Articles | Volume 15, issue 2
https://doi.org/10.5194/amt-15-485-2022
https://doi.org/10.5194/amt-15-485-2022
Research article
 | 
27 Jan 2022
Research article |  | 27 Jan 2022

Rainfall retrieval algorithm for commercial microwave links: stochastic calibration

Wagner Wolff, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet

Related authors

Evaluation of high-intensity rainfall observations from personal weather stations in the Netherlands
Nathalie Rombeek, Markus Hrachowitz, Arjan Droste, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2024-3207,https://doi.org/10.5194/egusphere-2024-3207, 2024
Short summary
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
Flood drivers and trends: a case study of the Geul River catchment (the Netherlands) over the past half century
Athanasios Tsiokanos, Martine Rutten, Ruud J. van der Ent, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 28, 3327–3345, https://doi.org/10.5194/hess-28-3327-2024,https://doi.org/10.5194/hess-28-3327-2024, 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
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

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Closing the gap in the tropics: the added value of radio-occultation data for wind field monitoring across the Equator
Julia Danzer, Magdalena Pieler, and Gottfried Kirchengast
Atmos. Meas. Tech., 17, 4979–4995, https://doi.org/10.5194/amt-17-4979-2024,https://doi.org/10.5194/amt-17-4979-2024, 2024
Short summary
Verification of weather-radar-based hail metrics with crowdsourced observations from Switzerland
Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius
Atmos. Meas. Tech., 17, 4529–4552, https://doi.org/10.5194/amt-17-4529-2024,https://doi.org/10.5194/amt-17-4529-2024, 2024
Short summary
Enhanced Quantitative Precipitation Estimation (QPE) through the opportunistic use of Ku TV-sat links via a Dual-Channel Procedure
Louise Gelbart, Laurent Barthès, François Mercier-Tigrine, Aymeric Chazottes, and Cecile Mallet
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-88,https://doi.org/10.5194/amt-2024-88, 2024
Revised manuscript accepted for AMT
Short summary
Atmospheric motion vector (AMV) error characterization and bias correction by leveraging independent lidar data: a simulation using an observing system simulation experiment (OSSE) and optical flow AMVs
Hai Nguyen, Derek Posselt, Igor Yanovsky, Longtao Wu, and Svetla Hristova-Veleva
Atmos. Meas. Tech., 17, 3103–3119, https://doi.org/10.5194/amt-17-3103-2024,https://doi.org/10.5194/amt-17-3103-2024, 2024
Short summary
Description and validation of the Japanese algorithm for radiative flux and heating rate products with all four EarthCARE instruments: Pre-launch test with A-Train
Akira Yamauchi, Kentaroh Suzuki, Eiji Oikawa, Miho Sekiguchi, Takashi Nagao, and Haruma Ishida
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-78,https://doi.org/10.5194/amt-2024-78, 2024
Revised manuscript accepted for AMT
Short summary

Cited articles

Abdelaziz, R. and Zambrano-Bigiarini, M.: Particle Swarm Optimization for inverse modeling of solute transport in fractured gneiss aquifer, J. Contam. Hydrol., 164, 285–298, https://doi.org/10.1016/j.jconhyd.2014.06.003, 2014. a
Atlas, D. and Ulbrich, C. W.: Path- and area-integrated rainfall measurement by microwave attenuation in the 1–3 cm band, J. Appl. Meteorol., 16, 1322–1331, https://doi.org/10.1175/1520-0450(1977)016<1322:PAAIRM>2.0.CO;2, 1977. a
Bianchi, B., van Leeuwen, P. J., Hogan, R. J., and Berne, A.: A variational approach to retrieve rain rate by combining information from rain gauges, radars, and microwave links, J. Hydrometeorol., 14, 1897–1909, https://doi.org/10.1175/JHM-D-12-094.1, 2013. a
Bisselink, B., Zambrano-Bigiarini, M., Burek, P., and de Roo, A.: Assessing the role of uncertain precipitation estimates on the robustness of hydrological model parameters under highly variable climate conditions, Journal of Hydrology: Regional Studies, 8, 112–129, https://doi.org/10.1016/j.ejrh.2016.09.003, 2016. a
Brauer, C. C., Overeem, A., Leijnse, H., and Uijlenhoet, R.: The effect of differences between rainfall measurement techniques on groundwater and discharge simulations in a lowland catchment, Hydrol. Process., 30, 3885–3900, https://doi.org/10.1002/hyp.10898, 2016. a
Download
Short summary
The existing infrastructure for cellular communication is promising for ground-based rainfall remote sensing. Rain-induced signal attenuation is used in dedicated algorithms for retrieving rainfall depth along commercial microwave links (CMLs) between cell phone towers. This processing is a source of many uncertainties about input data, algorithm structures, parameters, CML network, and local climate. Application of a stochastic optimization method leads to improved CML rainfall estimates.