Articles | Volume 28, issue 3
https://doi.org/10.5194/hess-28-649-2024
https://doi.org/10.5194/hess-28-649-2024
Research article
 | 
14 Feb 2024
Research article |  | 14 Feb 2024

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

Related authors

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
Hydrol. Earth Syst. Sci., 28, 4715–4731, https://doi.org/10.5194/hess-28-4715-2024,https://doi.org/10.5194/hess-28-4715-2024, 2024
Short summary
Measuring rainfall using microwave links: the influence of temporal sampling
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024,https://doi.org/10.5194/amt-17-2811-2024, 2024
Short summary
Assessing sampling and retrieval errors of GPROF precipitation estimates over the Netherlands
Linda Bogerd, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 247–259, https://doi.org/10.5194/amt-17-247-2024,https://doi.org/10.5194/amt-17-247-2024, 2024
Short summary
EURADCLIM: the European climatological high-resolution gauge-adjusted radar precipitation dataset
Aart Overeem, Else van den Besselaar, Gerard van der Schrier, Jan Fokke Meirink, Emiel van der Plas, and Hidde Leijnse
Earth Syst. Sci. Data, 15, 1441–1464, https://doi.org/10.5194/essd-15-1441-2023,https://doi.org/10.5194/essd-15-1441-2023, 2023
Short summary
Rainfall retrieval algorithm for commercial microwave links: stochastic calibration
Wagner Wolff, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 15, 485–502, https://doi.org/10.5194/amt-15-485-2022,https://doi.org/10.5194/amt-15-485-2022, 2022
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Instruments and observation techniques
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
Hydrol. Earth Syst. Sci., 28, 4715–4731, https://doi.org/10.5194/hess-28-4715-2024,https://doi.org/10.5194/hess-28-4715-2024, 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
Technical Note: A simple feedforward artificial neural network for high temporal resolution classification of wet and dry periods using signal attenuation from commercial microwave links
Erlend Øydvin, Maximilian Graf, Christian Chwala, Mareile Astrid Wolff, Nils-Otto Kitterød, and Vegard Nilsen
EGUsphere, https://doi.org/10.5194/egusphere-2024-647,https://doi.org/10.5194/egusphere-2024-647, 2024
Short summary
An intercomparison of four gridded precipitation products over Europe using the three-cornered-hat method
Llorenç Lledó, Thomas Haiden, and Matthieu Chevallier
EGUsphere, https://doi.org/10.5194/egusphere-2024-807,https://doi.org/10.5194/egusphere-2024-807, 2024
Short summary

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. a
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, e, f
Barnes, S. L.: A technique for maximizing details in numerical weather map analysis, J. Appl. Meteorol., 3, 396–409, https://doi.org/10.1175/1520-0450(1964)003<0396:ATFMDI>2.0.CO;2, 1964. a
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. a, b, c, d
Bell, S., Cornford, D., and Bastin, L.: The state of automated amateur weather observations, Weather, 68, 36–41, https://doi.org/10.1002/wea.1980, 2013. a
Download
Short summary
Ground-based radar precipitation products typically need adjustment with rain gauge accumulations to achieve a reasonable accuracy. Crowdsourced rain gauge networks have a much higher density than conventional ones. Here, a 1-year personal weather station (PWS) gauge dataset is obtained. After quality control, the 1 h PWS gauge accumulations are merged with pan-European radar accumulations. The potential of crowdsourcing to improve radar precipitation products in (near) real time is confirmed.