Articles | Volume 18, issue 13
https://doi.org/10.5194/amt-18-3229-2025
https://doi.org/10.5194/amt-18-3229-2025
Research article
 | 
16 Jul 2025
Research article |  | 16 Jul 2025

Adaptation of RainGaugeQC algorithms for quality control of rain gauge data from professional and non-professional measurement networks

Katarzyna Ośródka, Jan Szturc, Anna Jurczyk, and Agnieszka Kurcz

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Cited articles

Alerskans, E., Lussana, C., Nipen, T. N., and Seierstad, I. A.: Optimizing Spatial Quality Control for a Dense Network of Meteorological Stations, J. Atmos. Ocean. Tech., 39, 973–984, https://doi.org/10.1175/JTECH-D-21-0184.1, 2022. 
Bárdossy, A., Seidel, J., and El Hachem, A.: The use of personal weather station observations to improve precipitation estimation and interpolation, Hydrol. Earth Syst. Sci., 25, 583–601, https://doi.org/10.5194/hess-25-583-2021, 2021. 
Båserud, L., Lussana, C., Nipen, T. N., Seierstad, I. A., Oram, L., and Aspelien, T.: TITAN automatic spatial quality control of meteorological in-situ observations, Adv. Sci. Res., 17, 153–163, https://doi.org/10.5194/asr-17-153-2020, 2020. 
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Berndt, C. and Haberlandt, U.: Spatial interpolation of climate variables in Northern Germany –Influence of temporal resolution and network density, J. Hydrol., 15, 184–202, https://doi.org/10.1016/j.ejrh.2018.02.002, 2018. 
Short summary
This paper describes a modified RainGaugeQC system for real-time quality control of rain gauge measurements made every 10 min. It has been significantly modified to control data from non-professional and private measurement networks of lower quality than professional data. The modifications went in the direction of performing more sophisticated data control, applying weather radar data, and taking into account various aspects such as consistency analysis of data time series and bias detection.
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