Probabilistic Subseasonal Weather Forecasts for the Energy Sector

June 20, 2020

Probabilistic Subseasonal Weather Forecasts for the Energy Sector

With Small Business Innovation Research (SBIR) funding, the Climate Forecast Applications Network (CFAN) has developed a new probabilistic multi-model subseasonal forecasting system for U.S. temperatures and 100 mph winds. Innovations include extreme event probabilities, ensemble clustering, 2-step calibration process, real-time verification, and a dynamic user interface.

Key Takeaways:

1. There is a great need for reliable subseasonal forecasts in the energy and financial sectors, particularly for extreme events.

2. Communication of forecast uncertainty and real-time verification of forecasts helps overcome skepticism of end users about forecast accuracy

3. A "forecast window of opportunityā€¯ approach is useful to identify situations with high versus low predictability.

About the Speaker: Judith Curry is President and co-founder of CFAN. Following an influential career in academic research and administration, Curry founded CFAN to translate cutting-edge weather and climate research into forecast products that support the mitigation of weather and climate risk for public and private sector decision makers.