Cloud rainfall estimation with multi-attribute typhoon data and edge extraction
Quantitative estimation of the typhoon rainfall is one of the focus in the typhoon research field. In this paper, in order to improve estimation accuracy in the scope and rainfall, the authors use the cloud classify rainfall forecast model based on edge extraction with multi-attribute typhoon data such as infrared data, water vapor data and temperature of brightness blackbody(TBB) data etc. First of all, we use the edge extraction to get the outline of the rainfall, then use the cloud classify rainfall estimation model to obtain the predicted rainfall in the inner area. At last, authors take "Phoenix" typhoon, in 2008, as an example to improve the estimation accuracy in rainfall distribution as well as the cloud rainfall by using the method of cloud rainfall estimation with multi-attribute typhoon data and edge extraction.