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

Related authors

Assessing rainfall radar errors with an inverse stochastic modelling framework
Amy Charlotte Green, Chris G. Kilsby, and András Bárdossy
EGUsphere, https://doi.org/10.5194/egusphere-2024-26,https://doi.org/10.5194/egusphere-2024-26, 2024
Short summary
Probabilistic downscaling of EURO-CORDEX precipitation data for the assessment of future areal precipitation extremes of different durations
Abbas El Hachem, Jochen Seidel, and András Bárdossy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-288,https://doi.org/10.5194/hess-2023-288, 2024
Preprint under review for HESS
Short summary
Technical note: Overview and comparison of three quality control algorithms for rainfall data from personal weather stations
Abbas El Hachem, Jochen Seidel, Tess O'Hara, Roberto Villalobos Herrera, Aart Overeem, Remko Uijlenhoet, András Bárdossy, and Lotte de Vos
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-195,https://doi.org/10.5194/hess-2023-195, 2023
Revised manuscript under review for HESS
Short summary
Why do our rainfall–runoff models keep underestimating the peak flows?
András Bárdossy and Faizan Anwar
Hydrol. Earth Syst. Sci., 27, 1987–2000, https://doi.org/10.5194/hess-27-1987-2023,https://doi.org/10.5194/hess-27-1987-2023, 2023
Short summary
Technical Note: Space–time statistical quality control of extreme precipitation observations
Abbas El Hachem, Jochen Seidel, Florian Imbery, Thomas Junghänel, and András Bárdossy
Hydrol. Earth Syst. Sci., 26, 6137–6146, https://doi.org/10.5194/hess-26-6137-2022,https://doi.org/10.5194/hess-26-6137-2022, 2022
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Mathematical applications
Using statistical models to depict the response of multi-timescale drought to forest cover change across climate zones
Yan Li, Bo Huang, and Henning W. Rust
Hydrol. Earth Syst. Sci., 28, 321–339, https://doi.org/10.5194/hess-28-321-2024,https://doi.org/10.5194/hess-28-321-2024, 2024
Short summary
Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations
Magdalena Uber, Michael Haller, Christoph Brendel, Gudrun Hillebrand, and Thomas Hoffmann
Hydrol. Earth Syst. Sci., 28, 87–102, https://doi.org/10.5194/hess-28-87-2024,https://doi.org/10.5194/hess-28-87-2024, 2024
Short summary
The most extreme rainfall erosivity event ever recorded in China up to 2022: the 7.20 storm in Henan Province
Yuanyuan Xiao, Shuiqing Yin, Bofu Yu, Conghui Fan, Wenting Wang, and Yun Xie
Hydrol. Earth Syst. Sci., 27, 4563–4577, https://doi.org/10.5194/hess-27-4563-2023,https://doi.org/10.5194/hess-27-4563-2023, 2023
Short summary
The role of atmospheric rivers in the distribution of heavy precipitation events over North America
Sara M. Vallejo-Bernal, Frederik Wolf, Niklas Boers, Dominik Traxl, Norbert Marwan, and Jürgen Kurths
Hydrol. Earth Syst. Sci., 27, 2645–2660, https://doi.org/10.5194/hess-27-2645-2023,https://doi.org/10.5194/hess-27-2645-2023, 2023
Short summary
Study on a mother wavelet optimization framework based on change-point detection of hydrological time series
Jiqing Li, Jing Huang, Lei Zheng, and Wei Zheng
Hydrol. Earth Syst. Sci., 27, 2325–2339, https://doi.org/10.5194/hess-27-2325-2023,https://doi.org/10.5194/hess-27-2325-2023, 2023
Short summary

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
Download
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.