Abstract: Fluctuations of the annual number of tropical cyclones over the North Atlantic and of the energy dissipated by the most intense hurricane of a season are related to a variety of predictors [global temperature, SST and ...

Abstract: ne of the main objectives of statistical climatology is to extract relevant information hidden in complex spatial?temporal climatological datasets. To identify spatial patterns, most well-known statistical techniques are ...

Abstract: nsembles used for probabilistic weather forecasting tend to be biased and underdispersive. This paper proposes a statistical method for postprocessing ensembles based on quantile regression forests (QRF), a generalization ...

Abstract: umerical weather forecast errors are routinely corrected through statistical postprocessing by several national weather services. These statistical postprocessing methods build a regression function called model output ...

Abstract: AbstractTo satisfy a wide range of end users, rainfall ensemble forecasts have to be skillful for both low precipitation and extreme events. We introduce local statistical postprocessing methods based on quantile regression ...

Abstract: ne major concern of climate change is the possible rise of temperature extreme events, in terms of occurrence and intensity. To study this phenomenon, reliable daily series are required, for instance to compute daily-based ...