Speaker
Description
Accurate rainfall observations are key for several applications, such as nowcasting and hydrological forecasting. However, rainfall is highly variable in both space and time, resulting in significant uncertainties in areal rainfall products. Estimates of this spatial and temporal variability are needed for spatial interpolation and merging of rainfall products. Traditional rain gauge networks are often too sparse to resolve this variability. In this study, we make use of personal weather stations, a unique high-density rain gauge network with a high temporal resolution (i.e. 5-min) over a three-year period to quantify the spatial variability of rainfall over the whole of the Netherlands (about 1 gauge per 10km2). We investigated the spatial variability of rainfall at different temporal aggregation intervals by fitting climatological spherical semi-variograms, revealing a strong seasonal pattern. In addition, we examined the spatial dependency of rainfall in different directions to characterize anisotropy.