2022 Volume 22 Pages 33-38
A large ensemble historical and future climate simulation dataset (d4PDF; database for Policy Decision making for Future climate change) was spatially interpolated into a grid-spacing of approximately 1-km to cover Hokkaido, Japan using a statistical downscaling method. This dataset offers daily mean 2-m air temperatures and daily total precipitations under historical and future climate with 2 K and 4 K temperature rises. 900-year meteorological variables were available for historical and future climate, allowing probabilistic assessment of effects of meteorology on agricultural productivity. Biases in the downscaled data were corrected by a method based on cumulative density function of the variables and present-day climate dataset called the Agro-Meteorological Grid Square Data developed by National Agricultural and Food Research Organization (NARO) as the reference dataset. We here present the procedure of statistical downscaling and a typical use case of this dataset focusing on probabilistic assessment of wine grape production in Hokkaido. Several points to be noted are mentioned for potential users of this dataset.
