Articles | Volume 11, issue 8
https://doi.org/10.5194/amt-11-4645-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-4645-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Aug 2018
Research article |
| 09 Aug 2018
| 09 Aug 2018
A measurement campaign to assess sources of error in microwave link rainfall estimation
Hydrology and Quantitative Water Management Group, Wageningen
University & Research, P.O. Box 47, 6700 AA, Wageningen, the Netherlands
Aart Overeem
Hydrology and Quantitative Water Management Group, Wageningen
University & Research, P.O. Box 47, 6700 AA, Wageningen, the Netherlands
Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730
AE, De Bilt, the Netherlands
Hidde Leijnse
Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730
AE, De Bilt, the Netherlands
Remko Uijlenhoet
Hydrology and Quantitative Water Management Group, Wageningen
University & Research, P.O. Box 47, 6700 AA, Wageningen, the Netherlands
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39 citations as recorded by crossref.
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- Precipitation Estimates From Commercial Microwave Links: Practical Approaches to Wet-Antenna Correction J. Pastorek et al. 10.1109/TGRS.2021.3110004
- Modeling of Wet Antenna Attenuation for Precipitation Estimation From Microwave Links C. Moroder et al. 10.1109/LGRS.2019.2922768
- Error Analysis of Rainfall Inversion Based on Commercial Microwave Links With A–R Relationship Considering the Rainfall Features K. Pu et al. 10.1109/TGRS.2023.3253949
- Merging weather radar data and opportunistic rainfall sensor data to enhance rainfall estimates J. Nielsen et al. 10.1016/j.atmosres.2024.107228
- Combining commercial microwave links and weather radar for classification of dry snow and rainfall E. Øydvin et al. 10.5194/amt-18-2279-2025
- Deep Learning for an Improved Prediction of Rainfall Retrievals From Commercial Microwave Links J. Pudashine et al. 10.1029/2019WR026255
- Use of the C-Band Microwave Link to Distinguish between Rainy and Dry Periods B. He et al. 10.1155/2019/3428786
- Tropical rainfall monitoring with commercial microwave links in Sri Lanka A. Overeem et al. 10.1088/1748-9326/ac0fa6
- Low complexity single-layer neural network for enhanced rainfall estimation using microwave links A. Daher et al. 10.2166/hydro.2022.099
- The Feasibility Analysis of Cellphone Signal to Detect the Rain: Experimental Study K. Song et al. 10.1109/LGRS.2019.2940854
- Rainfall estimation from a German-wide commercial microwave link network: optimized processing and validation for 1 year of data M. Graf et al. 10.5194/hess-24-2931-2020
- Rain Monitoring with Polarimetric GNSS Signals: Ground-Based Experimental Research H. An et al. 10.3390/rs11192293
- Commercial microwave links for urban drainage modelling: The effect of link characteristics and their position on runoff simulations J. Pastorek et al. 10.1016/j.jenvman.2019.109522
- Missing Rainfall Extremes in Commercial Microwave Link Data Due To Complete Loss of Signal J. Polz et al. 10.1029/2022EA002456
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- A year of attenuation data from a commercial dual-polarized duplex microwave link with concurrent disdrometer, rain gauge, and weather observations A. Špačková et al. 10.5194/essd-13-4219-2021
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- Atmospheric observations with E-band microwave links – challenges and opportunities M. Fencl et al. 10.5194/amt-13-6559-2020
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- Rainfall estimation using a microwave link based on an improved rain-induced attenuation model K. Song et al. 10.1080/2150704X.2019.1648902
- A Statistical Approach to Retrieve Rainfall Intensity by Attenuation Measurements From Commercial Microwave Links X. Zheng et al. 10.1029/2023EF003718
- An evaluation of weather radar adjustment algorithms using synthetic data M. Silver et al. 10.1016/j.jhydrol.2019.06.064
- Experimental Study of Detecting Rainfall Using Microwave Links: Classification of Wet and Dry Periods K. Song et al. 10.1109/JSTARS.2020.3021555
- On the potential of commercial microwave link networks for high spatial resolution rainfall monitoring in urban areas X. Zheng et al. 10.1016/j.atmosres.2022.106289
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- Application of commercial microwave links (CMLs) attenuation for quantitative estimation of precipitation M. Pasierb et al. 10.1002/met.2218
- Earth-to-Earth Microwave Rain Attenuation Measurements: A Survey On the Recent Literature V. Christofilakis et al. 10.3390/sym12091440
- Precipitation Monitoring Using Commercial Microwave Links: Current Status, Challenges and Prospectives P. Zhang et al. 10.3390/rs15194821
- Evaluation of error components in rainfall retrieval from collocated commercial microwave links A. Špačková et al. 10.5194/amt-16-3865-2023
- Characteristics of Rain-Induced Attenuation over Signal Links at Frequency Ranges of 25 and 38 GHz Observed in Beijing C. Han et al. 10.3390/rs13112156
- OpenMRG: Open data from Microwave links, Radar, and Gauges for rainfall quantification in Gothenburg, Sweden J. Andersson et al. 10.5194/essd-14-5411-2022
- Estimating raindrop size distributions using microwave link measurements: potential and limitations T. van Leth et al. 10.5194/amt-13-1797-2020
- Microwave Instrument for Simultaneous Wet Antenna Attenuation and Precipitation Measurement C. Moroder et al. 10.1109/TIM.2019.2961498
- Commercial microwave link networks for rainfall observation: Assessment of the current status and future challenges C. Chwala & H. Kunstmann 10.1002/wat2.1337
- Measuring rainfall using microwave links: the influence of temporal sampling L. van der Valk et al. 10.5194/amt-17-2811-2024
- Opportunistic remote sensing of rainfall using microwave links from cellular communication networks R. Uijlenhoet et al. 10.1002/wat2.1289
- Rainfall retrieval with commercial microwave links in São Paulo, Brazil M. Rios Gaona et al. 10.5194/amt-11-4465-2018
37 citations as recorded by crossref.
- A Novel Adaptive Rain-Induced Attenuation Model Based on Clustering Algorithm for Commercial Microwave Link-Based Rainfall Inversion K. Pu et al. 10.1109/LGRS.2023.3342976
- Precipitation Estimates From Commercial Microwave Links: Practical Approaches to Wet-Antenna Correction J. Pastorek et al. 10.1109/TGRS.2021.3110004
- Modeling of Wet Antenna Attenuation for Precipitation Estimation From Microwave Links C. Moroder et al. 10.1109/LGRS.2019.2922768
- Error Analysis of Rainfall Inversion Based on Commercial Microwave Links With A–R Relationship Considering the Rainfall Features K. Pu et al. 10.1109/TGRS.2023.3253949
- Merging weather radar data and opportunistic rainfall sensor data to enhance rainfall estimates J. Nielsen et al. 10.1016/j.atmosres.2024.107228
- Combining commercial microwave links and weather radar for classification of dry snow and rainfall E. Øydvin et al. 10.5194/amt-18-2279-2025
- Deep Learning for an Improved Prediction of Rainfall Retrievals From Commercial Microwave Links J. Pudashine et al. 10.1029/2019WR026255
- Use of the C-Band Microwave Link to Distinguish between Rainy and Dry Periods B. He et al. 10.1155/2019/3428786
- Tropical rainfall monitoring with commercial microwave links in Sri Lanka A. Overeem et al. 10.1088/1748-9326/ac0fa6
- Low complexity single-layer neural network for enhanced rainfall estimation using microwave links A. Daher et al. 10.2166/hydro.2022.099
- The Feasibility Analysis of Cellphone Signal to Detect the Rain: Experimental Study K. Song et al. 10.1109/LGRS.2019.2940854
- Rainfall estimation from a German-wide commercial microwave link network: optimized processing and validation for 1 year of data M. Graf et al. 10.5194/hess-24-2931-2020
- Rain Monitoring with Polarimetric GNSS Signals: Ground-Based Experimental Research H. An et al. 10.3390/rs11192293
- Commercial microwave links for urban drainage modelling: The effect of link characteristics and their position on runoff simulations J. Pastorek et al. 10.1016/j.jenvman.2019.109522
- Missing Rainfall Extremes in Commercial Microwave Link Data Due To Complete Loss of Signal J. Polz et al. 10.1029/2022EA002456
- Uncertainties in discharge predictions based on microwave link rainfall estimates in a small urban catchment J. Pastorek et al. 10.1016/j.jhydrol.2022.129051
- A year of attenuation data from a commercial dual-polarized duplex microwave link with concurrent disdrometer, rain gauge, and weather observations A. Špačková et al. 10.5194/essd-13-4219-2021
- Rainfall measurement from mobile telecommunication network and potential benefit for urban hydrology in Africa: a simulation framework for uncertainty propagation analysis M. Turko et al. 10.5194/piahs-383-237-2020
- Rainfall Estimation Accuracy of a Nationwide Instantaneously Sampling Commercial Microwave Link Network: Error Dependency on Known Characteristics L. de Vos et al. 10.1175/JTECH-D-18-0197.1
- Atmospheric observations with E-band microwave links – challenges and opportunities M. Fencl et al. 10.5194/amt-13-6559-2020
- Rainfall estimates from opportunistic sensors in Germany across spatio-temporal scales M. Graf et al. 10.1016/j.ejrh.2021.100883
- Rainfall estimation using a microwave link based on an improved rain-induced attenuation model K. Song et al. 10.1080/2150704X.2019.1648902
- A Statistical Approach to Retrieve Rainfall Intensity by Attenuation Measurements From Commercial Microwave Links X. Zheng et al. 10.1029/2023EF003718
- An evaluation of weather radar adjustment algorithms using synthetic data M. Silver et al. 10.1016/j.jhydrol.2019.06.064
- Experimental Study of Detecting Rainfall Using Microwave Links: Classification of Wet and Dry Periods K. Song et al. 10.1109/JSTARS.2020.3021555
- On the potential of commercial microwave link networks for high spatial resolution rainfall monitoring in urban areas X. Zheng et al. 10.1016/j.atmosres.2022.106289
- Using Machine Learning Techniques for Rainfall Estimation Based on Microwave Links of Mobile Telecommunication Networks E. Kamtchoum et al. 10.1007/s42979-022-01458-6
- Application of commercial microwave links (CMLs) attenuation for quantitative estimation of precipitation M. Pasierb et al. 10.1002/met.2218
- Earth-to-Earth Microwave Rain Attenuation Measurements: A Survey On the Recent Literature V. Christofilakis et al. 10.3390/sym12091440
- Precipitation Monitoring Using Commercial Microwave Links: Current Status, Challenges and Prospectives P. Zhang et al. 10.3390/rs15194821
- Evaluation of error components in rainfall retrieval from collocated commercial microwave links A. Špačková et al. 10.5194/amt-16-3865-2023
- Characteristics of Rain-Induced Attenuation over Signal Links at Frequency Ranges of 25 and 38 GHz Observed in Beijing C. Han et al. 10.3390/rs13112156
- OpenMRG: Open data from Microwave links, Radar, and Gauges for rainfall quantification in Gothenburg, Sweden J. Andersson et al. 10.5194/essd-14-5411-2022
- Estimating raindrop size distributions using microwave link measurements: potential and limitations T. van Leth et al. 10.5194/amt-13-1797-2020
- Microwave Instrument for Simultaneous Wet Antenna Attenuation and Precipitation Measurement C. Moroder et al. 10.1109/TIM.2019.2961498
- Commercial microwave link networks for rainfall observation: Assessment of the current status and future challenges C. Chwala & H. Kunstmann 10.1002/wat2.1337
- Measuring rainfall using microwave links: the influence of temporal sampling L. van der Valk et al. 10.5194/amt-17-2811-2024
Latest update: 17 Aug 2025
Short summary
We present a campaign to address several error sources associated with rainfall estimates from microwave links in cellular communication networks. The set-up consists of three co-located links, complemented with reference instruments. We investigate events covering different attenuating phenomena: Rainfall, solid precipitation, temperature, fog, antenna wetting due to rain or dew, and clutter.
We present a campaign to address several error sources associated with rainfall estimates from...
