Evaluation of a compound distribution based on weather pattern subsampling for extreme rainfall in Norway
- 1Univ. Grenoble Alpes, LTHE, 38000 Grenoble, France
- 2CNRS, LTHE, 38000 Grenoble, France
- 3Norwegian Water Resources and Energy Directorate (NVE), P.O. Box 5091, Majorstua, Oslo, Norway
- 4EDF – DTG, 21 Avenue de l'Europe, BP 41, 38040 Grenoble CEDEX 9, France
Abstract. Simulation methods for design flood analyses require estimates of extreme precipitation for simulating maximum discharges. This article evaluates the multi-exponential weather pattern (MEWP) model, a compound model based on weather pattern classification, seasonal splitting and exponential distributions, for its suitability for use in Norway. The MEWP model is the probabilistic rainfall model used in the SCHADEX method for extreme flood estimation. Regional scores of evaluation are used in a split sample framework to compare the MEWP distribution with more general heavy-tailed distributions, in this case the Multi Generalized Pareto Weather Pattern (MGPWP) distribution. The analysis shows the clear benefit obtained from seasonal and weather pattern-based subsampling for extreme value estimation. The MEWP distribution is found to have an overall better performance as compared with the MGPWP, which tends to overfit the data and lacks robustness. Finally, we take advantage of the split sample framework to present evidence for an increase in extreme rainfall in the southwestern part of Norway during the period 1979–2009, relative to 1948–1978.