{"id":1120,"date":"2023-07-03T01:49:30","date_gmt":"2023-07-03T00:49:30","guid":{"rendered":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/?page_id=1120"},"modified":"2023-07-03T01:49:30","modified_gmt":"2023-07-03T00:49:30","slug":"abstract208","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract208\/","title":{"rendered":"Abstract 208"},"content":{"rendered":"<p>[vc_row][vc_column][vc_column_text]<strong>Abstract ID:<\/strong> 208<\/p>\n<h2 style=\"text-align: center\">Application of sub-seasonal forecasts for farmer decision support in eastern and southern Africa<\/h2>\n<p style=\"text-align: center\"><span data-contrast=\"auto\"><strong>Lead Author:<\/strong> Emily Black<br \/>\nUniversity of Reading and the National Centre for Atmospheric Science, United Kingdom<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><strong>Keywords:<\/strong> Application of sub-seasonal forecasts, Agricultural decision support, Africa<\/p>\n<p><strong>Abstract:<\/strong> Skillful sub-seasonal forecasts have the potential to improve farmer decision making in sub-Saharan Africa. For this potential to be realised, meteorological forecasts must be presented as actionable advice, and integrated into holistic systems for farmer support. One way of accomplishing this is to integrate multiple streams of meteorological data into a decision support tool (DST) that targets a specific agronomical management issue. Here, we present a planting date DST, that has has been operational since 2019 in southern and eastern Africa, and which now serves &gt;1 million farmers. The DST combines meteorological observations and forecasts into a seamless sub-seasonal to seasonal framework for optimising planting date. Unlike most existing operational systems, which are based solely on rainfall, the DST presented here uses ensemble forecasts of soil moisture to estimate the optimal planting date at a local scale. Evaluations using &gt;30,000 observations of planting date and yield in Kenya, Rwanda, Uganda, Zambia and Malawi demonstrate that that planting at the optimal time would increase yield by 7-10% overall, and up to 20% for late planting farmers. The DST has been piloted by One Acre Fund for the 2019-2020, 2020-2021 and 2021-2022 seasons and there is strong demand for the service to be extended further. We conclude from the evaluations and pilots that the planting date DST has the potential to strengthen farmer decision making and hence their resilience to climate variability and change.<\/p>\n<p><strong>Co-authors:<br \/>\n<\/strong>Dagmawi Teklu Asfaw (School of Geographical Sciences, University of Bristol, UK)<br \/>\nAlex Sananka (One Acre Fund, Kigali, Rwanda)<br \/>\nStephen Aston (One Acre Fund, Kigali, Rwanda)<br \/>\nVictoria Boult (Department of Meteorology, University of Reading, Reading, UK; National Centre for Atmospheric Science)<br \/>\nRoss Maidment (Department of Meteorology, University of Reading, Reading, UK; National Centre for Atmospheric Science)[\/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: 208 Application of sub-seasonal forecasts for farmer decision support in eastern and southern Africa Lead Author: Emily Black University of Reading and the National Centre for Atmospheric Science,&#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;&#50;&#48;&#56;&#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-1120","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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