{"id":713,"date":"2023-07-02T18:05:59","date_gmt":"2023-07-02T17:05:59","guid":{"rendered":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/?page_id=713"},"modified":"2023-07-02T18:05:59","modified_gmt":"2023-07-02T17:05:59","slug":"abstract019","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract019\/","title":{"rendered":"Abstract 019"},"content":{"rendered":"<p>[vc_row][vc_column][vc_column_text]<strong>Abstract ID:<\/strong> 019<\/p>\n<h2 style=\"text-align: center\">Development of a Multi-physics Multi-ensemble system for efficient subseasonal prediction<\/h2>\n<p style=\"text-align: center\"><span data-contrast=\"auto\"><strong>Lead Author:<\/strong> Susmitha Joseph<br \/>\nIndian Institute of Tropical Meteorology, Pune, India<br \/>\n<\/span><\/p>\n<p><strong>Keywords:<\/strong> Subseasonal prediction<\/p>\n<p><strong>Abstract:<\/strong> Subseasonal predictions with a time scale of 2-4 weeks, which fills the gap between the weather and seasonal forecasts, are limited by the uncertainties arising from the initial conditions as well as the model physics. Therefore, in order to develop an efficient subseasonal prediction system, both these uncertainties need to be addressed. With this background, a multi-physics multi-ensemble approach has been adopted to develop a competent second-generation subseasonal prediction system at the Indian Institute of Tropical Meteorology (IITM), Pune, India. The first-generation prediction system developed at IITM is run operationally at the India Meteorological Department and has useful skills for up to two weeks.<br \/>\nA combination of physics perturbations and initial condition perturbations with a total of 18 ensemble members is present in the system. This system has been experimentally run since May 2022 to evaluate its real-time performance for the monsoon season 2022. The hindcast runs during 2003-2018 are also made on-the-fly. The initial results indicate a considerable improvement in the forecast skill compared to its predecessor and has reasonable deterministic (probabilistic) prediction skill for up to three (four) weeks.<\/p>\n<p><strong>Co-authors:<br \/>\n<\/strong>A K Sahai (Indian Institute of Tropical Meteorology, India)<br \/>\nR Mandal (Indian Institute of Tropical Meteorology, India)<br \/>\nA Dey (Indian Institute of Tropical Meteorology, India)<br \/>\nR Phani (Indian Institute of Tropical Meteorology, India)<br \/>\nM Kaur (Goethe University, Germany)<br \/>\nM Kalshetti (Indian Institute of Tropical Meteorology, India)<br \/>\nN Karmakar (Indian Institute of Tropical Meteorology, India)[\/vc_column_text][vc_separator][\/vc_column][\/vc_row][vc_row][vc_column width=&#8221;1\/6&#8243;][vc_single_image image=&#8221;344&#8243; img_size=&#8221;full&#8221; onclick=&#8221;custom_link&#8221; link=&#8221;http:\/\/s2sprediction.net\/&#8221;][\/vc_column][vc_column width=&#8221;1\/6&#8243;][vc_single_image image=&#8221;345&#8243; img_size=&#8221;full&#8221; onclick=&#8221;custom_link&#8221; link=&#8221;https:\/\/public.wmo.int\/en&#8221;][\/vc_column][vc_column width=&#8221;1\/6&#8243;][vc_single_image image=&#8221;346&#8243; img_size=&#8221;full&#8221; onclick=&#8221;custom_link&#8221; link=&#8221;https:\/\/community.wmo.int\/activity-areas\/wwrp&#8221;][\/vc_column][vc_column width=&#8221;1\/6&#8243;][vc_single_image image=&#8221;347&#8243; img_size=&#8221;full&#8221; onclick=&#8221;custom_link&#8221; link=&#8221;https:\/\/www.wcrp-climate.org\/&#8221;][\/vc_column][vc_column width=&#8221;1\/6&#8243;][vc_single_image image=&#8221;348&#8243; img_size=&#8221;full&#8221;][\/vc_column][vc_column width=&#8221;1\/6&#8243;][vc_single_image image=&#8221;349&#8243; img_size=&#8221;full&#8221; onclick=&#8221;custom_link&#8221; link=&#8221;https:\/\/www.reading.ac.uk\/&#8221;][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column][vc_column_text]Abstract ID: 019 Development of a Multi-physics Multi-ensemble system for efficient subseasonal prediction Lead Author: Susmitha Joseph Indian Institute of Tropical Meteorology, Pune, India Keywords: Subseasonal prediction Abstract: Subseasonal predictions&#8230;<a class=\"read-more\" href=\"&#104;&#116;&#116;&#112;&#115;&#58;&#47;&#47;&#114;&#101;&#115;&#101;&#97;&#114;&#99;&#104;&#46;&#114;&#101;&#97;&#100;&#105;&#110;&#103;&#46;&#97;&#99;&#46;&#117;&#107;&#47;&#115;&#50;&#115;&#45;&#115;&#117;&#109;&#109;&#105;&#116;&#50;&#48;&#50;&#51;&#47;&#112;&#114;&#111;&#103;&#114;&#97;&#109;&#109;&#101;&#47;&#97;&#98;&#115;&#116;&#114;&#97;&#99;&#116;&#48;&#49;&#57;&#47;\">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-713","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.8.1 - 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