{"id":1095,"date":"2023-07-03T01:29:14","date_gmt":"2023-07-03T00:29:14","guid":{"rendered":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/?page_id=1095"},"modified":"2023-07-03T01:29:14","modified_gmt":"2023-07-03T00:29:14","slug":"abstract194","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract194\/","title":{"rendered":"Abstract 194"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text]Abstract ID:<\/strong> 194<\/p>\n

On the source of model biases for subseasonal tropical cyclone precipitation prediction<\/h2>\n

Lead Author:<\/strong> Jorge L. Garcia Franco
\nColumbia University , United States of America, Mexico
\n<\/span><\/p>\n

Keywords:<\/strong> tropical cyclones, mean-state biases, genesis indices, large-scale, mean and extreme precipitation<\/p>\n

Abstract:<\/strong> In this presentation, we investigate the causes of mean model biases relevant for predicting tropical cyclone precipitation (TCP) at subseasonal time scales. We will analyze reforecasts from the NASA Goddard Earth Observing System-Subseasonal to Seasonal version 2 (GEOS-S2S) prediction system and those from global models that participate in the WMO S2S project. We will examine the source of biases from large-scale environmental conditions and storm-scale processes. Specifically, we examine the relationship between the simulated large-scale environmental conditions, measured through indices such as the Genesis Potential index (GPI) and Tropical Cyclone Genesis Indices (TCGI) and the simulated TC activity. We will also compare the relationship between relative sea-surface temperatures, precipitable water vapor and the mean and maximum TCP derived from observations to those derived from reforecasts. Lastly, we diagnose the degree to which these mean-state biases can help explain TCP biases as the forecast lead time increases. Our findings will provide insight into the relative importance of biases in large-scale conditions and storm-scale convective processes for subseasonal TCP prediction skill.<\/p>\n

Co-authors:
\n<\/strong>Lee, Chia-Ying (Columbia University)
\nCamargo, Suzana (Columbia University)
\nTippett, Michael (Columbia University)
\nMolod, Andrea (Goddard Space Flight Center, NASA, Greenbelt, MD, USA)
\nLim, Young-Kwon (Goddard Space Flight Center, NASA, Greenbelt, MD, USA)
\nKim, Daehyun (University of Washington)[\/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: 194 On the source of model biases for subseasonal tropical cyclone precipitation prediction Lead Author: Jorge L. Garcia Franco Columbia University , United States of America, Mexico Keywords:…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-1095","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nAbstract 194 - 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\/abstract194\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Abstract 194 - WWRP\/WCRP S2S Summit 2023\" \/>\n<meta property=\"og:description\" content=\"[vc_row][vc_column][vc_column_text]Abstract ID: 194 On the source of model biases for subseasonal tropical cyclone precipitation prediction Lead Author: Jorge L. Garcia Franco Columbia University , United States of America, Mexico Keywords:...Read More >\" \/>\n<meta property=\"og:url\" content=\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract194\/\" \/>\n<meta property=\"og:site_name\" content=\"WWRP\/WCRP S2S Summit 2023\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Estimated reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n\t<meta name=\"twitter:label2\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data2\" content=\"Robert Lee\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract194\/\",\"url\":\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract194\/\",\"name\":\"Abstract 194 - WWRP\/WCRP S2S Summit 2023\",\"isPartOf\":{\"@id\":\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/#website\"},\"datePublished\":\"2023-07-03T00:29:14+00:00\",\"dateModified\":\"2023-07-03T00:29:14+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract194\/#breadcrumb\"},\"inLanguage\":\"en-GB\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract194\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract194\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Programme\",\"item\":\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Abstract 194\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/#website\",\"url\":\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/\",\"name\":\"WWRP\/WCRP S2S Summit 2023\",\"description\":\"Advancing Sub-seasonal to Seasonal Predictions and their Applications\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/research.reading.ac.uk\/s2s-summit2023\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-GB\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Abstract 194 - WWRP\/WCRP S2S Summit 2023","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract194\/","og_locale":"en_GB","og_type":"article","og_title":"Abstract 194 - WWRP\/WCRP S2S Summit 2023","og_description":"[vc_row][vc_column][vc_column_text]Abstract ID: 194 On the source of model biases for subseasonal tropical cyclone precipitation prediction Lead Author: Jorge L. 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