Articles | Volume 25, issue 2
https://doi.org/10.5194/hess-25-583-2021
https://doi.org/10.5194/hess-25-583-2021
Research article
 | 
10 Feb 2021
Research article |  | 10 Feb 2021

The use of personal weather station observations to improve precipitation estimation and interpolation

András Bárdossy, Jochen Seidel, and Abbas El Hachem

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Cited articles

Ahmed, S. and de Marsily, G.: Comparison of geostatistical methods for estimating transmissivity using data transmissivity and specific capacity, Water Resour. Res., 23, 1717–1737, 1987. a
Bárdossy, A.: Interpolation of groundwater quality parameters with some values below the detection limit, Hydrol. Earth Syst. Sci., 15, 2763–2775, https://doi.org/10.5194/hess-15-2763-2011, 2011. a
Bárdossy, A. and Kundzewicz, Z.: Geostatistical methods for detection of outliers in groundwater quality spatial fields, J. Hydrol., 115, 343–359, https://doi.org/10.1016/0022-1694(90)90213-H, 1990. a
Bárdossy, A. and Pegram, G.: Interpolation of precipitation under topographic influence at different time scales, Water Resour. Res., 49, 4545–4565, 2013. a, b, c
Berndt, C. and Haberlandt, U.: Spatial interpolation of climate variables in Northern Germany – Influence of temporal resolution and network density, J. Hydrol.: Reg. Stud., 15, 184–202, https://doi.org/10.1016/j.ejrh.2018.02.002, 2018. a
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Short summary
In this study, the applicability of data from private weather stations (PWS) for precipitation interpolation was investigated. Due to unknown errors and biases in these observations, a two-step filter was developed that uses indicator correlations and event-based spatial precipitation patterns. The procedure was tested and cross validated for the state of Baden-Württemberg (Germany). The biggest improvement is achieved for the shortest time aggregations.