Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/20996

TitleKalman filtering approach in the calibration of radar rainfall data: a comparative analysis of state space representations
Author(s)Costa, Marco
Monteiro, Magda S. V.
Gonçalves, A. Manuela
KeywordsKalman filter
State space model
Rainfall estimates
Weather radar
Calibration
Nonparametric estimation
Issue date2012
PublisherNova Science Publishers
Abstract(s)In this chapter it is presented a comparative study of some methods to estimate radar rainfall in real time. This work in- tends to discuss and compare different state space formulations based on a same data set; for instance, the comparison between the mode- ling of the mean field radar rainfall logarithmic bias (Chumchean et al., 2006), a linear radar-rain gauge calibration model (Alpuim & Barbosa, 1999; Costa & Alpuim, 2011) and a power law model (Brown et al., 2001).
TypeBook part
URIhttp://hdl.handle.net/1822/20996
ISBN978-1-62081-591-5
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CMAT - Artigos em atas de conferências e capítulos de livros com arbitragem / Papers in proceedings of conferences and book chapters with peer review

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