{"id":2,"date":"2023-11-03T05:16:45","date_gmt":"2023-11-03T05:16:45","guid":{"rendered":"http:\/?page_id=2"},"modified":"2025-06-06T12:52:50","modified_gmt":"2025-06-06T12:52:50","slug":"sample-page","status":"publish","type":"page","link":"https:\/\/ucadre.org\/","title":{"rendered":"About"},"content":{"rendered":"\r\n<p><iframe loading=\"lazy\" title=\"CADRE: The Next Generation of Data Assimilation\" width=\"625\" height=\"352\" src=\"https:\/\/www.youtube.com\/embed\/rgAN4Wx1iTo?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\r\n<p><strong>What is Data Assimilation?<\/strong><\/p>\r\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignright  wp-image-299\" src=\"http:\/\/10.197.12.230\/wp-content\/uploads\/2024\/12\/fig1-1-1024x450.png\" alt=\"\" width=\"341\" height=\"150\" srcset=\"https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig1-1-1024x450.png 1024w, https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig1-1-300x132.png 300w, https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig1-1-768x337.png 768w, https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig1-1-1536x675.png 1536w, https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig1-1-2048x899.png 2048w, https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig1-1-624x274.png 624w\" sizes=\"auto, (max-width: 341px) 100vw, 341px\" \/><\/p>\r\n<p>Data assimilation (DA) is the science that fuses observations with numerical model outputs to obtain an analysis that best estimates the status of the Earth system as it evolves over time.<\/p>\r\n<p>DA is trans-disciplinary in nature, requiring an understanding of mathematical algorithms, physical processes, observations, modeling, high performance computing, and data science (Wang, X. 2022).<\/p>\r\n<p><strong>Why is Data Assimilation important?<\/strong><\/p>\r\n<p>Data assimilation plays a critical role in weather and climate prediction, including<\/p>\r\n<ul>\r\n<li style=\"list-style-type: none;\">\r\n<ul>\r\n<li>Providing starting points for daily forecasts<\/li>\r\n<li>Providing valuable datasets (e.g., reanalysis)\u00a0<\/li>\r\n<li>Optimizing observation network design<\/li>\r\n<li>Correcting\/keeping numerical models on track<\/li>\r\n<li>Understanding Earth system predictability and dynamics<\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>\r\n<p><strong>What are the challenges for Data Assimilation?<\/strong><\/p>\r\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignright  wp-image-300\" src=\"http:\/\/10.197.12.230\/wp-content\/uploads\/2024\/12\/fig2-1-1024x975.png\" alt=\"\" width=\"355\" height=\"338\" srcset=\"https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig2-1-1024x975.png 1024w, https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig2-1-300x286.png 300w, https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig2-1-768x731.png 768w, https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig2-1-624x594.png 624w, https:\/\/ucadre.org\/wp-content\/uploads\/2024\/12\/fig2-1.png 1066w\" sizes=\"auto, (max-width: 355px) 100vw, 355px\" \/><\/p>\r\n<p>Data assimilation is facing significant challenges associated with the future landscape of high-resolution, multiscale, coupled earth system modeling, and the large amount of diverse and complex observations (Wang, X. 2022).<\/p>\r\n<p>World-wide data assimilation workforce gap is\u00a0 identified in the US Congressionally-mandated Priorities for Weather Research (PWR) report (2021) and in the Transatlantic Data Science Academy (TDSA) phase 1 report (Dance et al. 2024)<\/p>\r\n<p>Sustained support of innovative data assimilation research is lacking.<\/p>\r\n<p><strong>How will CADRE address these challenges?<\/strong><\/p>\r\n<p>CADRE is a<span style=\"font-size: 1rem;\"> comprehensive, collaborative, integrated research, education and R2O2R (Research to Operations to Research) program that aims to<\/span><\/p>\r\n<p>(1) Increase the number of graduate students and postdocs formally trained in DA with NOAA UFS (Unified Forecast System) and JEDI (Joint Effort for Data assimilation Integration) DA system work experience<\/p>\r\n<p>(2) Enhance the national and international DA workforce pipeline development through training and outreach\u00a0<\/p>\r\n<p>(3) Seek solutions through JEDI to challenging DA issues in the UFS short range (RRFS, HAFS), medium range (GFS) and sub-seasonal to seasonal (S2S) predictions<\/p>\r\n<p>(4) Promote intellectual and technical exchanges in R2O and O2R<\/p>\r\n<p><strong>News:<\/strong><\/p>\r\n<p><a href=\"https:\/\/ucadre.org\/?page_id=479\">CADRE, in collaboration with EPIC, organized their first public data assimilation training event in Fort Collins, CO<\/a><\/p>\r\n<p><a href=\"http:\/\/ucadre.org\/?page_id=508\">Daryl Kleist and Xuguang Wang gave guest lectures to DA students at University of Maryland, Pennsylvania State University and Colorado State University (5\/1\/25)<\/a><\/p>\r\n<p><a href=\"http:\/\/ucadre.org\/wp-content\/uploads\/2025\/03\/Draft-DA-Training-Flyer-v5.pdf\" target=\"_blank\" rel=\"noopener\">CADRE announces public DA training opportunity<\/a>\u00a0(12\/31\/24)<\/p>\r\n<p><a href=\"https:\/\/www.youtube.com\/watch?v=rgAN4Wx1iTo\" target=\"_blank\" rel=\"noopener\">Short Film Introducing CADRE at 2024 AGU annual meeting<\/a> (12\/9\/24)<\/p>\r\n<p><a href=\"https:\/\/www.noaa.gov\/news-release\/biden-harris-administration-announces-66-million-for-new-data-assimilation-consortium\" target=\"_blank\" rel=\"noopener\">NOAA Announces establishment of CADRE<\/a> (5\/21\/24)<\/p>\r\n<p><strong>External Links:<\/strong><\/p>\r\n<p><a href=\"https:\/\/ufs.epic.noaa.gov\/\" target=\"_blank\" rel=\"noopener\">NOAA Unified Forecast System (UFS)<\/a><\/p>\r\n<p><a href=\"https:\/\/www.metoffice.gov.uk\/research\/approach\/collaboration\/transatlantic-data-science-academy\">Transatlantic Data Science Academy (TDSA)<\/a><\/p>\r\n<p><strong>Cited References:<\/strong><\/p>\r\n<p><a href=\"https:\/\/sab.noaa.gov\/wp-content\/uploads\/2021\/12\/PWR-Report_Final_12-9-21.pdf\" target=\"_blank\" rel=\"noopener\">PWR report (2021)<\/a><\/p>\r\n<p><a href=\"https:\/\/ams.confex.com\/ams\/2022SCM\/meetingapp.cgi\/Session\/62501\" target=\"_blank\" rel=\"noopener\">Wang, X. (2022)<\/a><\/p>\r\n<p><a href=\"https:\/\/zenodo.org\/records\/11191276\" target=\"_blank\" rel=\"noopener\">Dance et al. (2024)<\/a><\/p>\r\n<p>&nbsp;<\/p>\r\n","protected":false},"excerpt":{"rendered":"<p>What is Data Assimilation? Data assimilation (DA) is the science that fuses observations with numerical model outputs to obtain an analysis that best estimates the status of the Earth system as it evolves over time. DA is trans-disciplinary in nature, requiring an understanding of mathematical algorithms, physical processes, observations, modeling, high performance computing, and data [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"","meta":{"footnotes":""},"class_list":["post-2","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ucadre.org\/index.php?rest_route=\/wp\/v2\/pages\/2","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ucadre.org\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ucadre.org\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ucadre.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ucadre.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2"}],"version-history":[{"count":42,"href":"https:\/\/ucadre.org\/index.php?rest_route=\/wp\/v2\/pages\/2\/revisions"}],"predecessor-version":[{"id":577,"href":"https:\/\/ucadre.org\/index.php?rest_route=\/wp\/v2\/pages\/2\/revisions\/577"}],"wp:attachment":[{"href":"https:\/\/ucadre.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}