Kalman filtering approach in the calibration of radar rainfall data: a comparative analysis of state space representations

Abstract

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).