{"id":786,"date":"2023-07-02T19:10:31","date_gmt":"2023-07-02T18:10:31","guid":{"rendered":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/?page_id=786"},"modified":"2023-07-02T19:10:31","modified_gmt":"2023-07-02T18:10:31","slug":"abstract058","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract058\/","title":{"rendered":"Abstract 058"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text]Abstract ID:<\/strong> 058<\/p>\n

Subseasonal forecasting of temperature and precipitation over India using a machine learning approach<\/h2>\n

Lead Author:<\/strong> Prajwal P. Jadhav
\nIndian Institute of Science Education and Research Pune, India
\n<\/span><\/p>\n

Keywords:<\/strong> Sub-seasonal Forecasting, Machine Learning<\/p>\n

Abstract:<\/strong> Subseasonal forecasting is forecasting of the weather parameters, mainly temperature and precipitation, two weeks to two months in advance. Sub-seasonal variability accounts for a substantial portion of the summer rainfall over India. Prediction of sub-seasonal climate is of immense societal importance in agriculture planning, water management, emergency planning, etc. Using various weather parameters and ECMWF dynamical model forecasts as predictors, this study tries to investigate the weekly forecast of temperature and precipitation at 2-week, 3-week, and 4-week forecast horizon over India using a computationally inexpensive machine learning model-MultiLLR, which prunes out irrelevant predictors and integrates remaining predictors linearly for each target date. The model\u2019s predictions calculated over the years 2019-2022 are as skilful as IMD\u2019s Extended Range Forecasting System (ERFS). The skill of the model is better in the coastal region than in the inland part of India.<\/p>\n

Co-authors:
\n<\/strong>Dr Sreejith O. P., Indian Meteorological Department Pune
\nDr Sabeerali C. T., Indian Meteorological Department Pune[\/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: 058 Subseasonal forecasting of temperature and precipitation over India using a machine learning approach Lead Author: Prajwal P. Jadhav Indian Institute of Science Education and Research Pune, India…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-786","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nAbstract 058 - 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\/abstract058\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Abstract 058 - WWRP\/WCRP S2S Summit 2023\" \/>\n<meta property=\"og:description\" content=\"[vc_row][vc_column][vc_column_text]Abstract ID: 058 Subseasonal forecasting of temperature and precipitation over India using a machine learning approach Lead Author: Prajwal P. 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