articleHydrology and earth system sciencesMay 15, 2023GOLD OA

Hybrid forecasting: blending climate predictions with AI models

LSLouise SlaterLALouise ArnalMBMarie‐Amélie BoucherAYAnnie Y.-Y. ChangSMSimon Moulds

University of Oxford · University of Saskatchewan · +11 more institutions

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Abstract

Abstract. Hybrid hydroclimatic forecasting systems employ data-driven (statistical or machine learning) methods to harness and integrate a broad variety of predictions from dynamical, physics-based models – such as numerical weather prediction, climate, land, hydrology, and Earth system models – into a final prediction product. They are recognized as a promising way of enhancing the prediction skill of meteorological and hydroclimatic variables and events, including rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. Hybrid forecasting methods are now receiving growing attention due to advances in weather and climate prediction systems at subseasonal to decadal…

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209
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Topics & keywords

Topics
Keywords
  • Predictability
  • Merge (version control)
  • Computer science
  • Data assimilation
  • Numerical weather prediction
  • Forcing (mathematics)
  • Forecast skill
  • Ensemble forecasting
UN Sustainable Development Goals
  • Climate action
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