Exploring the Use of European Weather Regimes for Improving User-Relevant Hydrological Forecasts at the Subseasonal Scale in Switzerland ...

• Main Authors: Chang, Annie Y.-Y., Bogner, Konrad, Grams, Christian M., Monhart, Samuel, Domeisen, Daniela I. V., Zappa, Massimiliano
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Meteorological Society 2023
• Subjects: Climate classification/regimes; Hydrology; Operational forecasting; Machine learning; Ensembles; North Atlantic
• Online Access: https://dx.doi.org/10.5445/ir/1000163785; https://publikationen.bibliothek.kit.edu/1000163785

Across the globe, there has been an increasing interest in improving the predictability of subseasonal hydrometeorological forecasts, as they play a valuable role in medium- to long-term planning in many sectors, such as agriculture, navigation, hydropower, and emergency management. However, these forecasts still have very limited skill at the monthly time scale; hence, this study explores the possibilities for improving forecasts through different pre- and postprocessing techniques at the interface with a Precipitationn–Runoff–Evapotranspiration Hydrological Response Unit Model (PREVAH). Specifically, this research aims to assess the benefit of European weather regime (WR) data within a hybrid forecasting setup, a combination of a traditional hydrological model and a machine learning (ML) algorithm, to improve the performance of subseasonal hydrometeorological forecasts in Switzerland. The WR data contain information about the large-scale atmospheric circulation in the North Atlantic–European region, and ...