Abstract
Abstract. Rain gauges can offer high quality rainfall measurements at their locations. 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 variograms accurately. In this paper a 30-year dataset of daily rain accumulations gathered at 29 automatic weather stations operated by KNMI (Royal Netherlands Meteorological Institute) 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, following simple cosine functions. Semi-variances at short ranges during winter and spring tend to be underestimated, but semi-variances during summer and autumn are well predicted.
Highlights
Rainfall is highly variable both in time and space and accurate measurements are important in hydrology (Bell and Moore, 2000; Arnaud et al, 2002; Tetzlaff and Uhlenbrook, 2005)
The climatological analysis is applied to the KNMI gauges for the 30-year period between January 1979 and February 2009
The average sill and range found from the fitted spherical variograms follow a cosine www.hydrol-earth-syst-sci.net/15/171/2011/
Summary
Rainfall is highly variable both in time and space and accurate measurements are important in hydrology (Bell and Moore, 2000; Arnaud et al, 2002; Tetzlaff and Uhlenbrook, 2005). There are several instruments available to measure these rainfall distributions. The traditional instrument to measure rainfall is the rain gauge. While rain gauges measure rain accurately and continuously at a point, they offer little information on rainfall between gauges. Rain gauges themselves are not fully accurate and are influenced by factors such as calibration accuracy, wind effects and sampling uncertainty, which limits the accuracy for sampling intervals smaller than 10 min (Humphrey et al, 1997; Calder and Kidd, 1978; Marsalek, 1981; Habib et al, 2001; Ciach, 2003; Sieck et al, 2007). Frozen precipitation like snow and hail offers a problem as these hydro-meteors do not melt immediately and will result in a lower precipitation rate estimate over a longer period than occurred
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