{"id":733,"date":"2023-07-02T18:17:55","date_gmt":"2023-07-02T17:17:55","guid":{"rendered":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/?page_id=733"},"modified":"2023-07-02T18:17:55","modified_gmt":"2023-07-02T17:17:55","slug":"abstract027","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract027\/","title":{"rendered":"Abstract 027"},"content":{"rendered":"<p>[vc_row][vc_column][vc_column_text]<strong>Abstract ID:<\/strong> 027<\/p>\n<h2 style=\"text-align: center\">The predictability and representation of Indian monsoon low-pressure systems in Subseasonal-to-Seasonal prediction models<\/h2>\n<p style=\"text-align: center\"><span data-contrast=\"auto\"><strong>Lead Author:<\/strong> Akshay Deoras<br \/>\nNCAS &amp; Department of Meteorology, University of Reading, United Kingdom<br \/>\n<\/span><\/p>\n<p><strong>Keywords:<\/strong> S2S, Indian monsoon low-pressure systems<\/p>\n<p><strong>Abstract:\u00a0<\/strong>Indian monsoon low-pressure systems (LPSs) are synoptic-scale cyclonic vortices that typically develop over the head of the Bay of Bengal and produce substantial summer monsoon precipitation over India. Despite their ability to trigger catastrophic floods in the Indian subcontinent, there has been insufficient exploration of their representation in models, their predictability, and the role of large-scale controls on their frequency. In this study, we use a feature-tracking algorithm to identify LPSs in all ensemble members of eleven models of the Subseasonal-to-Seasonal (S2S) prediction project during a common reforecast period of June\u2013September 1999\u20132010. Forecast verification statistics for LPSs are produced, and composite storm-centred structures of many dynamic and thermodynamic fields are generated. The results are then verified against ERA-Interim and MERRA-2 reanalyses.<\/p>\n<p>We find that S2S models simulate tracks and structure of LPSs reasonably well; however, they underestimate their frequency, and BoM, CMA and HMCR models have large biases in their simulation. Most S2S models correctly simulate the modulation of LPS genesis by the Madden-Julian Oscillation, and the LPS frequency during La Ni\u00f1a and positive Indian Ocean Dipole (IOD) years is larger than during El Ni\u00f1o and negative IOD years. We also find that large-scale conditions, such as the position of the tropical easterly jet and mid-tropospheric relative humidity, play a role in modulating LPS lifespan.<\/p>\n<p>These results demonstrate the potential for S2S models at forecasting LPSs, envisaging improved disaster preparedness and water resources planning in the Indian subcontinent.<\/p>\n<p><strong>Co-authors:<br \/>\n<\/strong>Dr Kieran M. R. Hunt (National Centre for Atmospheric Science &amp; Department of Meteorology, University of Reading)<br \/>\nDr Andrew G. Turner (National Centre for Atmospheric Science &amp; Department of Meteorology, University of Reading)[\/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; 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