〈報文〉ダイナミカルダウンスケール手法による過去20年の気候再現性及び冬季積雪量予測の評価

摘要

This study conducted dynamical downscaling for Japan using a regional atmospheric model (TERC-RAMS) to create the spatially detailed meteorological data for the impact assessment of global warming on the surrounding fields including farming and hydrological cycle. In the first half of this paper, the downscaling for past 20-years climate was conducted and compared with the observational data. The simulated temperature was higher (lower) than the observed one in summer (winter) season, although the bias of temperature in most areas was less than 1℃ throughout year. Precipitation calculated by the model tended to overestimate, except for the summer rainfall in Kyushu and Okinawa. However, the simulated climate by the model was able to reproduce the past climate. Inthe second half, the snow cover change in 2070s was estimated by using the pseudo global warming method with regard to the low and high snow-cover years. The model results showed that the snow cover decreased over a large area. The snow cover in the low snowcover year remained only in a part of Hokkaido. The snow cover in the high snow-cover year was limited in the regions with an altitude higher than 500 m. This result agrees with that of Hara et al. (2008). This study indicates that TERC-RAMS is available to predict inter-annual variation of snow cover. However, the results suggest that the simulation on the coarser horizontal resolution tends to underestimate the amount of snow cover and overestimate the impact of global warming on snow cover change.