Seamless climate information for climate extremes through merging of forecasts across monthly to multi-year timescales: User application

Seamless climate information for climate extremes through merging of forecasts across monthly to multi-year timescales: User application | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Seamless climate information for climate extremes through merging of forecasts across monthly to multi-year timescales: User application Muhammad Adnan Abid, Beena Balan Sarojini, Antje Weisheimer This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7725005/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract There is a clear need of seamless climate information, which can provide forecast about the tailored climate extremes for agriculture sector on monthly multi-year lead timescales. Seamless forecast framework has been proposed to provide climate information to the climate user. In recent years, vineyard farmers in Raimat, Catalonia, have reported frost risk during spring months (March and April). Observed Frequency of Frost Days (FFD) over Catalonia shows high interannual variability for the period 1983–2022. The European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system (SEAS5), shows a varying level of FFD forecast skill during March-April season for monthly (month-1) to multi-year (month-22) lead timescales. A new temporal merging technique is developed to build a stable and seamless climate information of the tailored climate extremes on multi-year timescales. Merged forecast tends to enhance 5 to 7% of the forecast skill compared to individual start dates, added through large ensemble members which bring information from the earlier start dates, at no additional cost to the seamless system. A Ready-Steady-Action/Go framework is developed, for climate users about the potential frost risk on a monthly to multi-year lead timescales. Moreover, we found frost risk over Catalonia is predictable about 10 months prior to the target (March-April) season. FFD forecast skill over Catalonia is mainly contributed by long-term warming trends as noted for all start dates, while for the May start date (10-month lead) 60% of the forecast skill is attributed to climate variability. Climate Information Seamless forecast Frost risk ASPECT Europe Vineyard Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Seamless forecast framework has been proposed to provide climate information to the climate user. In recent years, vineyard farmers in Raimat, Catalonia, have reported frost risk during spring months (March and April). Observed Frequency of Frost Days (FFD) over Catalonia shows high interannual variability for the period 1983\u0026ndash;2022. The European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system (SEAS5), shows a varying level of FFD forecast skill during March-April season for monthly (month-1) to multi-year (month-22) lead timescales. A new temporal merging technique is developed to build a stable and seamless climate information of the tailored climate extremes on multi-year timescales. Merged forecast tends to enhance 5 to 7% of the forecast skill compared to individual start dates, added through large ensemble members which bring information from the earlier start dates, at no additional cost to the seamless system. A Ready-Steady-Action/Go framework is developed, for climate users about the potential frost risk on a monthly to multi-year lead timescales. Moreover, we found frost risk over Catalonia is predictable about 10 months prior to the target (March-April) season. 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