Advances in the application and utility of subseasonal-to-seasonal predictions

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  • 1 a Department of Civil and Environmental Engineering, University of Strathclyde, Glasgow, U.K.
  • | 2 b Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
  • | 3 c Center for Earth System Modeling, Analysis, and Data, Department of Meteorology and Atmospheric Science, Pennsylvania State University, State College, PA
  • | 4 d Department of Meteorology and Climate Science, Federal University of Tech Akure, Akure, Nigeria
  • | 5 e California Department of Water Resources, Sacramento, CO
  • | 6 f Kenya Meteorological Department, Nairobi, Kenya
  • | 7 g Oceans & Atmosphere, CSIRO, Hobart, Australia
  • | 8 h Department of Meteorology, University of Reading, Reading, U.K.
  • | 9 i Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, U.K.
  • | 10 j Institute of Meteorology and Climate Research, Department of Troposphere Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
  • | 11 k International Research Institute for Climate and Society, The Earth Institute, Columbia University, New York, NY
  • | 12 l Barcelona Supercomputing Center (BSC), Barcelona, Spain
  • | 13 m Center for Weather Forecast and Climate Studies, National Institute for Space Research, Cachoeira Paulista, Brazil
  • | 14 n Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California San Diego, San Diego, CA
  • | 15 o Forecast Department, European Centre for Medium-range Weather Forecasts, Reading, U.K.
  • | 16 p Escuela de Nutrición de la Facultad de Ciencias Químicas y Farmacia, Universidad de San Carlos, Guatemala City, Guatemala
  • | 17 q Formerly of Met Office, Exeter, U.K.
  • | 18 r Applied Research, British Telecommunications plc, London, U.K.
  • | 19 s Numerical Weather Prediction, Nigerian Meteorological Agency, Abuja, Nigeria
  • | 20 t National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, U.K.
  • | 21 u School of Geographical Sciences, University of Bristol, Bristol, U.K.
  • | 22 v Ceará State Meteorology and Water Resources Foundation, Fortaleza, Brazil
  • | 23 w Hydro Tasmania, Hobart, Australia
  • | 24 x Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, Canada
  • | 25 y IGAD Climate Prediction and Applications Centre, Nairobi, Kenya
  • | 26 z Federal University of Agriculture Abeokuta, Abeokuta, Nigeria
  • | 27 aa Hydrology R&D, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
  • | 28 bb Department of Anthropology and Geography, Colorado State University, Fort Collins, CO
  • | 29 cc Department of Civil and Environmental Engineering, University of Brasilia, Brasilia, Brazil
  • | 30 dd School of Geography, Planning and Spatial Sciences, University of Tasmania, Hobart, Australia
  • | 31 ee School of the Built Environment, University of Reading, Reading, U.K.
  • | 32 ff University of Sussex, Brighton, U.K.
  • | 33 gg Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA
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Abstract

The subseasonal-to-seasonal (S2S) predictive timescale, encompassing lead times ranging from 2 weeks to a season, is at the frontier of forecasting science. Forecasts on this timescale provide opportunities for enhanced application-focused capabilities to complement existing weather and climate services and products. There is, however, a ‘knowledge-value’ gap, where a lack of evidence and awareness of the potential socio-economic benefits of S2S forecasts limits their wider uptake. To address this gap, here we present the first global community effort at summarizing relevant applications of S2S forecasts to guide further decision-making and support the continued development of S2S forecasts and related services. Focusing on 12 sectoral case studies spanning public health, agriculture, water resource management, renewable energy and utilities, and emergency management and response, we draw on recent advancements to explore their application and utility. These case studies mark a significant step forward in moving from potential to actual S2S forecasting applications. We show that by placing user needs at the forefront of S2S forecast development – demonstrating both skill and utility across sectors – this dialogue can be used to help promote and accelerate the awareness, value and co-generation of S2S forecasts. We also highlight that while S2S forecasts are increasingly gaining interest among users, incorporating probabilistic S2S forecasts into existing decision-making operations is not trivial. Nevertheless, S2S forecasting represents a significant opportunity to generate useful, usable and actionable forecast applications for and with users that will increasingly unlock the potential of this forecasting timescale.

Corresponding author: Dr Christopher J. White, chris.white@strath.ac.uk, Department of Civil and Environmental Engineering, University of Strathclyde, James Weir Building, 75 Montrose Street, Glasgow, G1 1XJ, U.K.

Abstract

The subseasonal-to-seasonal (S2S) predictive timescale, encompassing lead times ranging from 2 weeks to a season, is at the frontier of forecasting science. Forecasts on this timescale provide opportunities for enhanced application-focused capabilities to complement existing weather and climate services and products. There is, however, a ‘knowledge-value’ gap, where a lack of evidence and awareness of the potential socio-economic benefits of S2S forecasts limits their wider uptake. To address this gap, here we present the first global community effort at summarizing relevant applications of S2S forecasts to guide further decision-making and support the continued development of S2S forecasts and related services. Focusing on 12 sectoral case studies spanning public health, agriculture, water resource management, renewable energy and utilities, and emergency management and response, we draw on recent advancements to explore their application and utility. These case studies mark a significant step forward in moving from potential to actual S2S forecasting applications. We show that by placing user needs at the forefront of S2S forecast development – demonstrating both skill and utility across sectors – this dialogue can be used to help promote and accelerate the awareness, value and co-generation of S2S forecasts. We also highlight that while S2S forecasts are increasingly gaining interest among users, incorporating probabilistic S2S forecasts into existing decision-making operations is not trivial. Nevertheless, S2S forecasting represents a significant opportunity to generate useful, usable and actionable forecast applications for and with users that will increasingly unlock the potential of this forecasting timescale.

Corresponding author: Dr Christopher J. White, chris.white@strath.ac.uk, Department of Civil and Environmental Engineering, University of Strathclyde, James Weir Building, 75 Montrose Street, Glasgow, G1 1XJ, U.K.
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