On the predictive skill for warm spells in Germany across seasons

Intense warm spells, such as heatwaves, can significantly impact human health, the environment, and socio-economic systems. Although heatwaves are typically associated with summer, the occurrence of warm spells during cold seasons can also have profound effects on various sectors. While some effects, such as reduced cold-related mortality, can be considered beneficial, the long-term consequences, e.g. on ecosystems, forests, and agriculture, are concerning. Warm spells during the cold seasons can alter the natural dormancy cycles of plants, causing premature sprouting, flowering, or growth and negatively affecting crop yield and quality. In addition, cold season warm spells can reduce snow accumulation in mountainous regions, potentially affecting downstream water availability. As climate change drives increases in the frequency, intensity, and duration of warm spells, their impacts are becoming more severe and far-reaching. This makes predicting such events a key priority for climate science and risk management.

Climate forecast models offer the potential to predict extreme events like warm spells weeks to months in advance, becoming increasingly relevant for decision-making across various socio-economic sectors. This study examines the predictive skill of the downscaled German Climate Forecast System Version 2.1 (GCFS2.1) for warm spells in Germany on a seasonal scale, encompassing both warm seasons (spring and summer) and cold seasons (autumn and winter).  The analysis relies on hindcast data from the 1991-2020 base period, statistically downscaled to 5 km resolution. It evaluates multiple extreme temperature climate indices, as for example the Warm Spells Duration index, and applies various statistical metrics to assess the predictive skill. The findings reveal high heterogeneity in the ability of the (downscaled) GCFS2.1 to forecast warm spells across seasons, with higher predictive skill during the cold seasons but more limited for the warm seasons.