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Advances in Geosciences An open-access journal for refereed proceedings and special publications
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Volume 10 | Copyright
Adv. Geosci., 10, 103-109, 2007
https://doi.org/10.5194/adgeo-10-103-2007
© Author(s) 2007. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.

  26 Apr 2007

26 Apr 2007

Spatial correlation of radar and gauge precipitation data in high temporal resolution

J. Brommundt and A. Bárdossy J. Brommundt and A. Bárdossy
  • Institute of Hydraulic Engineering, Chair of Hydrology and Geohydrology, Universitaet Stuttgart, Germany

Abstract. A multi-sites precipitation time series generator for engineering designs is currently being developed. The objective is to generate several time series' simultaneously with correct inter-station relationships. Therefore, a model to estimate correlation between stations for arbitrary points in a project area is needed, using rain gauge data as well as radar data.

Two methods are applied to compare the spatial behaviour of precipitation in both the rain gauge data and the radar data. The first approach is to calculate precipitation intensities from radar reflectivity and use it as gauge data. The results show that the spatial structure in both data sets is similar, but cross correlation varies too much to use radar derived spatial correlation to describe gauge inter-station relationship. Thus, a second approach was tested to account for the differences in the spatial correlation associated to the distribution. Using the indicator time series, cross correlations for different quantiles were calculated from both the rain gauge and radar data. This approach shows that cross correlation varies depending on the chosen quantile. In the lower quantiles, the correlation is very similar in rain gauge and radar data, hence a transfer is possible. This insight is useful to derive cross correlations of rain gauges from radar images. Correlation data for rain gauges thus obtained contains all the information about heterogeneity and anisotropy of the spatial structure of rainfall, which is in the radar data.

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