> <div class='blog-card__preview-content'> Mesoscale warm-core rings, known as Loop Current rings (LCRs) reshape the Gulf of Mexico water masses by redistributing large amounts of heat and salt laterally. LCRs also transform water masses via diapycnal mixing, but the mechanisms by which this occurs are poorly measured. Here, we present glider-MicroPod turbulence observations that reveal enhanced mixing below the mixed layer, along the eddy edges, driving the LCR’s heat, salt, and oxygen exchanges. Submesoscale stirring at the LCR’s edge yields interleavings of adjacent water masses, which facilitates double-diffusive mixing that transforms Subtropical Underwater into Gulf Common Water. Our findings highlight the need for ocean models to parameterize double-diffusive mixing processes directly resulting from submesoscale tracer stirring, which may be important at basin scale in the presence of LCRs in the Gulf of Mexico. </div> </a> </div> </div> </div> <div class="blog-card"> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.172097945.50489440/v1"> <div class="blog-card__title"> Hyperbolicity and Southern Hemisphere Persistent Synoptic Events </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Andrew Richard Axelsen" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABdFBMVEXiX1HhXlDiXlDiYVPgVEXfUkPfU0TgV0nmdWnnem/gV0jm eG3iYFL////ldGjlcWXiY1XeSTnuoprxs63dRTXxs6zvp6DdSDj88/H76+r4 29jfUkLhXE7hXU7fUUL43Nn76ef99/beSjrsm5LogHXognfeTT7iYlTfTj/n fnPog3nsmpHmeW3fUEHiYVTzvbfjZVj31NHdRjbdRjX2zcniY1bzwLvdRDTh W0365OHZMiDYKhj1ysbhWUrhWkzYKxjZMR/54N3gVkfhW0ziX1LiX1DiYlXe SzzqjIL0x8L1yMP54t/toJfeTT3eTj7tnJP65+XqkIbeSjvdRzf308/++/v+ /fz76+n66ObeSzv+/Pz77Ov42tfiYFP54N7bOinaNSP20c3hXU/31dHaNSTb OSj53tvgVUbxta7tnZTjZFfiZFbxtK7wrqfqj4XsmZDyubPrlYzvq6ThWkvu pp7rkYfvp5/hXE3vqqPsl47fTz8AAADzsHetAAAAAWJLR0R7T9K1/AAAAAd0 SU1FB+gLFRAXBtYSJyAAAAFxSURBVDgR5cEJQwxxHAbg9/3N1mbMW/9hGTEl g2bdV0uujWpHhygkue+jdYfw6Y3J2uQb8Dz43zCHAnP4i5nngcgRnmeG9YhS B0DAiM4SiD+RKHdtKBMk4G/s8kFiDWNQ9qTuDo/0Onsk5wc0tBlduEnaXHGk q2yRtkaOhjYiCLf1bteOGOjr186BXQlA/Gb0+ru1e4/2DqZpdZ/2H9DBQ4dp aCFd5YiOxjp2PE1PDAk1nTzlSLQQwyWdPnP2nOLz9bqGRi5c1OjYOBv4hdml CQ1MTk3r8syVq5qempzV3LWMhlVkev2GeudvLujW4uKsFm7P39HdyCOxivdG qfsPouThI2WP9eRpEj17rtoLjygYs+SlXoVLzcEJvX6jtzPNpeSd3icZDT8Z 4X/42FwOEA9/+jz3ZWUFwbL7+s0HDAUjvkd1kOgLq9UwBomxqAoaWpjWxgkQ Lk0dCBC1lGhjDjkWkGMOazQMBcuhYA38Q34ARU0uXV3st5AAAAAldEVYdGRh dGU6Y3JlYXRlADIwMjQtMTEtMjFUMTY6MjM6MDYrMDA6MDB1jUbpAAAAJXRF WHRkYXRlOm1vZGlmeQAyMDI0LTExLTIxVDE2OjIzOjA2KzAwOjAwBND+VQAA ACB0RVh0c29mdHdhcmUAaHR0cHM6Ly9pbWFnZW1hZ2ljay5vcme8zx2dAAAA GHRFWHRUaHVtYjo6RG9jdW1lbnQ6OlBhZ2VzADGn/7svAAAAGHRFWHRUaHVt Yjo6SW1hZ2U6OkhlaWdodAA2MDB63r21AAAAF3RFWHRUaHVtYjo6SW1hZ2U6 OldpZHRoADYwMOkv7egAAAAZdEVYdFRodW1iOjpNaW1ldHlwZQBpbWFnZS9w bmc/slZOAAAAF3RFWHRUaHVtYjo6TVRpbWUAMTczMjIwNjE4NkS/xjcAAAAT dEVYdFRodW1iOjpTaXplADEzODM3QkK0B+TvAAAAO3RFWHRUaHVtYjo6VVJJ AGZpbGU6Ly90bXAvbGV0dGVyX2F2YXRhcnMvMi9BQS8yMjZfOTVfODEvNjAw LnBuZ/qgv4oAAAAASUVORK5CYII= " /> </div> <div class="blog-card__second-avatar"> <img alt="Terence John O'Kane" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAAAAABWESUoAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAAAAmJLR0QAAKqNIzIAAAAHdElNRQfoCxUQGQM4+/4hAAABY0lEQVQ4 EYXBwWoTYRSG4fc7+ZtJYlKQiqumKAhuXAhegBvFgnoFXl527hVcKL0ElW5E sCJWColKJW0zxDnHzEwjVsT/eTTh/4wMI8PIMDKMDCMjUQt+U9AQrURDRssD GXhwLgGBlguxEjbAfp649ZKLRmJFy8vbpSCM93aabg7ODk4uuaglVqwc36F1 cLzzELj77PPQEaAJhKpitOg+/vG8b9PiCS+nW/d5Oi9cgAGKTnk0ncHRbLa4 zd6bcv8VtxYigMSKorORumjQpxzz8crG1ifG5grAaIS7g7tjEB5i1K+oGTUB 4p+MvwRICuaLDjXjAvNDtr/F96scVhasGGtBQPRec+/G6bVd3haBgMSa0RVe HL948AjY+zpyappQC7l2yi+JsPngerH8MB+5qCUaCvN31gvkw+V+qLdZiUai pbBhuECeNsEr0UqcU1S0ouIPiTXREhcYGUaGkWFkGBlGxi+C0oD05/sY6wAA ACV0RVh0ZGF0ZTpjcmVhdGUAMjAyNC0xMS0yMVQxNjoyNTowMyswMDowMCqr GQkAAAAldEVYdGRhdGU6bW9kaWZ5ADIwMjQtMTEtMjFUMTY6MjU6MDMrMDA6 MDBb9qG1AAAAIHRFWHRzb2Z0d2FyZQBodHRwczovL2ltYWdlbWFnaWNrLm9y Z7zPHZ0AAAAYdEVYdFRodW1iOjpEb2N1bWVudDo6UGFnZXMAMaf/uy8AAAAY dEVYdFRodW1iOjpJbWFnZTo6SGVpZ2h0ADYwMHrevbUAAAAXdEVYdFRodW1i OjpJbWFnZTo6V2lkdGgANjAw6S/t6AAAABl0RVh0VGh1bWI6Ok1pbWV0eXBl AGltYWdlL3BuZz+yVk4AAAAXdEVYdFRodW1iOjpNVGltZQAxNzMyMjA2MzAz /4hs3gAAABJ0RVh0VGh1bWI6OlNpemUANzg0MUJCuaOc8QAAAD10RVh0VGh1 bWI6OlVSSQBmaWxlOi8vdG1wL2xldHRlcl9hdmF0YXJzLzIvVE8vMTYzXzE2 M18xNjMvNjAwLnBuZ1F8qIcAAAAASUVORK5CYII= " /> </div> </div> <div> <div class="blog-card__authors-text"> <div class="blog-card-author-list" style="width: 100%;"> <a href="/users/794287"><p class="blog-card__owner">Andrew Richard Axelsen</p></a> <p class='blog-card__remaining-text'>and 3 more</p> </div> </div> <time datetime="2024-07-14" class="blog-card__date">July 14, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.172097945.50489440/v1"> <div class='blog-card__preview-content'> Predicting the occurrence of coherent blocking structures in synoptic weather systems remains a challenging problem that has taxed the numerical weather prediction community for decades. From a mathematical perspective, the underlying factor behind this difficulty is the so-called “loss of hyperbolicity” known to be linked with the alignment of dynamical vectors characterizing the growth and decay of flow instabilities. We introduce measures that utilize the close link between hyperbolicity, the alignment of Lyapunov vectors, and their associated growth and decay rates to characterize the dynamics and lifecycles of persistent synoptic events in the mid-troposphere of the Southern Hemisphere. These measures reveal a general loss of hyperbolicity that typically occurs during onset and decay of a given event, and a gain of hyperbolicity during the persistent mature phase. Facilitating this analysis in a typically high dimensional system first requires the extraction of the relevant observed coherent structures, i.e. feature space, and the generation of a reduced-order model for constructing the tangent space necessary for dynamical analysis. We achieve this through the combination of principal component analysis and a non-parametric, temporally regularized, vector auto-regressive clustering method. Analysis of the primary blocking sectors reveals hyperbolic dynamics that are consistent between metastable states and whose dynamics span the tangent subspace defined by the leading physical modes. The insights from this work are not only important for dynamical approaches applicable to high dimensional multi-scale systems, but are also of direct relevance to the development of modern operational ensemble numerical weather prediction systems. </div> </a> </div> </div> </div> <div class="blog-card"> <a href="/doi/full/10.22541/essoar.171820795.52152814/v1"> <div class="blog-card__image-container"> <img onerror="$(this).closest('a').remove()" height="200" class="blog-card__image-tag" loading="lazy" src="https://d197for5662m48.cloudfront.net/users/524098/articles/1108889-evaluating-cloud-properties-at-scott-base-comparing-ceilometer-observations-with-era5-jra55-and-merra2-reanalyses-using-an-instrument-simulator/master/file/figures/Figure1/Figure1.png?1732726516" /> </div> </a> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.171820795.52152814/v1"> <div class="blog-card__title"> Evaluating Cloud Properties at Scott Base: Comparing Ceilometer Observations with ERA... </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Adrian J. McDonald" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABv1BMVEXiX1HiXlDiX1DhXlDiYFLiYlTiYFPiYlXhWUvfUEDhW0zi X1LgVUbeTDzfUEHiXlHhXU7fTj/eTD3gWEnjZFfohHniYVThWkvgV0jmd2vr lIvphnvhXE7qjILrk4rkb2LdRTX2z8r////zv7ndRjbiY1XdRzfzwrzlcGTf U0TiYVPqjYPuoZneSjr9+fjiY1byubPdRzb2z8vtm5PdSDjtnZTyurTjZlny u7X+/PvfUkPgV0n88vH87+7319TdRTTyvLbupJzpiX/fUULtoJjwrabZMiD4 2dbeSTnjZ1r31tPdRDTeTT7++/r43NnognfsmZDyuLHXIg/lcWXuopneSzzh WkzxsqvfUUHqj4Xog3j1ycX1y8b1zMj76unmeGzogXbvqqPeTj788vD99fT+ /v399PPmeW7bOijrkIfbOSj99/b66Ob++vnZMB7cQzLbOyreTT3aNyXnfXHz vLfZLRvrkYfaNiXph3zbOinsm5LsmI/gVkfkbWD88O/eSjvgVEXrlYz+/v7t npXtnZXmdWnwsarogHXphXvwsKnne2/lcGPgWErsl47pioDgU0XldGjfU0Ph W03gVkgAAACzu7gRAAAAAWJLR0SUf2dKFQAAAAd0SU1FB+gLFRAXCt+kawsA AAHFSURBVDgR3cEHW5JhGAXg83hewCRsUEaJoxMvBfUJLjSz0mxoqdEw23vv Pa1o2S7LP9yneTX+gveN+cmqMMsM/zGSBnAGQgwZ/kEXcQQYjUVAgIjEHPEX XfWCmjjpFiZqF4HE4iVLk46GOYxXL1tetwIutXJVfYpAOt3Q2JR0xG9krHm1 1mRiPrtWWpfLRxLrpQ2Bp2GG0SWjUksuXcgWpWLG17W2Se2Bp2GG0Xd0qqSG RFe2Wy0be7jJq1edgadhBuGCzerQlq1dmT71a9tAYrt2qD3wNISM+Z4m9e3c JV8zWNKQdu8ZHhndq3LgaQgZfWafYvsP6ODYWFGHxnV4SEeOqhx4GkJEOjei Y8dP6GRPtqhTeZ0+o9ZGlQNPA2CMnK3XufMXLvbq0uVuXbl67fqN0ZudKgee BoCM3WrT0O07d+/p/oOSHj7qlx4/eapngacBYHTiuV68zOdZkQZLetXs9boy +EZvA08DQJd6N/m+EmU09+EjPk1+/pL7+u17cmp8asIRIaNLZX84gm4g+7OS Tcbjw7UuPp2ddjTMoivkCYB1BeQLjoxESFdwxBxjCAB/M4aMpOEPw6wqAwyA IWSYR34BxahJMNI1pA0AAAAldEVYdGRhdGU6Y3JlYXRlADIwMjQtMTEtMjFU MTY6MjM6MTArMDA6MDDa93NNAAAAJXRFWHRkYXRlOm1vZGlmeQAyMDI0LTEx LTIxVDE2OjIzOjEwKzAwOjAwq6rL8QAAACB0RVh0c29mdHdhcmUAaHR0cHM6 Ly9pbWFnZW1hZ2ljay5vcme8zx2dAAAAGHRFWHRUaHVtYjo6RG9jdW1lbnQ6 OlBhZ2VzADGn/7svAAAAGHRFWHRUaHVtYjo6SW1hZ2U6OkhlaWdodAA2MDB6 3r21AAAAF3RFWHRUaHVtYjo6SW1hZ2U6OldpZHRoADYwMOkv7egAAAAZdEVY dFRodW1iOjpNaW1ldHlwZQBpbWFnZS9wbmc/slZOAAAAF3RFWHRUaHVtYjo6 TVRpbWUAMTczMjIwNjE5MLTHUkMAAAATdEVYdFRodW1iOjpTaXplADIwMzg1 QkKgLu6iAAAAO3RFWHRUaHVtYjo6VVJJAGZpbGU6Ly90bXAvbGV0dGVyX2F2 YXRhcnMvMi9BTS8yMjZfOTVfODEvNjAwLnBuZxppr+0AAAAASUVORK5CYII= " /> </div> <div class="blog-card__second-avatar"> <img alt="Peter Kuma" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABaFBMVEX/imD/il//iV//imH/jGP/jGL/iWD/hVr/f1H/gFL/f1L/ gFP/iF3/flD/iV7/fU7/fE3/h13/hlv/kWr/o4P/nXr/nnv/nHj/g1f/i2H/ h1z/q43/rI//tp3/jmb/jWT/ekv/u6P/////pYb/ekr/dUT/08T/39T/gVX/ tJr/v6j/kGj/mXT/r5L/jmX/fk//c0H/uqL/6OD/d0f/sJP/ckD/bjr/s5j/ dUP/pYX/+Pb/hFj/i2L/sZX/dEL/bzz/sJT/tJn/dEP/+PX/jWX/jGT/tZr/ vKT/l3H/nnz/+vj/mnb/e0z//fz/7un/wav/bjv/j2f/t53/uqH/d0b//Pv/ tZv/0MD/rZD/u6L/fE7/qYv/ooD/7eb/eUn/ajX/fU//hFn/hFf/cj//2s3/ wq3/dkX/e0v//v7//f3/mXX/t57/hlr/oX//mnX/xrL/uJ7/uJ//iF7/p4j/ x7P/eEj/eEcAAABaX9HMAAAAAWJLR0R3RmT51wAAAAd0SU1FB+gLFRAXCt+k awsAAAFySURBVDgR3cGHQhNBAATQ2clGEkmOIxi93ah7jlhiLGBXsGAv2AWx 41lQUex+vxdyifALvIcNzRiswz4wB8Mc1mLJlnMgYS1IWAtiYBMxVKlurg7X LFmvk6VoJB4FDQpEY2xLc2tzWzLifKvl4ZPtO3Z6ED1kSHdp1e7xmtSI9uzV vv0A0UOGtK0DnYOHpMNHpNGJSR091nBEgQxpW8dP1E5O6tRpaeKMzlanpok+ MqRtnTuPCxc1c0mXr0idylVigAzpNV3HjZu3dHtWd+7q3v0HEf4jQ/pQqx49 9nPKjQ2XiQEypPN6svB0YfpZbWpOz1/o5SuA6CND2lbr9WL8xvpMit++0/sP gegjw9KM5usd6+Czj/JJ8kmfxy2JHjIsLWs5tST8F6mB+KvUGXJEgS5Z+baS OBKR//7D/ywv/vrdTBxRIEvZn6xEgoji2Qh0lb+ZIzFAFxyRI6wFQRscsQa7 0MUcwC6sY1AwBjljsJH8A6eHMRpBqrK8AAAAJXRFWHRkYXRlOmNyZWF0ZQAy MDI0LTExLTIxVDE2OjIzOjEwKzAwOjAw2vdzTQAAACV0RVh0ZGF0ZTptb2Rp ZnkAMjAyNC0xMS0yMVQxNjoyMzoxMCswMDowMKuqy/EAAAAgdEVYdHNvZnR3 YXJlAGh0dHBzOi8vaW1hZ2VtYWdpY2sub3JnvM8dnQAAABh0RVh0VGh1bWI6 OkRvY3VtZW50OjpQYWdlcwAxp/+7LwAAABh0RVh0VGh1bWI6OkltYWdlOjpI ZWlnaHQANjAwet69tQAAABd0RVh0VGh1bWI6OkltYWdlOjpXaWR0aAA2MDDp L+3oAAAAGXRFWHRUaHVtYjo6TWltZXR5cGUAaW1hZ2UvcG5nP7JWTgAAABd0 RVh0VGh1bWI6Ok1UaW1lADE3MzIyMDYxOTC0x1JDAAAAE3RFWHRUaHVtYjo6 U2l6ZQAxMzcxMkJCmpV5XgAAADx0RVh0VGh1bWI6OlVSSQBmaWxlOi8vdG1w L2xldHRlcl9hdmF0YXJzLzIvUEsvMjU1XzEzOF85Ni82MDAucG5nEEMgcAAA AABJRU5ErkJggg== " /> </div> </div> <div> <div class="blog-card__authors-text"> <div class="blog-card-author-list" style="width: 100%;"> <a href="/users/524098"><p class="blog-card__owner">Adrian J. McDonald</p></a> <p class='blog-card__remaining-text'>and 6 more</p> </div> </div> <time datetime="2024-06-12" class="blog-card__date">June 12, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.171820795.52152814/v1"> <div class='blog-card__preview-content'> This study compares CL51 ceilometer observations made at Scott Base, Antarctica, with statistics from the ERA5, JRA55, and MERRA2 reanalyses. To enhance the comparison we use a lidar instrument simulator to derive cloud statistics from the reanalyses which account for instrumental factors. The cloud occurrence in the three reanalyses is slightly overestimated above 3km, but displays a larger underestimation below 3 km relative to observations. Unlike previous studies, we see no relationship between relative humidity and cloud occurrence biases, suggesting that the cloud biases do not result from the representation of moisture. We also show that the seasonal variation of cloud occurrence and cloud fraction, defined as the vertically integrated cloud occurrence, are small in both the observations and the reanalyses. We also examine the quality of the cloud representation for a set of synoptic states derived from ERA5 surface winds. The variability associated with grouping cloud occurrence based on synoptic state is much larger than the seasonal variation, highlighting synoptic state is a strong control of cloud occurrence. All the reanalyses continue to display underestimates below 3km and overestimates above 3km for each synoptic state. But, the variability in ERA5 statistics matches the changes in the observations better than the other reanalyses. We also use a machine learning scheme to estimate the quantity of super-cooled liquid water cloud from the ceilometer observations. Ceilometer low-level super-cooled liquid water cloud occurrences are considerably larger than values derived from the reanalyses, further highlighting the poor representation of low-level clouds in the reanalyses. </div> </a> </div> </div> </div> <div class="blog-card"> <a href="/doi/full/10.22541/essoar.171805176.62108514/v1"> <div class="blog-card__image-container"> <img onerror="$(this).closest('a').remove()" height="200" class="blog-card__image-tag" loading="lazy" src="https://d197for5662m48.cloudfront.net/images/tagdashboard/banner/large-243fcdb05f224a75295a129767fd9215.jpg" /> </div> </a> <div class="blog-card__container"> <div class='blog-card__top-row'> </div> <div class='blog-card__heading-container '> <a href="/doi/full/10.22541/essoar.171805176.62108514/v1"> <div class="blog-card__title"> Convectively-Coupled Global Rossby Modes in an Idealized Moist GCM </div> </a> </div> <div class="blog-card__author-container"> <div class="blog-card__author-information"> <div class="blog-card__images-container"> <div class="blog-card__first-avatar"> <img alt="Cameron MacDonald" width="24" height="24" class="user-profile-pic" src="data:image/jpg;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAMAAABEpIrGAAAABGdBTUEAALGP C/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3Cc ulE8AAABtlBMVEW7Zcq7ZMq6ZMm8aMu8acu7Zsq7Z8q8Z8q6Y8mzVMSxT8Ky UcO3XMa2W8azU8O1V8W6YsmzU8S4X8i7ZMm2WsbNjtjYp+DUnt2/b82xUMK3 XcfGftLRmdvKiNa5YsnPktnQltq6ZMr8+Pz////ZquG0VsToy+2/bs3SmdzP k9q0V8X79vy5YcjAcc7y4/XKh9WqPrzmx+vds+SxTsLv3PPPlNrftuapPryu SMDEetHw3fOnObrnyu369PvAcM347/mwTsLlxevHgdO1WMW9asvIgtTIg9Su ScDmyOzcseSyUMPcsOTZqeHMjdewTcHDeNC4YMjBcs7pze6vS8G0VcTr0e/J hNTMi9ewTcLDedDkwurDd9DJhtXlxuvGf9O1WcXFfNKvSsC9a8zBdM/Gf9Lf t+atRr/eteWyUsPSmtzarOKqP72oOrvmx+zDedGvScDy4fT+/v7q0e+lNLnw 3/OpPbzmxuvFfdKrQb3br+OqQL3Lite8Z8vguebnyuz69fvnyezOkNm3XMfY puDWo9/Bc8/Lida+bMy5YMi1WcbUnd3Li9fdsuTBc864Xse4X8e9acsAAAAC ipKWAAAAAWJLR0SRDw2+mgAAAAd0SU1FB+gLFRAXIAQfot0AAAG8SURBVDgR 3cGHQtNgGAXQ+90/aZpgxUKrUASBK4pacOCelIoCKg6qFVBxi3uLA/fC7SOb WhSegXOwsJgZKgxVZpiPVWAFYowZ5hDO83yCCReAAOGcT/zHRDKMahY5IrW4 FiSxJEzXgfWoYpCpzS5d1tDo55qWN+dQj5bkitaGOp+oaGMi49oVW9nRuEpa nfJdTae0JnQ0xIjk2nVqzXd1a/2GjdKmHs+PNkvZ0NEAGF16i7Zu4/Yd2rlr t9r3pP3UXu1TNnQ0AEavt6C+4n6w/8DBAQ2qPzN0SId1JHQ0AEY3XNDRYoBk 5thwQcd1YqSkk6dUDh0NgNGdLmi0GJC5luGC8mMaGteZssqhowEwer1ndW7C Q3L0/IWCLl7S5Su6ek3l0NEAGN3kdd246UbG1X3rtu7c1b37Dx4OqBw6GmJE PiU1l/BI2cdPNPX0mdT3fEwvSo6GGDndMaWKl6XolZqiLr0u9r7R29DR8BeD 0rvO9x8+Rn7q0+DnmS9fv2Vyzd9//PSJWZzOT0aNqWn6E9EMkC76mOj55bMN /xDO8xIEAw+kC8jgt0/MYRUYA2cZ5jMzVBgAQ8ywgPwBgVdDItj/QwsAAAAl dEVYdGRhdGU6Y3JlYXRlADIwMjQtMTEtMjFUMTY6MjM6MTQrMDA6MDAuuFde AAAAJXRFWHRkYXRlOm1vZGlmeQAyMDI0LTExLTIxVDE2OjIzOjE0KzAwOjAw X+Xv4gAAACB0RVh0c29mdHdhcmUAaHR0cHM6Ly9pbWFnZW1hZ2ljay5vcme8 zx2dAAAAGHRFWHRUaHVtYjo6RG9jdW1lbnQ6OlBhZ2VzADGn/7svAAAAGHRF WHRUaHVtYjo6SW1hZ2U6OkhlaWdodAA2MDB63r21AAAAF3RFWHRUaHVtYjo6 SW1hZ2U6OldpZHRoADYwMOkv7egAAAAZdEVYdFRodW1iOjpNaW1ldHlwZQBp bWFnZS9wbmc/slZOAAAAF3RFWHRUaHVtYjo6TVRpbWUAMTczMjIwNjE5NLOq lloAAAATdEVYdFRodW1iOjpTaXplADIyOTA0QkJjIBXQAAAAPXRFWHRUaHVt Yjo6VVJJAGZpbGU6Ly90bXAvbGV0dGVyX2F2YXRhcnMvMi9DTS8xODdfMTAx XzIwMi82MDAucG5nCKoURQAAAABJRU5ErkJggg== " /> </div> <div class="blog-card__second-avatar"> </div> </div> <div> <div class="blog-card__authors-text"> <div class="blog-card-author-list" style="width: 100%;"> <a href="/users/547265"><p class="blog-card__owner">Cameron MacDonald</p></a> <p class='blog-card__remaining-text'>and 3 more</p> </div> </div> <time datetime="2024-06-10" class="blog-card__date">June 10, 2024</time> </div> </div> </div> <div class='blog-card__preview-content-container'> <a href="/doi/full/10.22541/essoar.171805176.62108514/v1"> <div class='blog-card__preview-content'> A document by Cameron MacDonald. 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