Applications of AI to ensemble forecasts of compound extreme weather events in support of operational adaptation of electric utilities

We propose a high-impact innovation for weather forecasting that integrates global ensemble weather forecasts with an AI-driven post-processing model of extreme weather indices. This innovation will provide the basis for skillful probabilistic forecasts of compound extreme weather events at extended lead times. Extreme weather/climate events of relevance to electric utilities focused on in Phase I are heat and cold extremes, wind droughts, extreme wind gusts, hail and lightning. The Phase I project focuses on specific needs for increased resilience of electric utilities in the face of compound extreme weather/climate events, including risks from the increasing penetration of renewable energy. CFAN's clients in the energy and insurance sectors have communicated the need for probabilistic forecasts of compound severe weather events with greater granularity and longer lead times than is currently produced by NOAA and other market providers. Advanced online decision support tools based on Visual Analytics will be developed in Phase II. Training these tools with data-driven and human insight will empower algorithms and experts continue to learn from and validate each other – this feedback will support operational adaptation to extreme weather events in a changing climate.