Search from over 60,000 research works

Advanced Search

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

[thumbnail of Bianchi-2013.pdf]
Preview
Bianchi-2013.pdf - Published Version (1MB) | Preview
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Bianchi, B., Van Leeuwen, P., Hogan, R. orcid id iconORCID: 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.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/40384
Item Type Article
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
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar