{"id":1211,"date":"2023-07-03T02:37:49","date_gmt":"2023-07-03T01:37:49","guid":{"rendered":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/?page_id=1211"},"modified":"2023-07-03T02:37:49","modified_gmt":"2023-07-03T01:37:49","slug":"abstract246","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract246\/","title":{"rendered":"Abstract 246"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text]Abstract ID:<\/strong> 246<\/p>\n

Impact of Stochastic Parameterization on S2S Forecasts with CESM<\/h2>\n

Lead Author:<\/strong> Judith Berner
\nNCAR, United States of America
\n<\/span><\/p>\n

Keywords:<\/strong> Stochastic parameterization, Forecast Skill, Ensemble spread, CESM2<\/p>\n

Abstract: <\/strong>There has been increasing interest on generating skillful forecasts on the sub-seasonal to seasonal timescale which fills the gap between weather and seasonal climate forecasts.
\nOn this timescale, ensemble systems tend to be unreliable and overconfident, i.e. they underestimate the uncertainty of a particular forecast. In addition, forecasts are limited by large systematic model errors.<\/p>\n

Stochastic parameterization schemes are used routinely to remedy the problem of unreliability, but also have the potential to reduce systematic model errors.<\/p>\n

Here, we study the impact of adding a stochastic parameterization scheme in initialized coupled simulations with the climate model CESM2. We will give details of the impact on precipitation, 2m-temperature and geopotential height in 500hPa skill for different geographical regions.<\/p>\n

Adding a stochastic scheme results in more reliable forecasts, but generally leads to a decrease in deterministic skill. In particular, tercile forecasts for precipitation and temperature for weeks 3-4 and weeks 5-6 are significantly improved.<\/p>\n

Co-authors:
\n<\/strong>Abigail Jaye (National Center for Atmospheric Research, Boulder, CO)[\/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: 246 Impact of Stochastic Parameterization on S2S Forecasts with CESM Lead Author: Judith Berner NCAR, United States of America Keywords: Stochastic parameterization, Forecast Skill, Ensemble spread, CESM2 Abstract:…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-1211","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nAbstract 246 - 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\/abstract246\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Abstract 246 - 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