Quantifying the usefulness of European subseasonal forecasts using a real-world energy-sector framework

Increasingly, operational forecasting centres are producing sub-seasonal forecasts, targeted at lead times of 3-6 weeks. These aim to fill the gap between conventional 2-week weather forecasts and longer term seasonal outlooks. However it is often difficult for end-users to know how these sub-seasonal forecasts can be best utilised, and how skilful they are for predicting variables of real world interest.

Much prior work on sub-seasonal forecasts has focused on assessing skill scores for large-scale smooth fields of mid- or upper-tropospheric variables, or else has looked at heavily time-averaged quantities. How to extend the lessons of these studies to user applications is not always obvious.

We take a more applied approach, focused on the chaotic and variable weather of Western Europe. We use sub-seasonal temperature forecasts alongside real-world French energy price and demand data in order to directly calculate the financial value of subseasonal forecasts to users in the energy sector. Using this new, real-world framework we make an estimate of cost-loss ratios and so can compare to the results of a simpler potential economic value model.