Introducing long-term trends into subseasonal temperature forecasts through trend-aware postprocessing

Abstract

Skilful subseasonal forecasts are crucial for issuing early warnings of extreme weather events, such as heatwaves and floods. Operational subseasonal climate forecasts are often produced by global climate models not dissimilar to seasonal forecast models, which typically fail to reproduce observed temperature trends. In this study, we identify that the same issue exists in the subseasonal forecasting system. Subsequently, we adapt a trend-aware forecast postprocessing method, previously developed for seasonal forecasts, to calibrate and correct the trend in subseasonal forecasts. We modify the method to embed 30-year climate trends into the calibrated forecasts even when the available hindca..