Abstract: tatistical methods to bias correct global or regional climate model output are now common to get data closer to observations in distribution. However, most bias correction (BC) methods work for one variable and one location ...

Abstract: tatistical downscaling models (SDMs) and bias correction (BC) methods are commonly used to provide regional or debiased climate projections. However, most SDMs are utilized in a ?perfect prognosis? context, meaning that ...

Abstract: This work focuses on the clustering of a large dataset of atmospheric vertical profiles of temperature and humidity in order to model a priori information for the problem of retrieving atmospheric variables from satellite ...

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: The comparison of circulation patterns (CPs) obtained from reanalysis data to those from general circulation model (GCM) simulations is a frequent task for model validation, downscaling of GCM simulations, or other climate ...

Abstract: enegal is particularly vulnerable to precipitation variability. To investigate the influence of large-scale circulation on local-scale precipitation, a full spatial?statistical description of precipitation occurrence and ...

Abstract: recipitation is highly variable in space and time; hence, rain gauge time series generally exhibit additional random small-scale variability compared to area averages. Therefore, differences between daily precipitation ...

Abstract: AbstractCompound events are extreme impacts that depend on multiple variables that need not be extreme themselves. In this study, we analyze soil moisture drought as a compound event of precipitation and potential ...