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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

ainfall retrieval algorithm for commercial microwave links: stochastic calibratio

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Author(s):
Wolff, Wagner [1] ; Overeem, Aart [2, 3] ; Leijnse, Hidde [2, 3] ; Uijlenhoet, Remko [3, 4]
Total Authors: 4
Affiliation:
[1] Luiz de Queiroz Coll Agr ESALQ USP, Dept Biosyst Engn, Piracicaba - Brazil
[2] Royal Netherlands Meteorol Inst KNMI, R&D Observat & Data Technol, De Bilt - Netherlands
[3] Wageningen Univ & Res WUR, Hydrol & Quantitat Water Management Grp, Wageningen - Netherlands
[4] Delft Univ Technol TU Delft, Dept Water Management, Delft - Netherlands
Total Affiliations: 4
Document type: Journal article
Source: Atmospheric Measurement Techniques; v. 15, n. 2, p. 485-502, JAN 27 2022.
Web of Science Citations: 0
Abstract

During the last decade, rainfall monitoring using signal-level data from commercial microwave links (CMLs) in cellular communication networks has been proposed as a complementary way to estimate rainfall for large areas. Path-averaged rainfall is retrieved between the transmitting and receiving cellular antennas of a CML. One rainfall estimation algorithm for CMLs is RAINLINK, which has been employed in different regions (e.g., Brazil, Italy, the Netherlands, and Pakistan) with satisfactory results. However, the RAINLINK parameters have been calibrated for a unique optimum solution, which is inconsistent with the fact that multiple similar or equivalent solutions may exist due to uncertainties in algorithm structure, input data, and parameters. Here, we show how CML rainfall estimates can be improved by calibrating all parameters of the algorithm systematically and simultaneously with the stochastic particle swarm optimization method, which is used for the numerical maximization of the objective function. An open dataset of approximately 2800 sub-links of minimum and maximum received signal levels over 15 min intervals covering the Netherlands (similar to 35 500 km(2)) is employed: 12 d are used for calibration and 3 months for validation. A gauge-adjusted radar rainfall dataset is utilized as a reference. Verification of path-average daily rainfall shows a reasonable improvement for the stochastically calibrated parameters with respect to RAINLINK's default parameter settings. Results further improve when averaged over the Netherlands. Moreover, the method provides a better underpinning of the chosen parameter values and is therefore of general interest for calibration of RAINLINK's parameters for other climates and cellular communication networks. (AU)

FAPESP's process: 17/09708-7 - Rainfall mapping from cellular commercial microwave links: parameters calibration and uncertainty analysis in subtropical climate
Grantee:Wagner Wolff
Support type: Scholarships abroad - Research Internship - Post-doctor
FAPESP's process: 16/15342-2 - Lysimetric calibration and uncertainty analysis of empirical parameters of the SEBAL algorithm in subtropical climate
Grantee:Wagner Wolff
Support type: Scholarships in Brazil - Post-Doctorate