Articles | Volume 28, issue 20
https://doi.org/10.5194/hess-28-4715-2024
https://doi.org/10.5194/hess-28-4715-2024
Technical note
 | 
29 Oct 2024
Technical note |  | 29 Oct 2024

Technical note: A guide to using three open-source 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

Related authors

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
Revised manuscript accepted for HESS
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
The use of personal weather station observations to improve precipitation estimation and interpolation
András Bárdossy, Jochen Seidel, and Abbas El Hachem
Hydrol. Earth Syst. Sci., 25, 583–601, https://doi.org/10.5194/hess-25-583-2021,https://doi.org/10.5194/hess-25-583-2021, 2021
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Instruments and observation techniques
An intercomparison of four gridded precipitation products over Europe using an extension of the three-cornered-hat method
Llorenç Lledó, Thomas Haiden, and Matthieu Chevallier
Hydrol. Earth Syst. Sci., 28, 5149–5162, https://doi.org/10.5194/hess-28-5149-2024,https://doi.org/10.5194/hess-28-5149-2024, 2024
Short summary
Technical note: A simple feedforward artificial neural network for high-temporal-resolution rain event detection using signal attenuation from commercial microwave links
Erlend Øydvin, Maximilian Graf, Christian Chwala, Mareile Astrid Wolff, Nils-Otto Kitterød, and Vegard Nilsen
Hydrol. Earth Syst. Sci., 28, 5163–5171, https://doi.org/10.5194/hess-28-5163-2024,https://doi.org/10.5194/hess-28-5163-2024, 2024
Short summary
Technical note: Investigating the potential for smartphone-based monitoring of evapotranspiration and land surface energy-balance partitioning
Adriaan J. Teuling, Belle Holthuis, and Jasper F. D. Lammers
Hydrol. Earth Syst. Sci., 28, 3799–3806, https://doi.org/10.5194/hess-28-3799-2024,https://doi.org/10.5194/hess-28-3799-2024, 2024
Short summary
Exploring patterns in precipitation intensity–duration–area–frequency relationships using weather radar data
Talia Rosin, Francesco Marra, and Efrat Morin
Hydrol. Earth Syst. Sci., 28, 3549–3566, https://doi.org/10.5194/hess-28-3549-2024,https://doi.org/10.5194/hess-28-3549-2024, 2024
Short summary
Merging with crowdsourced rain gauge data improves pan-European radar precipitation estimates
Aart Overeem, Hidde Leijnse, Gerard van der Schrier, Else van den Besselaar, Irene Garcia-Marti, and Lotte Wilhelmina de Vos
Hydrol. Earth Syst. Sci., 28, 649–668, https://doi.org/10.5194/hess-28-649-2024,https://doi.org/10.5194/hess-28-649-2024, 2024
Short summary

Cited articles

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. a, b, c, d
Bárdossy, A., Seidel, J., Eisele, M., Hachem, A. E., Kunstmann, H., Chwala, C., Graf, M., Demuth, N., and Gerlach, N.: Verbesserung der Abschätzung von Gebietsniederschlägen mittels opportunistischer Niederschlagsmessungen am Beispiel des Ahr-Hochwassers im Juli 2021, Hydrologie und Wasserbewirtschaftung, 66, 208–214, https://www.hywa-online.de/download/hywa-heft-4-2022/ (last access: 11 October 2024), 2022. a, b
Berne, A., Delrieu, G., Creutin, J.-D., and Obled, C.: Temporal and spatial resolution of rainfall measurements required for urban hydrology, J. Hydrol., 299, 166–179, https://doi.org/10.1016/j.jhydrol.2004.08.002, 2004. a
Boeckhout, M., Zielhuis, G. A., and Bredenoord, A. L.: The FAIR guiding principles for data stewardship: fair enough?, Eur. J. Hum. Genet., 26, 931–936, 2018. a
Chwala, C., Graf, M., Øydvin, E., Habi, H. V., El Hachem, A., Schutz, G., Seidel, J., de Vos, L., Fencl, M., Blettner, N., and Overeem, A.: OpenSenseAction/OPENSENSE_sandbox: v0.1.0 (v0.1.0), Zenodo [code], https://doi.org/10.5281/zenodo.13929196, 2024. a
Download
Short summary
This study presents an overview of open-source quality control (QC) algorithms for rainfall data from personal weather stations (PWSs). The methodology and usability along technical and operational guidelines for using every QC algorithm are presented. All three QC algorithms are available for users to explore in the OpenSense sandbox. They were applied in a case study using PWS data from the Amsterdam region in the Netherlands.  The results highlight the necessity for data quality control.