Quantifying spatial rainfall variability using a country-wide high-density rain gauge network

Accurate rainfall observations are important for hydrological applications. However, rainfall exhibits strong spatial and temporal variability, 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 a unique high-density rain gauge network with a high temporal resolution (i.e. 5-min) over a three-year period (2022-2024) 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. Furthermore, this high-density network enables us to assess uncertainties in rainfall estimates across different spatial scales, ranging from weather radar pixels (~1 km²), satellite footprints (~10-100 km²) to catchments scales.