Kalman filtering approach in the calibration of radar rainfall data: a comparative analysis of state space representations
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 lo...
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| Other Authors: | , |
| Format: | bookPart |
| Language: | eng |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1822/20996 |
| Country: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/20996 |
| Summary: | 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). |
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