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description Publicationkeyboard_double_arrow_right Article , Journal 2020 Argentina, Argentina, United Kingdom, Spain, France, Germany, United Kingdom, France, United Kingdom, Spain, United Kingdom, South AfricaPublisher:American Meteorological Society Funded by:EC | INPhINITEC| INPhINITMerryfield, William; Baehr, Johanna; Batté, Lauriane; Becker, Emily; Butler, Amy; Coelho, Caio; Danabasoglu, Gokhan; Dirmeyer, Paul; Doblas-Reyes, Francisco; Domeisen, Daniela; Ferranti, Laura; Ilynia, Tatiana; Kumar, Arun; Müller, Wolfgang; Rixen, Michel; Robertson, Andrew; Smith, Doug; Takaya, Yuhei; Tuma, Matthias; Vitart, Frederic; White, Christopher; Alvarez, Mariano; Ardilouze, Constantin; Attard, Hannah; Baggett, Cory; Balmaseda, Magdalena; Beraki, Asmerom; Bhattacharjee, Partha; Bilbao, Roberto; de Andrade, Felipe; Deflorio, Michael; Díaz, Leandro; Ehsan, Muhammad Azhar; Fragkoulidis, Georgios; Gonzalez, Alex; Grainger, Sam; Green, Benjamin; Hell, Momme; Infanti, Johnna; Isensee, Katharina; Kataoka, Takahito; Kirtman, Ben; Klingaman, Nicholas; Lee, June-Yi; Mayer, Kirsten; Mckay, Roseanna; Mecking, Jennifer; Miller, Douglas; Neddermann, Nele; Justin Ng, Ching Ho; Ossó, Albert; Pankatz, Klaus; Peatman, Simon; Pegion, Kathy; Perlwitz, Judith; Recalde-Coronel, G. Cristina; Reintges, Annika; Renkl, Christoph; Solaraju-Murali, Balakrishnan; Spring, Aaron; Stan, Cristiana; Sun, Y. Qiang; Tozer, Carly; Vigaud, Nicolas; Woolnough, Steven; Yeager, Stephen;handle: 11336/150980 , 2117/185086 , 2263/80103
Abstract Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.
CORE arrow_drop_down Recolector de Ciencia Abierta, RECOLECTAArticle . 2020Data sources: Recolector de Ciencia Abierta, RECOLECTAUPCommons. Portal del coneixement obert de la UPCArticle . 2020Data sources: UPCommons. Portal del coneixement obert de la UPCBulletin of the American Meteorological SocietyArticle . 2020 . Peer-reviewedData sources: CrossrefBulletin of the American Meteorological SocietyArticle . 2020 . Peer-reviewedData sources: European Union Open Data PortalNatural Environment Research Council: NERC Open Research ArchiveArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 126 citations 126 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 62visibility views 62 download downloads 45 Powered bymore_vert CORE arrow_drop_down Recolector de Ciencia Abierta, RECOLECTAArticle . 2020Data sources: Recolector de Ciencia Abierta, RECOLECTAUPCommons. Portal del coneixement obert de la UPCArticle . 2020Data sources: UPCommons. Portal del coneixement obert de la UPCBulletin of the American Meteorological SocietyArticle . 2020 . Peer-reviewedData sources: CrossrefBulletin of the American Meteorological SocietyArticle . 2020 . Peer-reviewedData sources: European Union Open Data PortalNatural Environment Research Council: NERC Open Research ArchiveArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2021 United KingdomPublisher:Elsevier BV Funded by:UKRI | Satellite data for Weathe..., UKRI | Towards Forecast-based Pr..., UKRI | GCRF African Science for ...UKRI| Satellite data for Weather Index Insurance-AgricuLtural EaRly warning system (SatWIN-ALERT) ,UKRI| Towards Forecast-based Preparedness Action (ForPAc): Probabilistic forecast information for defensible preparedness decision-making and action ,UKRI| GCRF African Science for Weather Information and Forecasting Techniques (African SWIFT)Linda Hirons; Elisabeth Morgan Thompson; Cheikh Dione; Victor S. Indasi; Mary Kilavi; Elias Nkiaka; Joshua Talib; Emma Visman; Elijah A. Adefisan; Felipe M. de Andrade; Jesse Ashong; Jasper Batureine Mwesigwa; Victoria L. Boult; Tidiane Diédhiou; Oumar Konte; Masilin Gudoshava; Chris Kiptum; Richmond Konadu Amoah; Benjamin Lamptey; Kamoru A. Lawal; Richard Muita; Richard Nzekwu; Patricia Nying'uro; Willis Ochieng; Eniola Olaniyan; Nana Kofi Opoku; Hussen Seid Endris; Zewdu T. Segele; P. Moudi Igri; Emmah Mwangi; S. J. Woolnough;Los pronósticos en escalas de tiempo subestacionales a estacionales (S2S) tienen un enorme potencial para ayudar a la preparación y las decisiones de planificación de la reducción del riesgo de desastres en una variedad de sectores. Sin embargo, la realización de este potencial depende de la provisión de información fiable que pueda aplicarse adecuadamente en el contexto de toma de decisiones de los usuarios. Este estudio describe el banco de pruebas de pronóstico SWIFT africano (Science for Weather Information and Forecasting Techniques) que reúne a investigadores, productores de pronósticos y usuarios de una variedad de instituciones africanas y del Reino Unido. El banco de pruebas de pronóstico está probando la provisión de productos de pronóstico S2S a medida y en tiempo real para los responsables de la toma de decisiones en África. Basándose en datos del taller de lanzamiento y ejemplos de estudios de casos iniciales, este estudio reflexiona críticamente sobre el proceso de coproducción. Específicamente, tener acceso directo a datos en tiempo real ha permitido iteraciones guiadas por el usuario a la escala espacial, el tiempo, la visualización y la comunicación de los productos pronosticados para hacerlos más procesables para los usuarios. Están surgiendo algunas lecciones clave para una coproducción efectiva. En primer lugar, es fundamental garantizar que haya recursos suficientes para apoyar la coproducción, especialmente en la coexploración temprana de las necesidades. En segundo lugar, todos los grupos en el proceso de coproducción requieren el desarrollo de capacidades para trabajar eficazmente en nuevos sistemas de conocimiento. En tercer lugar, la evaluación debe ser continua y combinar la verificación meteorológica con la retroalimentación de los responsables de la toma de decisiones. Garantizar la sostenibilidad de los servicios iniciados por el proyecto dentro del banco de pruebas depende de la integración de los intercambios de conocimientos entre las personas en el proceso de coproducción en la configuración de vías sostenibles para mejorar la previsión operativa de S2S dentro de las instituciones africanas. Les prévisions sur les échelles de temps sous-saisonnières à saisonnières (S2S) ont un énorme potentiel pour aider les décisions de planification de la préparation et de la réduction des risques de catastrophe dans divers secteurs. Cependant, la réalisation de ce potentiel dépend de la fourniture d'informations fiables qui peuvent être appliquées de manière appropriée dans le contexte de prise de décision des utilisateurs. Cette étude décrit le banc d'essai africain de prévision SWIFT (Science for Weather Information and Forecasting Techniques) qui rassemble des chercheurs, des producteurs de prévisions et des utilisateurs de diverses institutions africaines et britanniques. Le banc d'essai de prévision pilote la fourniture de produits de prévision S2S en temps réel et sur mesure aux décideurs en Afrique. S'appuyant sur les données de l'atelier de lancement et sur des exemples d'études de cas initiales, cette étude porte un regard critique sur le processus de coproduction. Plus précisément, avoir un accès direct aux données en temps réel a permis des itérations guidées par l'utilisateur sur l'échelle spatiale, la synchronisation, la visualisation et la communication des produits de prévision pour les rendre plus exploitables pour les utilisateurs. Certaines leçons clés pour une coproduction efficace émergent. Tout d'abord, il est essentiel de s'assurer qu'il y a suffisamment de ressources pour soutenir la coproduction, en particulier dans la co-exploration précoce des besoins. Deuxièmement, tous les groupes du processus de coproduction ont besoin d'un renforcement des capacités pour travailler efficacement dans de nouveaux systèmes de connaissances. Troisièmement, l'évaluation devrait être continue et combiner la vérification météorologique avec les commentaires des décideurs. Assurer la durabilité des services initiés par le projet au sein du banc d'essai repose sur l'intégration des échanges de connaissances entre les individus dans le processus de coproduction afin de façonner des voies durables pour améliorer les prévisions opérationnelles S2S au sein des institutions africaines. Forecasts on sub-seasonal to seasonal (S2S) timescales have huge potential to aid preparedness and disaster risk reduction planning decisions in a variety of sectors. However, realising this potential depends on the provision of reliable information that can be appropriately applied in the decision-making context of users. This study describes the African SWIFT (Science for Weather Information and Forecasting Techniques) forecasting testbed which brings together researchers, forecast producers and users from a range of African and UK institutions. The forecasting testbed is piloting the provision of real-time, bespoke S2S forecast products to decision-makers in Africa. Drawing on data from the kick-off workshop and initial case study examples, this study critically reflects on the co-production process. Specifically, having direct access to real-time data has allowed user-guided iterations to the spatial scale, timing, visualisation and communication of forecast products to make them more actionable for users. Some key lessons for effective co-production are emerging. First, it is critical to ensure there is sufficient resource to support co-production, especially in the early co-exploration of needs. Second, all the groups in the co-production process require capacity building to effectively work in new knowledge systems. Third, evaluation should be ongoing and combine meteorological verification with decision-makers feedback. Ensuring the sustainability of project-initiated services within the testbed hinges on integrating the knowledge-exchanges between individuals in the co-production process into shaping sustainable pathways for improved operational S2S forecasting within African institutions. تتمتع التنبؤات على الجداول الزمنية دون الموسمية إلى الموسمية (S2S) بإمكانات هائلة للمساعدة في التأهب وقرارات التخطيط للحد من مخاطر الكوارث في مجموعة متنوعة من القطاعات. ومع ذلك، فإن تحقيق هذه الإمكانات يعتمد على توفير معلومات موثوقة يمكن تطبيقها بشكل مناسب في سياق صنع القرار للمستخدمين. تصف هذه الدراسة اختبار التنبؤ الأفريقي SWIFT (علوم معلومات الطقس وتقنيات التنبؤ) الذي يجمع بين الباحثين ومنتجي التنبؤ والمستخدمين من مجموعة من المؤسسات الأفريقية والبريطانية. يختبر اختبار التنبؤ توفير منتجات توقعات S2S المخصصة في الوقت الفعلي لصانعي القرار في إفريقيا. بالاعتماد على البيانات من ورشة العمل الافتتاحية وأمثلة دراسة الحالة الأولية، تعكس هذه الدراسة بشكل نقدي عملية الإنتاج المشترك. على وجه التحديد، أتاح الوصول المباشر إلى البيانات في الوقت الفعلي التكرارات الموجهة من المستخدم إلى النطاق المكاني والتوقيت والتصور والتواصل لمنتجات التنبؤ لجعلها أكثر قابلية للتنفيذ للمستخدمين. بدأت بعض الدروس الرئيسية للإنتاج المشترك الفعال في الظهور. أولاً، من الأهمية بمكان ضمان وجود موارد كافية لدعم الإنتاج المشترك، خاصة في الاستكشاف المشترك المبكر للاحتياجات. ثانيًا، تتطلب جميع المجموعات في عملية الإنتاج المشترك بناء القدرات للعمل بفعالية في أنظمة المعرفة الجديدة. ثالثًا، يجب أن يكون التقييم مستمرًا وأن يجمع بين التحقق من الأرصاد الجوية وملاحظات صانعي القرار. يتوقف ضمان استدامة الخدمات التي يبدأها المشروع داخل منصة الاختبار على دمج تبادل المعرفة بين الأفراد في عملية الإنتاج المشترك في تشكيل مسارات مستدامة لتحسين التنبؤ التشغيلي S2S داخل المؤسسات الأفريقية.
CORE arrow_drop_down Natural Environment Research Council: NERC Open Research ArchiveArticle . 2021License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 21 citations 21 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
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description Publicationkeyboard_double_arrow_right Article , Journal 2020 Argentina, Argentina, United Kingdom, Spain, France, Germany, United Kingdom, France, United Kingdom, Spain, United Kingdom, South AfricaPublisher:American Meteorological Society Funded by:EC | INPhINITEC| INPhINITMerryfield, William; Baehr, Johanna; Batté, Lauriane; Becker, Emily; Butler, Amy; Coelho, Caio; Danabasoglu, Gokhan; Dirmeyer, Paul; Doblas-Reyes, Francisco; Domeisen, Daniela; Ferranti, Laura; Ilynia, Tatiana; Kumar, Arun; Müller, Wolfgang; Rixen, Michel; Robertson, Andrew; Smith, Doug; Takaya, Yuhei; Tuma, Matthias; Vitart, Frederic; White, Christopher; Alvarez, Mariano; Ardilouze, Constantin; Attard, Hannah; Baggett, Cory; Balmaseda, Magdalena; Beraki, Asmerom; Bhattacharjee, Partha; Bilbao, Roberto; de Andrade, Felipe; Deflorio, Michael; Díaz, Leandro; Ehsan, Muhammad Azhar; Fragkoulidis, Georgios; Gonzalez, Alex; Grainger, Sam; Green, Benjamin; Hell, Momme; Infanti, Johnna; Isensee, Katharina; Kataoka, Takahito; Kirtman, Ben; Klingaman, Nicholas; Lee, June-Yi; Mayer, Kirsten; Mckay, Roseanna; Mecking, Jennifer; Miller, Douglas; Neddermann, Nele; Justin Ng, Ching Ho; Ossó, Albert; Pankatz, Klaus; Peatman, Simon; Pegion, Kathy; Perlwitz, Judith; Recalde-Coronel, G. Cristina; Reintges, Annika; Renkl, Christoph; Solaraju-Murali, Balakrishnan; Spring, Aaron; Stan, Cristiana; Sun, Y. Qiang; Tozer, Carly; Vigaud, Nicolas; Woolnough, Steven; Yeager, Stephen;handle: 11336/150980 , 2117/185086 , 2263/80103
Abstract Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.
CORE arrow_drop_down Recolector de Ciencia Abierta, RECOLECTAArticle . 2020Data sources: Recolector de Ciencia Abierta, RECOLECTAUPCommons. Portal del coneixement obert de la UPCArticle . 2020Data sources: UPCommons. Portal del coneixement obert de la UPCBulletin of the American Meteorological SocietyArticle . 2020 . Peer-reviewedData sources: CrossrefBulletin of the American Meteorological SocietyArticle . 2020 . Peer-reviewedData sources: European Union Open Data PortalNatural Environment Research Council: NERC Open Research ArchiveArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 126 citations 126 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 62visibility views 62 download downloads 45 Powered bymore_vert CORE arrow_drop_down Recolector de Ciencia Abierta, RECOLECTAArticle . 2020Data sources: Recolector de Ciencia Abierta, RECOLECTAUPCommons. Portal del coneixement obert de la UPCArticle . 2020Data sources: UPCommons. Portal del coneixement obert de la UPCBulletin of the American Meteorological SocietyArticle . 2020 . Peer-reviewedData sources: CrossrefBulletin of the American Meteorological SocietyArticle . 2020 . Peer-reviewedData sources: European Union Open Data PortalNatural Environment Research Council: NERC Open Research ArchiveArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2021 United KingdomPublisher:Elsevier BV Funded by:UKRI | Satellite data for Weathe..., UKRI | Towards Forecast-based Pr..., UKRI | GCRF African Science for ...UKRI| Satellite data for Weather Index Insurance-AgricuLtural EaRly warning system (SatWIN-ALERT) ,UKRI| Towards Forecast-based Preparedness Action (ForPAc): Probabilistic forecast information for defensible preparedness decision-making and action ,UKRI| GCRF African Science for Weather Information and Forecasting Techniques (African SWIFT)Linda Hirons; Elisabeth Morgan Thompson; Cheikh Dione; Victor S. Indasi; Mary Kilavi; Elias Nkiaka; Joshua Talib; Emma Visman; Elijah A. Adefisan; Felipe M. de Andrade; Jesse Ashong; Jasper Batureine Mwesigwa; Victoria L. Boult; Tidiane Diédhiou; Oumar Konte; Masilin Gudoshava; Chris Kiptum; Richmond Konadu Amoah; Benjamin Lamptey; Kamoru A. Lawal; Richard Muita; Richard Nzekwu; Patricia Nying'uro; Willis Ochieng; Eniola Olaniyan; Nana Kofi Opoku; Hussen Seid Endris; Zewdu T. Segele; P. Moudi Igri; Emmah Mwangi; S. J. Woolnough;Los pronósticos en escalas de tiempo subestacionales a estacionales (S2S) tienen un enorme potencial para ayudar a la preparación y las decisiones de planificación de la reducción del riesgo de desastres en una variedad de sectores. Sin embargo, la realización de este potencial depende de la provisión de información fiable que pueda aplicarse adecuadamente en el contexto de toma de decisiones de los usuarios. Este estudio describe el banco de pruebas de pronóstico SWIFT africano (Science for Weather Information and Forecasting Techniques) que reúne a investigadores, productores de pronósticos y usuarios de una variedad de instituciones africanas y del Reino Unido. El banco de pruebas de pronóstico está probando la provisión de productos de pronóstico S2S a medida y en tiempo real para los responsables de la toma de decisiones en África. Basándose en datos del taller de lanzamiento y ejemplos de estudios de casos iniciales, este estudio reflexiona críticamente sobre el proceso de coproducción. Específicamente, tener acceso directo a datos en tiempo real ha permitido iteraciones guiadas por el usuario a la escala espacial, el tiempo, la visualización y la comunicación de los productos pronosticados para hacerlos más procesables para los usuarios. Están surgiendo algunas lecciones clave para una coproducción efectiva. En primer lugar, es fundamental garantizar que haya recursos suficientes para apoyar la coproducción, especialmente en la coexploración temprana de las necesidades. En segundo lugar, todos los grupos en el proceso de coproducción requieren el desarrollo de capacidades para trabajar eficazmente en nuevos sistemas de conocimiento. En tercer lugar, la evaluación debe ser continua y combinar la verificación meteorológica con la retroalimentación de los responsables de la toma de decisiones. Garantizar la sostenibilidad de los servicios iniciados por el proyecto dentro del banco de pruebas depende de la integración de los intercambios de conocimientos entre las personas en el proceso de coproducción en la configuración de vías sostenibles para mejorar la previsión operativa de S2S dentro de las instituciones africanas. Les prévisions sur les échelles de temps sous-saisonnières à saisonnières (S2S) ont un énorme potentiel pour aider les décisions de planification de la préparation et de la réduction des risques de catastrophe dans divers secteurs. Cependant, la réalisation de ce potentiel dépend de la fourniture d'informations fiables qui peuvent être appliquées de manière appropriée dans le contexte de prise de décision des utilisateurs. Cette étude décrit le banc d'essai africain de prévision SWIFT (Science for Weather Information and Forecasting Techniques) qui rassemble des chercheurs, des producteurs de prévisions et des utilisateurs de diverses institutions africaines et britanniques. Le banc d'essai de prévision pilote la fourniture de produits de prévision S2S en temps réel et sur mesure aux décideurs en Afrique. S'appuyant sur les données de l'atelier de lancement et sur des exemples d'études de cas initiales, cette étude porte un regard critique sur le processus de coproduction. Plus précisément, avoir un accès direct aux données en temps réel a permis des itérations guidées par l'utilisateur sur l'échelle spatiale, la synchronisation, la visualisation et la communication des produits de prévision pour les rendre plus exploitables pour les utilisateurs. Certaines leçons clés pour une coproduction efficace émergent. Tout d'abord, il est essentiel de s'assurer qu'il y a suffisamment de ressources pour soutenir la coproduction, en particulier dans la co-exploration précoce des besoins. Deuxièmement, tous les groupes du processus de coproduction ont besoin d'un renforcement des capacités pour travailler efficacement dans de nouveaux systèmes de connaissances. Troisièmement, l'évaluation devrait être continue et combiner la vérification météorologique avec les commentaires des décideurs. Assurer la durabilité des services initiés par le projet au sein du banc d'essai repose sur l'intégration des échanges de connaissances entre les individus dans le processus de coproduction afin de façonner des voies durables pour améliorer les prévisions opérationnelles S2S au sein des institutions africaines. Forecasts on sub-seasonal to seasonal (S2S) timescales have huge potential to aid preparedness and disaster risk reduction planning decisions in a variety of sectors. However, realising this potential depends on the provision of reliable information that can be appropriately applied in the decision-making context of users. This study describes the African SWIFT (Science for Weather Information and Forecasting Techniques) forecasting testbed which brings together researchers, forecast producers and users from a range of African and UK institutions. The forecasting testbed is piloting the provision of real-time, bespoke S2S forecast products to decision-makers in Africa. Drawing on data from the kick-off workshop and initial case study examples, this study critically reflects on the co-production process. Specifically, having direct access to real-time data has allowed user-guided iterations to the spatial scale, timing, visualisation and communication of forecast products to make them more actionable for users. Some key lessons for effective co-production are emerging. First, it is critical to ensure there is sufficient resource to support co-production, especially in the early co-exploration of needs. Second, all the groups in the co-production process require capacity building to effectively work in new knowledge systems. Third, evaluation should be ongoing and combine meteorological verification with decision-makers feedback. Ensuring the sustainability of project-initiated services within the testbed hinges on integrating the knowledge-exchanges between individuals in the co-production process into shaping sustainable pathways for improved operational S2S forecasting within African institutions. تتمتع التنبؤات على الجداول الزمنية دون الموسمية إلى الموسمية (S2S) بإمكانات هائلة للمساعدة في التأهب وقرارات التخطيط للحد من مخاطر الكوارث في مجموعة متنوعة من القطاعات. ومع ذلك، فإن تحقيق هذه الإمكانات يعتمد على توفير معلومات موثوقة يمكن تطبيقها بشكل مناسب في سياق صنع القرار للمستخدمين. تصف هذه الدراسة اختبار التنبؤ الأفريقي SWIFT (علوم معلومات الطقس وتقنيات التنبؤ) الذي يجمع بين الباحثين ومنتجي التنبؤ والمستخدمين من مجموعة من المؤسسات الأفريقية والبريطانية. يختبر اختبار التنبؤ توفير منتجات توقعات S2S المخصصة في الوقت الفعلي لصانعي القرار في إفريقيا. بالاعتماد على البيانات من ورشة العمل الافتتاحية وأمثلة دراسة الحالة الأولية، تعكس هذه الدراسة بشكل نقدي عملية الإنتاج المشترك. على وجه التحديد، أتاح الوصول المباشر إلى البيانات في الوقت الفعلي التكرارات الموجهة من المستخدم إلى النطاق المكاني والتوقيت والتصور والتواصل لمنتجات التنبؤ لجعلها أكثر قابلية للتنفيذ للمستخدمين. بدأت بعض الدروس الرئيسية للإنتاج المشترك الفعال في الظهور. أولاً، من الأهمية بمكان ضمان وجود موارد كافية لدعم الإنتاج المشترك، خاصة في الاستكشاف المشترك المبكر للاحتياجات. ثانيًا، تتطلب جميع المجموعات في عملية الإنتاج المشترك بناء القدرات للعمل بفعالية في أنظمة المعرفة الجديدة. ثالثًا، يجب أن يكون التقييم مستمرًا وأن يجمع بين التحقق من الأرصاد الجوية وملاحظات صانعي القرار. يتوقف ضمان استدامة الخدمات التي يبدأها المشروع داخل منصة الاختبار على دمج تبادل المعرفة بين الأفراد في عملية الإنتاج المشترك في تشكيل مسارات مستدامة لتحسين التنبؤ التشغيلي S2S داخل المؤسسات الأفريقية.
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