Climatology of daily rainfall semivariance in The Netherlands
Abstract. Rain gauges can offer high quality rainfall measurements at their location. Networks of rain gauges can offer better insight into the space-time variability of rainfall, but they tend to be too widely spaced for accurate estimates between points. While remote sensing systems, such as radars and networks of microwave links, can offer good insight in the spatial variability of rainfall they tend to have more problems in identifying the correct rain amounts at the ground. A way to estimate the variability of rainfall between gauge points is to interpolate between them using fitted variograms. If a dense rain gauge network is lacking it is difficult to estimate accurate variograms. In this paper a 30-year dataset of daily rain accumulations gathered at 29 automatic weather stations operated by KNMI and a one-year dataset of 10 gauges in a network with a radius of 5 km around CESAR (Cabauw Experimental Site for Atmospheric Research) are employed to estimate variograms. Fitted variogram parameters are shown to vary according to season, closely following simple cosine functions allowing for applications in catchment hydrology and rainfall field generation. Semivariances at short ranges during winter and spring tend to be underestimated, but summer and autumn are well predicted. This climatological semivariance can be employed to estimate the accuracy of the rainfall input to a hydrological model even with only few gauges in a given catchment area.