A variational approach to retrieve rain rate by combining information from rain gauges, radars, and microwave links

Bianchi, B., Van Leeuwen, P., Hogan, R. ORCID: https://orcid.org/0000-0002-3180-5157 and Berne, A. (2013) A variational approach to retrieve rain rate by combining information from rain gauges, radars, and microwave links. Journal of Hydrometeorology, 14 (6). pp. 1897-1909. ISSN 1525-7541 doi: 10.1175/JHM-D-12-094.1

Abstract/Summary

Accurate and reliable rain rate estimates are important for various hydrometeorological applications. Consequently, rain sensors of different types have been deployed in many regions. In this work, measurements from different instruments, namely, rain gauge, weather radar, and microwave link, are combined for the first time to estimate with greater accuracy the spatial distribution and intensity of rainfall. The objective is to retrieve the rain rate that is consistent with all these measurements while incorporating the uncertainty associated with the different sources of information. Assuming the problem is not strongly nonlinear, a variational approach is implemented and the Gauss–Newton method is used to minimize the cost function containing proper error estimates from all sensors. Furthermore, the method can be flexibly adapted to additional data sources. The proposed approach is tested using data from 14 rain gauges and 14 operational microwave links located in the Zürich area (Switzerland) to correct the prior rain rate provided by the operational radar rain product from the Swiss meteorological service (MeteoSwiss). A cross-validation approach demonstrates the improvement of rain rate estimates when assimilating rain gauge and microwave link information.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/40384
Identification Number/DOI	10.1175/JHM-D-12-094.1
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO) Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	American Meteorological Society
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