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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 15, issue 1
Hydrol. Earth Syst. Sci., 15, 171–183, 2011
https://doi.org/10.5194/hess-15-171-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 15, 171–183, 2011
https://doi.org/10.5194/hess-15-171-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.

  18 Jan 2011

18 Jan 2011

Climatology of daily rainfall semi-variance in The Netherlands

C. Z. van de Beek, H. Leijnse, P. J. J. F. Torfs, and R. Uijlenhoet C. Z. van de Beek et al.
  • Hydrology and Quantitative Water Management Group, Department of Environmental Sciences, Wageningen University, Wageningen, The Netherlands

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.

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