Simulations of Monthly Variation in Snowfall over Complicated Mountainous Areas around Japan's Northern Alps

Abstract

We investigated the seasonal variation of snow cover at different altitudes using station data, satellite data, and a high-resolution numerical model around the Japan's Northern Alps during three winters (2011/12, 2012/13, and 2013/14). The satellite data showed that the snow cover fraction was largest in 2012/13 before late December, which indicates that much of snowfall occurs at higher elevations in the early winter. In midwinter, the snow cover fraction was over 90% in 2011/12, while it was approximately 70% and 60% in 2012/13 and 2013/14, respectively. The station data also showed the greatest snow depth at lower elevations in 2011/12 among the three winters. The numerical model well simulates the year-to-year and monthly variations of the snow cover fraction, although the threshold of snow depth are larger than that of the satellite data. The numerical simulations indicate that the total amount of snowfall is controlled by spring snowfall as much as by winter snowfall at higher elevations. The year-toyear variations of spring snowfall are relatively larger than those of winter snowfall, resulting in different year-to-year variations of snow cover at lower and higher elevations.

Changes in extremely heavy and light snow-cover winters due to global warming over high mountainous areas in central Japan

“…This means that the weakened winter monsoon reduces the precipitation over the coastal areas of the Sea of Japan and activates extratropical cyclones passing south of Japan, which brings precipitation over the coastal areas of the Pacific Ocean. The weakening of the winter monsoon due to global warming has been pointed out in previous studies (e.g., Hu et al 2000;Kimoto 2005;Hori and Ueda 2006;Kawase et al 2015). In addition, future changes in mid-winter storm tracks affect the winter precipitation in Japan.…”

“…In Japan's Northern Alps, at Murododaira ( Fig. 1d), whose altitude is 2450 m above sea level (mASL), the snow depth and snow water equivalent (SWE) are about 600 cm and 3000 mm, respectively, in early spring (Aoki and Watanabe 2009;Kawase et al 2015Kawase et al , 2018bKawase et al , 2019a. Enormous SWEs in the mountainous areas are available as water resources in the spring and early summer in Japan.…”

“…In Japan, some studies have indicated that the maximum snow depth and SWE would decrease due to global warming (Hara et al 2008;Yokoyama 1998, 2003;Kawase et al 2013Kawase et al , 2016. Additionally, an East Asian Winter Monsoon weakened due to global warming (Hori and Ueda 2006;Kawase et al 2015) decreases winter precipitation, including snowfall, on the Sea of Japan side. Katsuyama et al (2017) also showed that global warming would decrease the snow depth in Hokkaido, a northern part of Japan, throughout the winter season and discussed future changes in the seasonal variation of snowpack types, such as melt forms and depth hoar.…”

Simulation of Extremely Small Amounts of Snow Observed at High Elevations over the Japanese Northern Alps in the 2015/16 Winter

“…In this study, we investigate the extremely small amounts of snow observed at high elevations in the 2015/16 winter and interannual variations of snow cover from 2000/01 to 2015/16 in the Japanese Northern Alps. We use a regional climate model, which is useful tools for simulating the snow cover in mountainous areas (Hara et al 2008;Rasmussen et al 2011;Kawase et al 2015). The specifications of the numerical simulation and overviews of snow-cover observations are presented in Section 2.…”

Regional Snowfall Distributions in a Japan-Sea Side Area of Japan Associated with Jet Variability and Blocking

“…A detailed process connecting the large-scale circulation anomalies to individual snowfall events accompanied by a convective system: Here, we could not investigate the mesoscale fields associated with the large-scale circulations, since it was difficult to sufficiently investigate such small and short scale processes in the global reanalysis. Using radar and mesoscale analysis data and dynamical downscaling approaches using convection-permitting models may be promising (e.g., Nakai et al 2005;Kawase et al 2015;Kayaba et al 2016;Fukui et al 2018).…”