Global warming response of snowpack at mountain range in northern Japan estimated using multiple dynamically downscaled data

We estimate the response of snowpack to global warming along with the uncertainty of the snowpack change by using a combination of multiple general-circulation models (GCMs), a single regional atmospheric model, and a one-dimensional multi-layered snowpack model. The target site is Mt. Annupuri in Kutchan, Hokkaido, Japan. The forcing of the snowpack model is taken from dynamically downscaled data from GCMs for the present climate and GCMs in a decade when the global-mean temperature has increased by 2 K from present conditions. The results show that global warming would decrease the monthly-mean snow depth throughout the winter season. Other salient features are the decrease of snow depth by 60 cm with maximum uncertainty of 20 cm at the beginning of the snow ablation period, the occurrence of the snow-depth peak a month earlier, and the dominance of melt forms in an earlier season. The ratio of melt forms for all snowpack layers increases with little uncertainty before the snow ablation period. The ratio of hoar does not change much, even though the air temperature increases. The uncertainty in snowpack evaluation is also discussed. (C) 2017 Elsevier B.V. All rights reserved