Estimates of Snowfall Depth, Maximum Snow Depth, and Snow Pack Environments under Global Warming in Japan from Five Sets of Predicted Data

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Abstract

Snowfall depth, maximum snow depth, and snow pack environments under global warming are estimated over all of Japan by using 5 sets of predicted data. The input data used for the estimation were interpolated monthly mean air temperatures and amounts of monthly precipitation under a gradually increasing concentration of co2 for 100 years from present conditions as predicted by 5 different institutes. The predicted trends varied according to geographic location. In Hokkaido and in the highlands of Honshu, no significant change was found, but the maximum snow depth decreased. In the Tohoku district (northeastern Honshu), except for in the highlands, snowfall and maximum snow depth decreased considerably. Snow pack environments changed from "dry" to "wet." At low elevations on the side of the Sea of Japan of Honshu south of the Hokuriku district, no snowfall occurred and no snow pack of consequence was present by the mid-21st century. Although details among the 5 sets of predicted global warming data are different for air temperature and precipitation, the results predicted for snow conditions are very similar. For the influences of precipitation, the decrease observed in Canadian Centre for Climate Modelling and Analysis, and the large fluctuations of Australia's Commonwealth Scientific and Industrial Research Organization, are limited to the winter snowfall depth in Hokkaido and in the highlands of Honshu. In contrast, the influence of the late temperature rising of Meteorological Research Institute (Japan) affects all aspects of snow. Air temperature is a more important predictor of snow than is precipitation. © 2003, The Society of Agricultural Meteorology of Japan. All rights reserved.

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Inoue, S., & Yokoyama, K. (2003). Estimates of Snowfall Depth, Maximum Snow Depth, and Snow Pack Environments under Global Warming in Japan from Five Sets of Predicted Data. Journal of Agricultural Meteorology, 59(3), 227–236. https://doi.org/10.2480/agrmet.59.227

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