{"id":851,"date":"2023-07-02T20:42:07","date_gmt":"2023-07-02T19:42:07","guid":{"rendered":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/?page_id=851"},"modified":"2023-07-02T20:42:07","modified_gmt":"2023-07-02T19:42:07","slug":"abstract090","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract090\/","title":{"rendered":"Abstract 090"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text]Abstract ID:<\/strong> 090<\/p>\n

Assessing opportunities for improved coastal data assimilation in ocean model analyses and forecasting systems<\/h2>\n

Lead Author:<\/strong> Matthew Widlansky
\nCooperative Institute for Marine and Atmospheric Research, School of Ocean and Earth Science and Technology, University of Hawai\u2019i at M\u0101noa, United States of America
\n<\/span><\/p>\n

Keywords:<\/strong> monthly ocean forecasting, sea level variability, ocean heat content, ocean data assimilation<\/p>\n

Abstract:<\/strong> Satellite altimetry measurements of sea surface height provide near-global ocean state observations on sub-monthly time scales, which are not always utilized by climate forecasting systems. As early as the mid-1990s, attempts were made to assimilate altimetry observations to initialize climate models. These experiments demonstrated improved ocean forecasting skill, especially compared to experiments that did not assimilate subsurface ocean temperature information. Nowadays, some operational climate forecasting models utilize altimetry in their assimilation systems, whereas others do not. Here, we assess the impact of altimetry assimilation on analyses and monthly prediction skill of ocean variables in two climate forecasting systems that are from the European Centre for Medium-Range Weather Forecasts (SEAS5) and the Australian Bureau of Meteorology (ACCESS-S). We show that assimilating altimetry improves the initialization of subsurface ocean temperatures, as well as forecasts of monthly variability in upper-ocean heat content and sea level. Skill improvements are largest in the subtropics, especially away from the shallow waters over coastal shelves. Elsewhere, the skill improvements are minimal. In summary, we find that utilizing altimetry observations improves the overall global ocean forecasting skill, at least for upper-ocean heat content and sea level in the open ocean. We compare these results with the coastal ocean depicted in the Copernicus GLORYS12 reanalysis as well as a new coastal water level reanalysis from NOAA, both of which have much higher spatial resolutions and utilize different data assimilation methods compared to our experiment set (i.e., SEAS5 and ACCESS-S). We will conclude by discussing potential opportunities for improved ocean data assimilation in many shallow-self regions, such as for much of the U.S. East Coast, which have typically been the most challenging to initialize and forecast well.<\/p>\n

Co-authors:
\n<\/strong>Xiaoyu Long (Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA),
\nMagdalena Balmaseda (European Centre for Medium-Range Weather Forecasts, Reading, UK),
\nClaire Spillman (Bureau of Meteorology, Melbourne, VIC, AUS)>,
\nGrant Smith (Bureau of Meteorology, Melbourne, VIC, AUS),
\nHao Zuo (European Centre for Medium-Range Weather Forecasts, Reading, UK),
\nYonghong Yin (Bureau of Meteorology, Melbourne, VIC, AUS),
\nOscar Alves (Bureau of Meteorology, Melbourne, VIC, AUS),
\nArun Kumar (Climate Prediction Center, NCEP\/NWS\/NOAA, College Park, MD, USA),
\nXue Feng (Cooperative Institute for Marine and Atmospheric Research, School of Ocean and Earth Science and Technology, University of Hawai\u2019i at M\u0101noa, Honolulu, HI, USA),
\nLinta Rose (Cooperative Institute for Marine and Atmospheric Research, School of Ocean and Earth Science and Technology, University of Hawai\u2019i at M\u0101noa, Honolulu, HI, USA),
\nGregory Dusek (Center for Operational Oceanographic Products and Services, NOS\/NOAA, Silver Spring, MD, USA)[\/vc_column_text][vc_separator][\/vc_column][\/vc_row][vc_row][vc_column width=”1\/6″][vc_single_image image=”344″ img_size=”full” onclick=”custom_link” link=”http:\/\/s2sprediction.net\/”][\/vc_column][vc_column width=”1\/6″][vc_single_image image=”345″ img_size=”full” onclick=”custom_link” link=”https:\/\/public.wmo.int\/en”][\/vc_column][vc_column width=”1\/6″][vc_single_image image=”346″ img_size=”full” onclick=”custom_link” link=”https:\/\/community.wmo.int\/activity-areas\/wwrp”][\/vc_column][vc_column width=”1\/6″][vc_single_image image=”347″ img_size=”full” onclick=”custom_link” link=”https:\/\/www.wcrp-climate.org\/”][\/vc_column][vc_column width=”1\/6″][vc_single_image image=”348″ img_size=”full”][\/vc_column][vc_column width=”1\/6″][vc_single_image image=”349″ img_size=”full” onclick=”custom_link” link=”https:\/\/www.reading.ac.uk\/”][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"

[vc_row][vc_column][vc_column_text]Abstract ID: 090 Assessing opportunities for improved coastal data assimilation in ocean model analyses and forecasting systems Lead Author: Matthew Widlansky Cooperative Institute for Marine and Atmospheric Research, School of…Read More ><\/a><\/p>\n","protected":false},"author":145,"featured_media":0,"parent":528,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"__cvm_playback_settings":[],"__cvm_video_id":"","footnotes":""},"coauthors":[13],"class_list":["post-851","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nAbstract 090 - WWRP\/WCRP S2S Summit 2023<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract090\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Abstract 090 - 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