Local precipitation amounts and frequency are greatly influenced by surrounding topography, such as mountains. However, it has been difficult for conventional numerical forecast models to accurately calculate these effects, as they require more sophisticated and higher resolution models. Professor Kei Yoshimura and Project Associate Professor Takao Yoshikane of the University of Tokyo's Institute of Industrial Science have developed a method to correct for bias by recognizing patterns in the relationship between regional and local weather, which is strongly influenced by complex terrain and other factors. As a result, the method significantly reduces errors and enables estimation of precipitation corresponding to complex topography. This method is expected to reduce the risk of water-related disasters and improve the accuracy of water resource estimation.

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