Short-range forecast of heavy rainfall over the Kama River basin in 2019 with atmospheric models ICON, GFS and WRF

Abstract

The summer of 2019 was one of the wettest in the observation history in the western part of the Ural region. Excessive rainfall formed several rain flood events on the rivers of the Kama reservoir basin. In this study, we assess the accuracy of short-range (with a 15-27 h lead time) forecasts of heavy rainfall events observed in 2019 with global numerical weather prediction (NWP) models, ICON and GFS, and a mesoscale model, WRF, launched in a convection-permitting mode. Two metrics, Critical Success Index (CSI) and Extreme Dependency Score (EDI), are used to assess the forecast skills of the global NWP models. Throughout the study period, both global NWP models underestimate the frequency and intensity of heavy rainfall events, mainly due to the omission of local rainstorms. However, heavy precipitation related to cyclones or frontal waves is predicted quite successfully. In addition, we analyse in detail a heavy rainfall event on July 14-16, 2019 which caused a high flood in the western part of the Perm region. The most reliable simulation results have been obtained with the WRF model.