Kawase et al. Progress in Earth and Planetary Science
https://doi.org/10.1186/s40645-020-0322-x(2020) 7:10

RESEARCH ARTICLE

Progress in Earth andPlanetary Science

Open Access

Changes in extremely heavy and lightsnow-cover winters due to global warming
over high mountainous areas in central
Japan
Hiroaki Kawase1* , Takeshi Yamazaki2, Shiori Sugimoto3, Takahiro Sasai2, Rui Ito4, Takashi Hamada5,
Masatoshi Kuribayashi5, Mikiko Fujita3, Akihiko Murata1, Masaya Nosaka1 and Hidetaka Sasaki1

Abstract
To investigate future changes in snow cover and snowfall over mountainous areas in central Japan, we conductedregional climate projections using a high-resolution non-hydrostatic regional climate model (NHRCM) with 5 km
and 1 km grid spacings. Boundary conditions are derived from the database for Policy Decision making for Futureclimate change (d4PDF) 20 km regional climate projections (d4PDF20). The d4PDF20 assumes two future climateswhen global mean surface air temperatures are approximately 2 K and 4 K warmer than in the preindustrial period.
Experiments with 5 km grid spacing are conducted by NHRCM for 372 years in d4PDF20 in each climate.
Experiments with 1 km grid spacing are performed focusing on 5 years with heavy, median, and light snow coverof mountainous areas in each climate. In the years with heavy snow cover in 2 K and 4 K warming climates,
snowfall is enhanced from late December to February at more than 2000 m above sea level (mASL) in the northernparts of Japan’s Northern Alps, resulting in heavy snow cover comparable to that in the present climate. Heavy daily
snowfall remarkably increases due to global warming in the years with heavy snow cover. At low elevations below
500 mASL, snowfall decreases in all ranges of snowfall intensity in the 4 K warming climate, while the frequency ofheavy daily snowfall increases in the 2 K warming climate. Precipitation is enhanced around the Japan-Sea Polarairmass Convergence Zone and the mountainous area facing the Sea of Japan, resulting in strengthened heavy
snowfall at high elevations where the winter mean temperature is approximately − 10 °C in the present climate. On
the other hand, remarkable reductions in snow cover and snowfall are projected in years with light snow cover.
Our results indicate that global warming causes heavy and light mid-winter snowfalls at high elevations of Japan’s
Northern Alps that are more extreme than those in the present climate.
Keywords: Mountainous snow cover, Heavy snowfall, Regional climate modeling, Global warming, Dynamical
downscaling, Japan’s Northern Alps

Introduction
Japan’s Northern Alps, located in central Japan, are
known as one of the deepest snow-cover regions in theworld (Fig. 1). The cold and dry northwesterly from theEurasian continent, called the East Asian Winter Monsoon, obtains plenty of moisture from the relatively
warm Sea of Japan, causing snowfall over the Sea of* Correspondence: hkawase@mri-jma.go.jp
1
Meteorological Research Institute, Japan Meteorological Agency, 1-1
Nagamine, Tsukuba 305-0052, Japan
Full list of author information is available at the end of the article

Japan’s coast. Additionally, the topographic updraft enhances the snowfall over Japan’s Northern Alps facing
the Sea of 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, inearly spring (Aoki and Watanabe 2009; Kawase et al.
2015, 2018b, 2019a). Enormous SWEs in the mountainous areas are available as water resources in the springand early summer in Japan.

© The Author(s). 2020 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made.

Kawase et al. Progress in Earth and Planetary Science(2020) 7:10

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Fig. 1 Model domains and topography. a NHRCM20 (d4PDF 20 km), b NHRCM05, and c NHRCM01. The annual maximum snow depth in central
Japan is represented by the area enclosed by a red line, 35N–37N and 136.5E–139E. The area enclosed by blue lines is our target region, thenorthern parts of Japan’s Northern Alps (NN-Alps). d Detailed topography in the NN-Alps and the location of Murododaira (white cross symbol). A
contour interval is 500 m. e Names and locations of three Japanese Alps mountain ranges. A yellow star indicates the location of Murododaira

Since the late 1980s, snow cover has been decreasingover the Japanese archipelago, especially in the central
and western parts of Japan. Rapid warming changes
snowfall to rainfall, resulting in a decrease in snow coverat low elevations (Ishizaka 2004; Suzuki 2006; Ishii and
Suzuki 2011; Kawase et al. 2012). On the other hand,such reductions in snow cover are not observed in highmountainous areas where the annual variation of snow
cover correlates with that of total precipitation (Suzuki
2006; Matsuura et al. 2005; Ishii and Suzuki 2011).
Yamaguchi et al. (2011) pointed out that snow cover issensitive to air temperature at low elevations, while it isinfluenced by precipitation rather than air temperature
at high elevations. Kawase et al. (2018b) simulated annual variations of snow depth around Japan’s Northern
Alps and showed that annual variations of snow coverdepend on elevation.
Global climate models project that snow cover will
decrease due to global warming in most parts of theworld, while snow cover could increase in very cold regions where the winter mean temperature is lower than
− 20 °C in the present climate (Raisanen 2007; Brown

and Mote 2009). Basically, global climate models cannot
resolve complex terrain because of the horizontal resolutions (~ 150 km). Snow-cover distributions in mountainous areas are, however, strongly influenced by complex
terrain. Dynamical downscaling using a regional climate
model (RCM) is a useful method of reproducing andprojecting snow cover in mountainous areas. For instance, an RCM with a horizontal grid spacing of lessthan 2 km is required to calculate snow cover over the
Rocky Mountains (Ikeda et al. 2010; Rasmussen et al.
2011; Gutmann et al. 2012). Rasmussen et al. (2011)
conducted pseudo-global warming downscaling (Kimura
and Kitoh 2007) and evaluated future changes in snow
cover over the Rocky Mountains using the Weather Research and Forecasting (WRF) model. They indicatedthat global warming enhanced melting at lower elevations and increased snowfall at higher elevations. Rasmussen et al. (2014) indicated that snowpack did notchange until January over the Colorado Headwaters in
the future climate, while, above 3000 mASL, snowpack
increased from January to March and decreased after
April. On the other hand, an enhancement of heavy

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snowfall has been projected around the Great Lakes because the lake ice would melt due to global warming,and much water vapor could evaporate from the lakes(Gula and Peltier 2012; Notaro et al. 2015). Steger et al.
(2012) pointed out that, over the European Alps, theSWE would largely decrease at the lower elevations,while the changes in the SWE were small at the higher
elevations. These changes are consistent with the snow
cover changes in the Colorado Headwaters (Rasmussen
et al. 2011, 2014). Steger et al. (2012) also stated that
future changes in snow cover over the European Alps
had inter-model variability.
In Japan, some studies have indicated that the maximum snow depth and SWE would decrease due to global warming (Hara et al. 2008; Inoue and Yokoyama
1998, 2003; Kawase et al. 2013, 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 showedthat global warming would decrease the snow depth in
Hokkaido, a northern part of Japan, throughout the winter season and discussed future changes in the seasonalvariation of snowpack types, such as melt forms anddepth hoar. Kawase et al. (2016) analyzed the databasefor Policy Decision making for Future climate change(hereafter referred to as d4PDF) (Mizuta et al. 2017) andpointed out that extremely heavy daily snowfall could increase in inland areas over the Sea of Japan side in central Japan due to global warming. They stated thatenhancements of the Japan-Sea Polar-airmass Convergence Zone (hereafter referred to as the JPCZ) and topographic updraft brought about heavier snowfall overinland areas where the air temperature will still be lower
than 0 °C in the future climate.
The d4PDF, which contains a global climate simulation with about 60 km grid spacing and a regional
climate simulation with 20 km grid spacing (hereafterreferred to as d4PDF20), is a useful dataset for evaluating the impact of global warming on extreme events,
such as heat waves (Imada et al. 2019), heavy rainfalls(Kawase et al. 2019b; Ohba and Sugimoto 2019), andheavy snowfalls (Kawase et al. 2016). However, d4PDF20
has insufficient grid spacing to resolve the complex
mountains of Japan. Kawase et al. (2018a) conducted dynamical downscaling from several ensemble experimentsin the d4PDF20 in the present climate using the nonhydrostatic regional climate model (NHRCM) (Sasaki
et al. 2008) with 5 km grid spacing (hereafter referred toas the 5km_HIST experiment). Based on the 5km_HIST
experiment, they clarified that the geographical boundaries of extremely heavy snowfall events caused by two
typical patterns—a cold air outbreak and an extratropical
cyclone—are more clearly defined than those of othersnowfall events. As with Kawase et al. (2018a), Sasai
et al. (2019) conducted dynamical downscaling fromd4PDF20 in two future climates, assuming that the global mean temperatures are 2 K and 4 K warmer thanthose in the pre-industrial period (Mizuta et al. 2017;
Fujita et al. 2019) (hereafter referred to as the 5km_2K
and 5km_4K experiments, respectively). For 5km_2K
and 5km_4K experiments, they selected two ensemble
members from each sea surface temperature (SST) pattern in d4PDF, which has six SST patterns, and conducted a 31-year simulation for each ensemble member.
Then, a 372-year simulation was obtained in each futureclimate as with the present climate (Kawase et al.
2018a).
Over Japan’s Northern Alps, the snow depth is, however, overestimated by the NHRCM with 5 km grid spacing (hereafter referred to as NHRCM05), especiallyaround 1000–2000 mASL, as compared with snow observations and the NHRCM with 2 km grid spacing(hereafter referred to as NHRCM02) (Kawase et al.
2019a). NHRCM05 cannot resolve small-scale convective precipitation over the Sea of Japan, which results inthe overestimation of snow depth on the windward sideof Japan’s Northern Alps. Therefore, at least 2 km grid
spacing is required to accurately simulate and project
the snow cover over the complex mountains of central
Japan, such as Japan’s Northern Alps.
Most previous studies focus on the climatologicalchanges in snow cover due to global warming (Haraet al. 2008; Inoue and Yokoyama 2003; Kawase et al.
2016), and the horizontal resolution of the regional
climate model is coarser than 5 km, which is not highenough to simulate winter precipitation in the mountainous areas of central Japan, as pointed out by Kawase
et al. (2019a). The purpose of this study is to evaluate
the impact of global warming on snowfall and snow
cover in the high mountainous areas of central Japan in
extremely heavy and light snow-cover years using the
NHRCM with 1 km grid spacing (hereafter referred toas NHRCM01).

Kawase et al. Progress in Earth and Planetary Science

Methods/Experimental
Experimental designs

Regional mean maximum snow depths are calculated in
the mountainous areas of central Japan, where the altitude is higher than 1000 mASL (red frame in Fig. 1b) in
the 5km_HIST, 5km_2K, and 5km_4K experiments. Fiveyears of heaviest, median, and lightest snow cover (hereafter referred to as heavy snow-cover years, mediansnow-cover years, and light snow-cover years, respectively) are selected from each climate (Table 1). Focusing
on three types of winter, dynamical downscaling is conducted by using the NHRCM with 1 km grid spacing(hereafter referred to as NHRM01) from the 5km_HIST,Kawase et al. Progress in Earth and Planetary Science(2020) 7:10

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Table 1 Selected ensemble members and the regional mean annual maximum snow depth
Historical (HPB)

Year

Snow depth (cm)

2 K warming (HFB_2K)

Year

Snow depth (cm)

4 K warming (HFB_4K)

Year

Snow depth (cm)

2095

52.4

Light snow-cover year
m004

2009

118.8

CC_m105

2061

92.8

CC_m101

m004

2000

131.3

CC_m105

2084

92.9

HA_m105

2081

54.6

m022

2004

132.7

MP_m105

2086

94.6

GF_m105

2081

58.3

m005

2010

138.2

CC_m105

2080

95.6

CC_m101

2101

64.9

m002

1995

143.0

MP_m105

2061

104.8

MI_m101

2087

69.7

2097

137.6

Median snow-cover year
m002

1984

209.7

MP_m105

2063

171.5

MR_m101

m008

2006

209.8

HA_m105

2069

171.8

CC_m105

2107

137.8

m010

2000

209.8

HA_m105

2077

172.2

MI_m101

2097

138.2

m021

1981

210.0

MI_m101

2064

172.3

HA_m101

2084

139.0

m022

1985

210.4

GF_m101

2064

172.5

GF_m101

2106

139.0

Heavy snow-cover year
m004

1992

285.3

GF_m105

2069

259.1

GF_m101

2108

219.6

m009

1982

296.3

GF_m101

2070

259.7

MP_m101

2103

223.5

m004

2010

298.9

CC_m101

2072

274.4

MI_m105

2096

231.4

m008

1989

300.6

MI_m105

2076

275.0

GF_m101

2091

231.5

m004

1981

317.1

GF_m101

2076

285.4

GF_m101

2100

243.8

5km_2K, and 5km_4K experiments, which are referred
to as the 1km_HIST, 1km_2K, and 1km_4K experiments, respectively. The experimental designs are summarized in Table 2.
Figure 1a–c shows the model domains and topography resolved by NHRCM20, NHRCM05, andNHRCM01, respectively. NHRCM01 resolves complex
mountains in central Japan (Fig. 1c, d). Numerical experiments were conducted from August 20 to August
29 in the following year to simulate the annual snow
cover of central Japan’s high elevations. The precipitation process was calculated only by a microphysics
scheme (Ikawa et al. 1991) in NHRCM01, while
NHRCM05 used both the microphysics scheme andKain-Fritsch cumulus convective parameterization(Kain and Fritsch 1993). The atmospheric boundary
layer process was calculated by the improved MellorYamada-Nakanishi-Niino (MYNN) level 3 (Nakanishiand Niino 2004). The land-surface process was calculated by the improved MRI/JMA Simple Biosphere(iSiB), which was updated from that used by Hirai andOh’izumi (2004). An urban canopy model (Aoyagi and
Seino 2011; Ito et al. 2018) was used in NHRCM01, aswith NHRCM05. The other physical parameterizations
and the experimental design in NHRCM01 are summarized in Tables 3 and 4, respectively.

Results and discussion
Mean maximum snow cover in the 2 K and 4 K warming
climatesFigure 2a and b shows horizontal distributions of 15year mean annual maximum snow cover, which consists of five light, five median, and five heavy snowcover years, simulated by the 5km_HIST and 1km_
HIST experiments, respectively. Snow cover simulatedby the 5km_HIST experiment exceeds 900 cm overTable 2 Experimental design
Experimental nameClimateTotal year

Detailed description

5km_HIST

Present climate372

31 years and 12 ensemble experiments

5km_2K

Future climate (+2 K)

372

31 years and 2 ensemble experiments in 6 SST patterns

5km_4K

Future climate (+4 K)

372

1km_HIST

Present climate

15

1km_2K

Future climate (+ 2K)

15

1km_4K

Future climate (+4 K)

15

5 heaviest snow years in 372 years
5 median snow years in 372 years
5 lightest snow years in 372 yearsKawase et al. Progress in Earth and Planetary Science(2020) 7:10

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Table 3 Specifications of the NHRCM01
Specification

DetailNumerical model

Non-hydrostatic Regional Climate Model (Sasaki et al. 2008)

Horizontal resolution

1 km

Boundary condition

d4PDF05 (Kawase et al. 2018a; Sasai et al. 2019)

Nesting

One-way nesting

Nudging

Spectral nudging (Nakano et al. 2012)

Initial dateAugust 20

the northern side of Japan’s Northern Alps facing the
Sea of Japan (Fig. 2a). On the other hand, the 1km_
HIST experiment simulates snow cover of 700 cm
over the high elevations above 2000 mASL at thenorthern part of Japan’s Northern Alps, which is consistent with the snow-cover survey at Murododaira inJapan’s Northern Alps (Aoki and Watanabe 2009;
Kawase et al. 2019a). NHRCM01 can resolve a steep
valley, called the Kurobe Gorge. Deep snow-coverareas are limited over the high mountainous areas.
The overestimation of snow cover in the 5km_HIST
experiment is caused by the envelope-type highmountains (Kawase et al. 2018a) and a lack of horizontal resolution for calculating the small-scale convections over the Sea of Japan (Kawase et al. 2019a).
Figure 2c–f shows future changes in the 15-year meanannual maximum snow cover projected by the 1km_2K
and 1km_4K experiments. Both simulations indicate thatthe annual maximum snow cover will decrease due toglobal warming over whole areas. The 1km_4K experiment projects more than a 150 cm decrease in the maximum snow cover above 1000 mASL in Japan’s
Northern Alps (Fig. 2d). The decrease in snow cover islarger at high elevations than at low elevations (Fig. 2c,d), while the decreasing ratio is larger at low elevations
than at high elevations (Fig. 2e, f), which is consistent
with the findings of previous studies (Hara et al. 2008;
Kawase et al. 2013). Here, we focus on the northern partof Japan’s Northern Alps (hereafter, NN-Alps; the blue
rectangle in Fig. 1c), where the complex topography iswell resolved by the NHRCM01 (Fig. 1d), and the enormous snow cover is calculated in our model domain.

We individually analyze the snow cover changes in three
types of winter.
Seasonal variations of snow cover and snowfall

Seasonal variations of snow cover in the 1km_HIST
experiment are different among three types of winterat elevations above 2000 mASL of the NN-Alps (Fig.
3a). In heavy snow-cover years, peak snow cover appears in late March to early April, and snow coverdecreases after mid-April. On the other hand, peaksnow cover appears in mid-March and late February
in median and light snow-cover years, respectively.
The seasonal variation of snow cover in light snowcover years shows a gentle slope as compared withthe others.
Figure 3b–d shows future changes in seasonal variations of snow cover above 2000 mASL of the NN-Alps.
In heavy snow-cover years, the seasonal variation in the
1km_2K experiment is similar to that in the 1km_HIST
experiment from December to mid-March (Fig. 3b).
After late March, the snow cover gradually decreases in
the 1km_2K experiment, which is approximately half amonth earlier than in the 1km_HIST experiment. From
October to January, snow cover in the 1km_4K experiment is much smaller than that in the 1km_HIST experiment, while the differences become smaller as winterprogresses. In mid-February, the 5-year mean snow
cover in the 1km_4K experiment is comparable to thatin the 1km_HIST experiment. After mid-February, the
1km_4K experiment shows a long continuous peak ofsnow cover until early April. Snow cover rapidly decreases after mid-April, as with the 1km_HIST and

Table 4 Physical processes in the NHRCM01
Process

Physical parameterization

Microphysics

Bulk-type cloud microphysics (Ikawa et al. 1991)

Radiation process

Clear-sky radiation scheme (Yabu et al. 2005)
Cloud radiation scheme (Kitagawa 2000)

Boundary-layer process

Improved Mellor-Yamada-Nakanishi-Niino (MYNN) Level 3(Nakanishi and Niino 2004)

Land-surface process

Improved MRI/JMA Simple Biosphere (iSiB) (Hirai and Oh’izumi 2004)

Urban model

Square Prism Urban Canopy Scheme (SPUC) with snow cover process(Aoyagi and Seino 2011; Ito et al. 2018)

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Fig. 2 Horizontal distribution of the 15-year mean annual maximum snow depth and changes due to global warming. Fifteen-year mean
maximum snow depth simulated by a 5km_HIST and b 1km_HIST experiments. Differences in maximum snow depths between c 1km_2K and
1km_HIST experiments and d 1km_4K and 1km_HIST experiments. Contours represent elevations. The contour interval is 500 m, and the thickcontour interval is 1000 m

1km_2K experiments, and snow cover disappears in lateJuly. The shapes of the seasonal variations in the 1km_
HIST, 1km_2K, and 1km_4K experiments are different.
In median snow-cover years, snow covers simulated by
the 1km_2K and 1km_4K experiments are less than thatsimulated by the 1km_HIST experiment, except in December (Fig. 3b). The half-monthly snowfalls in the

1km_2K and 1km_4K experiments are comparable to or
larger than the snowfall in the 1km_HIST experimentfrom December to January (figure not shown), resulting
in similar snow depths among the three climates. As
compared with the heavy snow-cover years, the 1km_2K
experiment is similar to the 1km_4K experiment. In thelight snow-cover years, the snow cover in the 1km_4K

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Fig. 3 Seasonal variation of snow depth in the NN-Alps. a Snow depth in the 1km_HIST experiment. Heavy (blue), median (green), and lightsnow-cover years (brown) in the 1km_HIST experiment. b Heavy, c median, and d light snow-cover years in the 1km_HIST, 1km_2K, and 1km_4K
experiments. Blue, green, and red lines represent 1km_HIST, 1km_2K, and 1km_4K experiments, respectively. Thin lines represent individual
simulations, and thick lines represent the 5-year mean in each condition

experiment is much less than that in the 1km_HIST experiment for the entire duration of snow cover, except
for December of one year (Fig. 3d). The 5-year mean
maximum snow depth is approximately 100 cm in the
1km_4K experiment, which is about one-third of the
maximum snow depth in the 1km_HIST experiment.
The snow cover disappears by mid-May in the 1km_4K
experiment, which is approximately 2 months earlier
than that in the 1km_HIST experiment. Therefore, theimpact of global warming on the seasonal variation ofsnow cover depends on the type of winter. Snow coveris clearly reduced in the light snow-cover years as compared to that of heavy snow-cover years. This indicates
that, with the progress of global warming, the amplitudeof the interannual variation in mid-winter snow cover
would become larger than that in the present climate.
On the other hand, global warming reduces the snow
cover during snow-melting periods in both heavy andlight snow-cover years. Note that selected 5-year simulations are conducted for each type of winter.
Figure 4 shows the time sequences of half-monthly
accumulated snowfall, rainfall, and precipitation simulated by the 1km_HIST, 1km_2K, and 1km_4K experiments, respectively, in heavy and light snowcover years. From October to November, the 1km_

HIST experiment simulates the largest amounts ofsnowfall in both heavy and light snow-cover years.
In heavy snow-cover years, it is noteworthy that,among the three experiments, the 1km_4K experiment calculates the largest snowfall from the latter
half of December to the first half of February. The
amount of snowfall in the 1km_2K experiment also
exceeds that in the 1km_HIST experiment fromJanuary to February. In heavy snow-cover years, global warming can bring more snowfall in mid-winterthan in the present climate, resulting in plenty ofsnow cover comparable to that of the present climate in February (Fig. 3b). In light snow-cover years,
snowfall considerably decreases in the 1km_4K experiment during the entire cold season (Fig. 4b).
From the latter half of January to March, the 1km_
2K experiment simulates larger snowfalls than does
the 1km_HIST experiment.
In heavy snow-cover years, all simulations show little
rainfall in winter (December to February: DJF), while the
1km_4K experiment simulates increased rainfall inautumn and spring (Fig. 4c). In light snow-cover years,
the 1km_2K and 1km_4K experiments show increased
rainfall during mid-winter (Fig. 4d). The amount of halfmonthly rainfall is above 50 mm from January toKawase et al. Progress in Earth and Planetary Science(2020) 7:10

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Fig. 4 Seasonal variations in snowfall, rainfall, and precipitation above 2000 mASL of the NN-Alps. Snowfall includes graupel, and precipitation is
the sum of snowfall and rainfall. a Snowfall in heavy snow-cover years, b snowfall in light snow-cover years, c rainfall in heavy snow-cover years,
d rainfall in light snow-cover years, e precipitation in heavy snow-cover years, and f precipitation in light snow-cover years. Blue, green, and red
represent the 1km_HIST, 1km_2K, and 1km_4K experiments, respectively. Thin lines represent individual simulations, and bars represent five-year
averages in each climate condition

February in the 1km_4K experiment. The total precipitation shows changes similar to those of the snowfall inheavy snow-cover years (Fig. 4e), indicating that the increased precipitation during mid-winter results inincreased snowfall above 2000 mASL of the NN-Alps.
Heavy and light snow-cover years also show an increase
in total precipitation in January and February (Fig. 4f).
However, snowfall decreases in light snow-cover years
since rainfall increases due to warming (Fig. 4d).

Seasonal variations of snowfall at high and middle
elevations

Snowfall over Japan’s Northern Alps is strongly influenced by the air temperature and SST of the Sea ofJapan. Figures 5 and 6 show the seasonal variations of
the daily mean SST, surface air temperature, and halfmonthly accumulated snowfall, which are the same as inFig. 4a, b, over 2000 mASL and 1000 to 1500 mASL of
the NN-Alps. Here, the SST is regionally averaged over

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Fig. 5 Seasonal progress of surface air temperature, SST, half-monthly snowfall, and accumulated snowfall above 2000 mASL. a, b SST, surface airtemperature, and half-monthly snowfall, c, d accumulated snowfall, a, c heavy snow-cover years, and b, d light snow-cover years. The SST isregionally averaged over the Sea of Japan in the NHRCM01 domain (Fig. 1c). Blue, green, and red represent the 1km_HIST, 1km_2K, and 1km_4K
experiments, respectively. Thin lines represent individual simulations. Thick lines and bars represent five-year averages in each climate condition

the Sea of Japan in the NHRCM01 domain (Fig. 1c).
Above 2000 mASL of the NN-Alps, the 5-year meansurface air temperature is lower than − 10 °C from midDecember to mid-March in the 1km_HIST experiment(Fig. 5a). In the 1km_4K experiment during the same

Fig. 6 Same as Fig. 5 but at elevations from 1000 to1500 mASL

term, the surface air temperature is still lower than − 5°C, which is cold enough to snow. No year shows positive surface air temperature from December to midFebruary. The SST in the 1km_4K experiment exceeds
15 °C from December to January, which is approximately

Kawase et al. Progress in Earth and Planetary Science(2020) 7:10

5 °C higher than that in 1km_HIST. The warmer SST
results in more moisture evaporating from the Sea ofJapan and larger amounts of snowfall below freezing
temperatures. Note that SSTs are given in our simulation. SSTs are not influenced by short-term variations inatmospheric conditions. On the other hand, the meansurface air temperature is between 0 and − 5 °C in the
1km_4K experiment, and some years occasionally exceed
0 °C above 2000 mASL of the NN-Alps in mid-winter inlight snow-cover years (Fig. 5b), which causes rainfall
even in mid-winter (Fig. 4d). We will discuss the influence of the basic air temperature on the total snowfall ineach type of winter in a later section. Daily variations of
the surface air temperature are larger in light snowcover years than those in heavy snow-cover years, which
implies that extra-tropical cyclones pass more frequently
in light snow-cover years. Warm and cold air advections
occur before and after the passing of the extratropical
cyclone, respectively.
At 1000–1500 mASL of the NN-Alps, snowfall dramatically decreases in the 1km_4K experiment from
November to the first half of December, when thesurface air temperature exceeds 0 °C, in heavy snowcover years (Fig. 6a). The snowfall in the 1km_4K
experiment is comparable to or larger than that in
the 1km_HIST experiment from the latter half of December to the first half of March. In light snow-coveryears, the surface air temperature in the 1km_HIST
and 1km_2K experiments is lower than 0 °C from December to February, while the surface air temperature
frequently exceeds 0 °C in the 1km_4K experiment,
and snowfall decreases through most of the winter(Fig. 6b). As with elevations above 2000 mASL in the
NN-Alps, the daily variation of the surface airtemperature in light snow-cover years is larger thanthat in heavy snow-cover years.
Accumulated snowfalls from October to August are
shown in Figs. 5c, d and 6c, d. In heavy snow-coveryears, the accumulated snowfalls in three climates arecomparable from mid-February to mid-March (Fig. 5c),which results from considerable amounts of snowfallfrom late December to February (Fig. 4a). The differences in accumulated snowfall become larger after midMarch. In light snow-cover years, there is a large difference among the three climates, although there is a large
5-year variation in the 1km_4K experiment (Fig. 5d).
Above 1000–1500 mASL of the NN-Alps, the accumulated snowfalls in the 1km_2K and 1km_4K experiments
are lower than that in the 1km_HIST experiment, although some years overlap between the 1km_HIST and
1km_2K experiments (Fig. 6c). In light snow-cover years,
the seasonal variations of accumulated snowfall are different among the three periods (Fig. 6d), which are similar to those above 2000 mASL of the NN-Alps (Fig. 5d).

Page 10 of 17

Changes in daily snowfall intensity

Kawase et al. (2016) pointed out an enhancement of
the extremely heavy daily snowfall, occurring once
every 10 years, in inland areas over the Sea of Japanside of central Japan due to global warming. Figure 7
shows relative frequencies of daily snowfall intensity
over three elevations, i.e., above 2000 mASL, 1000–
1500 mASL, and 0–500 mASL of the NN-Alps. Here,the daily snowfall is accumulated by the increment of
the hourly snow depth, which is consistent with thedefinition of the Japan Meteorological Agency. Above
2000 mASL, the number of non-snowfall days increases,
and the number of weak daily snowfalls decreases due
to global warming (Fig. 7a). Daily snowfall—more
than 30 cm/day—occurs more frequently in the 1km_
2K and 1km_4K experiments than in the 1km_HIST
experiment. Extremely heavy daily snowfall—more
than 80 cm/day—remarkably increases in the 1km_4K
experiment. These results indicate that global warming enhances heavy daily snowfall and causes heavy
daily snowfall not previously experienced above 2000
mASL in heavy snow-cover years. In light snow-coveryears (Fig. 7b), the number of non-snowfall days increases, and the relative frequency decreases for mostsnowfall intensities. However, the frequency of heavy
daily snowfalls—more than 60 cm/day—increases bothin the 1km_2K and 1km_4K experiments, even inlight snow-cover years.
Changes in the daily snowfall intensity above 1000–
1500 mASL in heavy snow-cover years (Fig. 7c) are similar to those above 2000 mASL (Fig. 7a), while thefrequency of daily snowfall increases over 50 cm/day due
to global warming. In the 1km_4K experiment, extremely heavy snowfall occurs most frequently above
1000–1500 mASL, as with above 2000 mASL. In lightsnow-cover years, the daily snowfall frequency decreases
in most ranges of snowfall intensity. Extremely heavy
snowfall—more than 80 cm/day—however, occurs mostfrequently in 1km_2K.
Low elevations—below 500 mASL—show differentchanges in the frequency of daily snowfall intensity ascompared with high elevations (Fig. 7e–f). In heavysnow-cover years, it is noteworthy that the 1km_2K experiment shows an increase in heavy snowfall—more
than 40 cm/day—(Fig. 6e) while the daily snowfall frequency decreases in all ranges of snowfall intensity in
1km_4K. In light snow-cover years, daily snowfall frequency dramatically decreases at 0–500 mASL of the
NN-Alps due to global warming (Fig. 6f). Note thatthree types of winter are defined using the annual maximum snow depth in central Japan exceeding 1000
mASL. In the next subsection, we will discuss changes in
the winter total precipitation at each elevation aroundthe NN-Alps in each type of winter.

Kawase et al. Progress in Earth and Planetary Science(2020) 7:10

Page 11 of 17

Fig. 7 Relative frequency of daily snowfall intensity. a, b Over 2000 mASL, c, d 1000–1500 mASL, and e, f 0–500 mASL; a, d, e heavy snow-coveryears and b, d, f light snow-cover years. Blue, green, and red bars represent the 1km_HIST, 1km_2K, and 1km_4K experiments, respectively

Relationship between mean air temperature and total
precipitation during each winterTakeuchi et al. (2008) investigated the relationship between the winter mean air temperature and precipitationin heavy-snowfall areas of Japan and identified a highnegative correlation between the winter mean air
temperature and precipitation, i.e., there was more precipitation with lower temperatures. As with Takeuchi
et al. (2008), we investigated the relationship between
the winter mean air temperature (hereafter referred to as
the winter temperature) and the winter total precipitation (hereafter referred to as the winter precipitation)using our simulation results. Here, the winter is from
December to February (DJF). Our experiments with 1
km grid spacing, however, include only 5 years of eachtype of winter and in each climate. Here, we focus onchanges in the relationships with the progress of global
warming in each type of winter (Fig. 8).
At all elevations, the winter temperature is lowest andhighest in heavy and light snow-cover years, respectively(Figs. 8a–c). The winter temperature in heavy snow-coveryears exceeds 0 °C below 500 m in the 1km_HIST experiment and below 1000 m in the 1km_4K experiment. The
winter temperature is around 5 °C and 10 °C below 500 m
in the 1km_HIST and 1km_4K experiments, respectively,in light snow-cover years. The winter temperature exceeds
0 °C at elevations between 500 and 1000 mASL in 1km_
2K and even at elevations between 1000 and 1500 mASL
in 1km_4K (Fig. 8c). The basic winter temperature is different among high, median, and light snow-cover years.
In heavy snow-cover years, winter precipitation clearly
increases with elevation (Fig. 8a), which is consistentKawase et al. Progress in Earth and Planetary Science(2020) 7:10

Page 12 of 17

Fig. 8 Relationships between winter temperature and precipitation and between winter temperature and snowfall. a–c Relationships between
winter temperature and precipitation, d–f relationships between winter temperature and snowfall. a, d Heavy snow-cover years, b, e mediansnow-cover years, and c, f light snow-cover years. Filled circles represent the five-year means. Here, snowfall represents the water equivalent(mm) of solid precipitation, i.e., snowfall and graupel in NHRCM01

with the findings of previous studies (e.g., Uno et al.
2014; Asaoka and Kominami 2013). Winter precipitation
will increase with the progress of global warming at allelevations. In median snow-cover years, winter precipitation increases with elevation, while the increase ratio issmaller than that in heavy snow-cover years (Fig. 8b).
The relationship between winter temperature and precipitation in light snow-cover years differs from those inheavy and median snow-cover years (Fig. 8c). The elevation dependency of winter precipitation is not clear, andglobal warming does not necessarily enhance winter precipitation in light snow-cover years.
Winter snowfall has a strong negative correlation
with the winter mean temperature in all types of winter (Fig. 8d–f). On the other hand, the impacts ofglobal warming on winter snowfall depend on the elevation and the type of winter. In heavy snow-coveryears, snowfall decreases with the progress of global
warming at low elevations below 500 mASL, where
the winter temperature is 2–3 °C in the present climate(Fig. 8d). Winter snowfall totals do not change at middle

elevations—around 500–1500 mASL—where the wintertemperature is from − 7 to − 2 °C in the present climate,in spite of global warming. At elevations above 1500
mASL, where winter temperatures are below − 7 °C in
the present climate, winter snowfall obviously increases
due to global warming. In median snow-cover years,
winter snowfall decreases due to global warming below
1000 mASL (Fig. 8e). The decrease in snowfall is unclear at elevations higher than 1500 mASL. In lightsnow-cover years, winter snowfall decreases due toglobal warming not only at low elevations but also athigh elevations (Fig. 8f). At elevations above 2000
mASL, winter precipitation in the 1km_4K experimentis comparable to that in the present climate, resulting
in a reduction of snowfall, although the wintertemperature is still around − 5 °C. Figure 8 indicatesthat future changes in snowfall depend on not onlychanges in winter temperatures but also changes in winterprecipitation, which is strongly influenced by the type of
winter. This result is a new finding as compared withthose of previous studies.

Kawase et al. Progress in Earth and Planetary Science(2020) 7:10

Characteristics of synoptic-scale atmospheric conditions

Future changes in snow cover and snowfall are caused
by not only atmospheric warming and moistening, i.e., athermo-dynamical effect, but also atmospheric circulation changes, i.e., a dynamical effect. Composite analyses
are conducted by using d4PDF05 to discuss low-level atmospheric circulation changes and corresponding precipitation changes around Japan.
Figure 9a–c shows the DJF mean surface wind and sea
level pressure (SLP) over the ocean and the DJF total
water equivalent of falling snow and graupel over the Japanese archipelago in the 5km_HIST experiment. The typical SLP pattern in winter, i.e., higher pressure over west
Japan and lower pressure over east Japan, appears, and thenorthwesterly prevails around Japan irrespective of thesnow cover. The largest pressure gradient and strongest
northwesterly in heavy snow-cover years reflect a strongor continuous cold surge during the winter (Fig. 9a). The
smallest pressure gradient indicates that a weak northwesterly prevails in light snow-cover years (Fig. 9c).
Figure 10 shows differences in the surface wind over
the ocean and precipitation between the 5km_HISTPage 13 of 17

and 5km_2K experiments, and between the 5km_HIST
and 5km_4K experiments. In heavy snow-cover years,
the 5km_2K experiment simulates the increase in precipitation over the Sea of Japan’s coast in eastern Japan(Fig. 10a). The northwesterly wind anomaly prevails
over the northern part of the Sea of Japan. In mediansnow-cover years, on the other hand, precipitation decreases over the Sea of Japan’s coast, and a southeasterly wind anomaly prevails around Japan (Fig. 9b).
Precipitation increases over the coastal areas of the Pacific Ocean side and to the south of Japan. This meansthat 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 andUeda 2006; Kawase et al. 2015). In addition, futurechanges in mid-winter storm tracks affect the winterprecipitation in Japan. Inatsu and Kimoto (2005) examined the response of global warming to mid-winterFig. 9 Composite of DJF mean surface winds and SLP, and DJF total snowfall and precipitation simulated by the 5km_HIST experiment. a–c
Surface wind, SLP, and snowfall over land; d–e surface wind and precipitation; a, d heavy snow-cover years; b, e median snow-cover years; and c,
f light snow-cover years. Vectors and contours represent surface wind and SLP, respectively. Shadings represent a–c snowfall andd–f precipitation

Kawase et al. Progress in Earth and Planetary Science(2020) 7:10

Page 14 of 17

Fig. 10 Differences in DJF mean surface wind and DJF total precipitation. Differences a–c between the 5km_HIST and 5km_2K experiments andd, e between the 5km_HIST and 5km_4K experiments; a, d heavy snow-cover years, b, e median snow-cover years, and c, f light snow-coveryears. Vectors and shadings represent surface wind and precipitation, respectively. Hatched areas represent significant changes in precipitation at
the 95% confidence interval, according to the Mann-Whitney U test. Contours represent elevations. The contour interval is 1000 m

storm tracks using a high-resolution atmospheric general circulation model and pointed out that global
warming could make the storm tracks stronger in thewestern Pacific. Analyzing the reanalysis data from1979/80 to 2010/11, Iwao et al. (2012) indicated thatthe frequency of explosively developing extratropical
cyclones that originated southwest of Japan and passed
south of Japan has been increasing east of Japan.
Changes in the atmospheric circulation during mediansnow-cover years represent climatological changes in
winter due to global warming. Over the mountainous
areas of central Japan, the increase in precipitation due
to activated extratropical cyclones is canceled out by
the decrease in precipitation due to the weakened East
Asian Winter Monsoon (Fig. 10b). In light snow-coveryears, eastern and southeastern wind anomalies prevailaround Japan, and precipitation increases from central
Japan to western Japan (Fig. 10c).
On the other hand, the 5km_4K experiment shows
recognizable changes in the surface wind and precipitation around Japan. In heavy snow-cover years, precipitation is enhanced over Japan’s mountainous areas andover the central part of the Sea of Japan at a 95% confidence interval, according to the Mann-Whitney U
test, while precipitation is inhibited over the westernparts of Japan. The zonally enhanced precipitation
band over the Sea of Japan corresponds to the enhancement of the JPCZ, where the precipitation isgreater than that in the surrounding areas in 1km_
HIST (Fig. 9a). Kawase et al. (2016) suggested that theenhancement of JPCZ due to global warming brought
extremely heavy daily snowfall over the inland areas of
the Sea of Japan side. Figure 10d indicates that not
only extremely heavy daily snowfall events but also thewinter mean atmospheric field shows the enhancementof JPCZ in heavy snow-cover years. Precipitation
clearly decreases over the Sea of Japan coast in mediansnow-cover years, while precipitation increases overthe Pacific Ocean side and mountainous areas of central Japan, which corresponds to the weakened wintermonsoon (Fig. 10e). Changes during light snow-coveryears also reflect the weakened winter monsoon, but
the signals are smaller than those in median snowcover years.

(2020) 7:10

Page 15 of 17

Our results indicate that the weakened winter monsoon
effects changes in precipitation, including snowfall, in median and light snow-cover years, while the enhancementof the JPCZ brings increases in snowfall and snow coverin heavy snow-cover years in the high mountainous areasof central Japan, such as Japan’s Northern Alps.

Abbreviations
d4PDF: Database for Policy Decision making for Future climate change;
JMA: Japan Meteorological Agency; JPCZ: Japan-Sea Polar-airmass Convergence Zone; mASL: m above sea level; MRI: Meteorological ResearchInstitute; NHRCM: Non-hydrostatic regional climate model; NN-Alps: Northernparts of Japan’s Northern Alps

Kawase et al. Progress in Earth and Planetary Science

Conclusions
We conducted dynamical downscaling using NHRCM
with 1 km and 5 km grid spacing from d4PDF 20 km
NHRCM and investigated future changes in snowfall
and snow cover over the high mountainous areas of central Japan. We picked up 5 years with heavy snow cover,
5 years with median snow cover, and 5 years with lightsnow cover over the Japanese Alps in three climates, i.e.,
the present climate and 2 K and 4 K warming climates
relative to the pre-industrial period.
In heavy snow-cover years under 2 K and 4 K warming
climates, the mid-winter snowfall amount is comparable
to that in the present climate above 2000 mASL in the
NN-Alps. Due to global warming, the amount of halfmonthly snowfall becomes larger above 2000 mASL of
the NN-Alps in mid-winter. The strengthened Japan-Sea
Polar-airmass Convergence Zone (JPCZ) corresponds tothe increase in snowfall during heavy snow-cover years,
especially under a 4 K warming climate. Daily heavy
snowfall is also strengthened under 4 K warming at highelevations. At lower elevations—below 500 m—thefrequency of snowfall decreases in all ranges of snowfall
intensity under a 4 K warming climate, while heavy
snowfall increases under a 2 K warming climate.
On the other hand, a large reduction of snow cover is
projected above 2000 mASL of the NN-Alps throughout
the winter in light snow-cover years under a 4 K warming climate, which results from changes from snowfall torainfall during the winter. These results indicate that thedifference in mid-winter snow cover between heavy andlight snow-cover years gets larger at high elevations ofJapan’s Northern Alps due to global warming. At low elevations, snow cover drastically decreases over the entire
winter, and daily snowfall intensity is also weakened
under both 2 K and 4 K warming climates.
Our simulations using NHRCM01 can resolve thecomplex Japanese mountains and evaluate the impact of
global warming on years with heavy and light snow
cover based on a large ensemble of climate simulations.
However, we only analyzed 5 years of each snow-covertype under the present, 2K warming, and 4K warming
climate conditions. Some of our results have large uncertainties. To more accurately evaluate future changes
in snowfall over complex mountainous areas and elucidate the mechanisms in consideration of changes in atmospheric circulation, 10- to 20-year simulations are
required using NHRCM01 in each climate.

Acknowledgments
We thank two anonymous reviewers for their useful comments andsuggestions. This work was supported by the Social Implementation
Program on Climate Change Adaptation Technology (SI-CAT) and theIntegrated Research Program for Advancing Climate Models (TOUGOU)Programs of the Ministry of Education, Culture, Sports, Science andTechnology(MEXT), Japan. HK was partly supported by JSPS KAKENHI Grant Number
19H01377. The Earth Simulator was used in this study as the Earth Simulator
Proposed Research Project of “Estimation of Spatial Patterns of Extremely
Heavy Snowfall using High-resolution Regional Climate Ensemble Experiments” in JAMSTEC.
Availability of data and material
The database for Policy Decision making for Future climate change (d4PDF) isavailable at http://www.miroc-gcm.jp/~pub/d4PDF/index_en.html. Data sharing
is not applicable to this article, as no datasets were generated or analyzed
during the current study. Please contact the author with data requests.
Authors’ contributions
HK proposed the topics, conducted the numerical simulations, and analyzed
the output of the simulations. TY supported the analysis of the changes insnow cover in the mountainous areas. SS arranged the output of numericalsimulations and supported the corresponding author in the construction of
the manuscript. TH and MK provided the information about Japan’s Northern
Alps. TS and RI supported the conducting of the numerical simulations. MF
created the boundary conditions of the 2 K warming experiments. AM, MN,
and HS supported the establishing of the numerical design. All authors readand approved the final manuscript.
Funding
This work was supported by the Social Implementation Program on Climate
Change Adaptation Technology (SI-CAT) and the Integrated Research
Program for Advancing Climate Models (TOUGOU) Programs of the Ministryof Education, Culture, Sports, Science and Technology (MEXT), Japan. HK was
partly supported by JSPS KAKENHI Grant Number 19H01377.
Competing interests
The authors declare that they have no competing interest.
Author details
Meteorological Research Institute, Japan Meteorological Agency, 1-1
Nagamine, Tsukuba 305-0052, Japan. 2Department of Geophysics, Graduate
School of Science, Tohoku University, 6-3 Aramaki Aza-Aoba, Aoba-ku, Sendai
980-8578, Japan. 3Japan Agency for Marine-Earth Science and Technology,
3173-25 Showamachi, Kanazawa-ku, Yokohama 236-0001, Japan. 4Japan
Meteorological Business Support Center, 1-1 Nagamine, Tsukuba 305-0052,
Japan. 5Natural Environment Division, Nagano Environmental Conservation
Research Institute, 2054-120 Kitago, Nagano 381-0075, Japan.
1

Received: 6 September 2019 Accepted: 22 January 2020

References
Aoki K, Watanabe K (2009) Measurements of atmospheric aerosol at Mt. Tateyama,
Japan. Earozoru Kenkyu 24:112–116 (in Japanese with English abstract)
Aoyagi T, Seino N (2011) A square prism urban canopy scheme 671 for the NHM
and its evaluation on summer conditions in the Tokyo metropolitan area,
Japan. J Appl Meteorol Climatol 50:1476–1496
Asaoka Y, Kominami Y (2013) Incorporation of satellite-derived snow-cover areain spatial snowmelt modeling for a large area: determination of a gridded
degree-day factor. Ann Glaciol 54:205–213
Brown RD, Mote P (2009) The response of Northern Hemisphere snow cover to achanging climate. J Clim 22:2124–2145

(2020) 7:10

Page 16 of 17

Fujita M, Mizuta R, Ishii M, Endo H, Sato T, Okada Y, Kawazoe S, Sugimoto S,
Ishihara K, Watanabe S (2019) Precipitation changes in a climate with 2-K
surface warming from large ensemble simulations by 60-km global and 20km regional atmospheric models. Geophys Res Lett 46:435–442
Gula J, Peltier RW (2012) Dynamical downscaling over the Great Lakes basinof North America using the WRF regional climate model: the impact of
the Great Lakes system on regional greenhouse warming. J Clim 25:
7723–7742
Gutmann ED, Rasmussen RM, Liu C, Ikeda K, Gochis DJ, Clark MP, Dudhia J,
Thompson G (2012) A comparison of statistical and dynamical downscalingof winter precipitation over complex terrain. J Clim 25:262–281
Hara M, Yoshikane T, Kawase H, Kimura F (2008) Estimation of the impact of
global warming on snow depth in Japan by the pseudo-global-warming
method. HRL 2:61–64
Hirai M, Oh’izumi M (2004) Development of a new land-surface model for JMAGSM. Proceedings of the 20th Conference on Weather Analysis andForecasting/16th Conference on Numerical Weather Prediction, P2.22[Available at https://ams.confex.com/ams/84Annual/techprogram/paper_6
8652.htm.]
Hori M E, Ueda H (2006) Impact of global warming on the East Asian wintermonsoon as revealed by nine coupled atmosphere-ocean GCMs. Geophys
Res Lett 33:L03713
Hu Z-Z, Bengtsson L, Arpe K (2000) Impact of the global warming on the Asian
winter monsoon in a coupled GCM. J Geophys Res 105:4607–4624
Ikawa M, Mizuno H, Matsuo T, Murakami M, Yamada Y, Saito K (1991) Numericalmodeling of the convective snow cloud over the Sea ofJapan—precipitation mechanism and sensitivity to ice crystal nucleation
rates. J Meteor Soc Japan 69:641–667
Ikeda K, Rasmussen R, Liu C, Gochis D, Yates D, Chen F, Tewari M, Barlage
M, Dudhia J, Miller K, Arsenault K, Grubišić V, Thompson G, Guttman E(2010) Simulation of seasonal snowfall over Colorado. Atmos Res 97:
462–477
Imada Y, Watanabe M, Kawase H, Shiogama H, Arai M (2019) The July 2018 hightemperature event in Japan could not have happened without humaninduced global warming. SOLA 15A:8–12
Inatsu M, Kimoto M (2005) Two types of interannual variability of the mid-winterstorm-tracks and their relationship to global warming. SOLA 1:61–64
Inoue S, Yokoyama K (1998) Estimation of snowfall, maximum snow depth andsnowpack condition in Japan under global climate change. Seppyo 60:367–
378 (in Japanese with English abstract)
Inoue S, Yokoyama K (2003) Estimates of snowfall depth, maximum snow depth,and snow pack environments under global warming in Japan from five setsof predicted data. J Agric Meteorol 59:227–236
Ishii Y, Suzuki K (2011) Regional characteristics of variation of snowfall in Japan. J
Jpn Assoc Hydrol Sci 41:27–37 (in Japanese with English abstract)
Ishizaka M (2004) Climatic response of snow depth to recent warmer winterseasons in heavy-snowfall areas in Japan. Ann Glaciol 38:299–304
Ito R, Aoyagi T, Hori N, Oh’izumi M, Kawase H, Dairaku K, Seino N, Sasaki H (2018)
Improvement of snow depth reproduction in Japanese urban areas by the
inclusion of a snowpack scheme in the SPUC model. J Meteor Soc Japan 96:
511–534
Iwao K, Inatsu M, Kimoto M (2012) Recent changes in explosively developing
extratropical cyclones over the winter Northwestern Pacific. J Clim 25:
7282–7296
Kain JS, Fritsch JM (1993) Convective parameterization for mesoscale models: theKain-Fritsch scheme, in The Representation of Cumulus Convection in
Numerical Models. Meteorological Monographs, Emanuel KA and RaymondDJ (eds.), chapter 24, pp. 165–170, Am Meteorol Soc, Boston
Katsuyama Y, Inatsu M, Nakamura K, Matoba S (2017) Global warming
response of snowpack at mountain range in northern Japan estimatedusing multiple dynamically downscaled data. Cold Reg Sci and Technol
136:62–71
Kawase H, Hara M, Yoshikane T, Ishizaki NN, Uno F, Hatsushika H, Kimura F (2013)
Altitude dependence of future snow cover changes over Central Japanevaluated by a regional climate model. J Geophys Res 118:12444–12457
Kawase H, Murata A, Mizuta R, Sasaki H, Nosaka M, Ishii M, Takayabu I (2016)
Enhancement of heavy daily snowfall in central Japan due to global
warming as projected by large ensemble of regional climate simulations.
Climatic Change 139:265–278
Kawase H, Iida H, Aoki K, Shimada W, Nosaka M, Murata A, Sasaki H (2019a)
Comparison of snow cover observations along the Tateyama-Kurobe Alpine

route with snow cover simulations using the non-hydrostatic regional climate
model (NHRCM) with different horizontal resolutions. J Geogr (Chigaku Zasshi)
128:77–92 (in Japanese with English abstract)
Kawase H, Imada Y, Sasaki H, Nakaegawa T, Murata A, Nosaka M, Takayabu I(2019b) Contribution of historical global warming to local-scale heavy
precipitation in western Japan estimated by large ensemble high-resolution
simulations. J Geophys Res 124:6093–6103
Kawase H, Suzuki C, Ishizaki NN, Uno F, Iida H, Aoki K (2015) Simulations ofmonthly variation in snowfall over complicated mountainous areas around
Japan’s Northern Alps. SOLA 11:138–143
Kawase H, Sasai T, Yamazaki T, Ito R, Dairaku K, Sugimoto S, Sasaki H, Murata A,
Nosaka M (2018a) Characteristics of synoptic conditions for heavy snowfall inwestern to northeastern Japan analyzed by the 5-km regional climate
ensemble experiments. J Meteor Soc Japan 96:161–178.
Kawase H, Yamazaki A, Iida H, Aoki K, Sasaki H, Murata A, Nosaka M (2018b)
Simulation of extremely small amounts of snow observed at highelevations over the Japanese Northern Alps in the 2015/16 winter. SOLA
14:39–45
Kawase H, Yoshikane T, Hara M, Fujita M, Ishizaki N, Hatsushika H, Kimura F (2012)
Downscaling of snow cover changes in the late 20th century using a past
climate simulation method over Central Japan. SOLA 8:61–64
Kimoto M (2005) Simulated change of the East Asian circulation under global
warming scenario. Geophys Res Lett. https://doi.org/10.1029/2005GL023383
Kimura F, Kitoh A (2007) Downscaling by pseudo global warming method. The
Final Report of the ICCAP:43–46
Kitagawa H (2000) Radiation processes. Separate volume of the annual report ofnumerical prediction division 46:16–31 (in Japanese)
Matsuura S, Matsuyama K, Asano S, Okamoto T, Takeuchi Y (2005) Fluctuation of
the seasonal snowpack in a mountainous area of the heavy-snow district inthe warm-temperate zone of Japan. J Glaciol 51:547–554
Mizuta R, Murata A, Ishii M, Shiogama H, Hibino K, Mori N, Arakawa O, Imada Y,
Yoshida K, Aoyagi T, Kawase H, Mori M, Okada Y, Shimura T, Nagatomo T,
Ikeda M, Endo H, Nosaka M, Arai M, Takahashi C, Tanaka K, Takemi T,
Tachikawa Y, Temur K, Kamae Y, Watanabe M, Sasaki H, Kitoh A, Takayabu I,
Nakakita E, Kimoto M (2017) Over 5000 years of ensemble future climate
simulations by 60 km global and 20 km regional atmospheric models. Bull
Amer Meteor Soc 98:1383–1398
Nakanishi M, Niino H (2004) An improved Mellor-Yamada level-3 model withcondensation physics: its design and verification. Bound-Lay Meteor 112:1–31
Nakano M, Kato T, Hayashi S, Kanada S, Yamada Y, Kurihara K (2012) Development ofa 5-km-mesh cloud-system-resolving regional climate model at theMeteorological Research Institute. J Meteor Soc Japan 90:339–350
Notaro M, Bennington V, Vavrus S (2015) Dynamically downscaled projections oflake-effect snow in the Great Lakes basin. J Clim 28:1661–1684
Ohba M, Sugimoto S (2019) Differences in climate change impacts between
weather patterns: possible effects on spatial heterogeneous changes of
future extreme rainfall. Clim Dyn 52:4177–4191
Raisanen J (2007) Warmer climate: less or more snow? Clim Dyn 30:307–319
Rasmussen R, Liu C, Ikeda K, Gochis D, Yates D, Chen F, Tewari M, Barlage M,
Dudhia J, Yu W, Miller K (2011) High-resolution coupled climate runoff
simulations of seasonal snowfall over Colorado: a process study of current
and warmer climate. J Clim 24:3015–3048
Rasmussen R, Ikeda K, Liu C, Gochis D, Clark M, Dai A, Gutmann E, Dudhia J, Chen
F, Barlage M, Yates D, Zhang G (2014) Climate change impacts on the waterbalance of the Colorado headwaters: High‐resolution regional climate model
simulations. J Hydrometeorol 15:1091–1116
Sasai T, Kawase H, Kanno Y, Yamaguchi J, Sugimoto S, Yamazaki T, Sasaki H, Fujita
M, Iwasaki T (2019) Future projection in extreme heavy snowfall event with
5-km large ensemble regional climate simulation. J Geophys Res. https://doi.
org/10.1029/2019JD030781
Sasaki H, Kurihara K, Takayabu I, Uchiyama T (2008) Preliminary experiments ofreproducing the present climate using the non-hydrostatic regional climate
model. SOLA 4:25–28
Steger C, Kotlarski S, Jonas T, Schar C (2012) Alpine snow cover in a changing
climate: a regional climate model perspective. Clim Dyn 41:735–754
Suzuki H (2006) Long-term changes in snowfall depth and snow cover depth inand around Niigata Prefecture from 1927 to 2005: analysis using data
observed at railway stations. Tenki 53:185–196 (in Japanese with English
abstract)
Takeuchi Y, Endo Y, Murakami S (2008) High correlation between winterprecipitation and air temperature. Ann Glaciol 49:7–10

Kawase et al. Progress in Earth and Planetary ScienceKawase et al. Progress in Earth and Planetary Science(2020) 7:10

Uno F, Kawase H, Ishizaki NN, Yoshikane T, Hara M, Kimura F, Iyobe T, Kawashima
K (2014) Analysis of regional difference in altitude dependence of snow
depth using high resolve numerical experiments. SOLA 10:19–22
Yabu S, Murai S, Kitagawa H (2005) Clear sky radiation scheme. Separate Volumeof the Annual Report of Numerical Prediction Division 51:53–64 (in Japanese)
Yamaguchi S, Abe O, Nakai S, Sato A (2011) Recent fluctuations of meteorologicaland snow conditions in Japanese mountains. Ann Glaciol 52:209–215

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