Tibetan Plateau’s snow accumulation estimated from regional climatemodel simulation*Izuru Takayabu1, Hidetaka Sasaki1, Kazuyo Murazaki1, Kazuo Kurihara)1
andTomoyoshi Hirota2(1: Meteorological Research Institute, 2: National Agricultural Research Center for Hokkaido Region )*Meteorological Research Institute, 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan, e-mail:takayabu@mri-jma.go.jp
Abstract
To investigate the hydrological cycle of Asian region, we developed a regional climate model coupled witha simple snow model and integrated it for 10 years continuously, nested into a general circulation model. The
accumulation mechanism of snow around Tibetan Plateau is investigated using that model. At thesouth-eastern part of the plateau, the main source of snow is the summer monsoon precipitation. However,around the western part, we have another precipitation maximum, caused by the western disturbances
evolving in early spring. These characteristics have good correspondence to the field studies.

1. Introduction
The largest gross area of the mountain glaciers inthe northern hemisphere mid-latitude is foundaround the Tibetan Plateau. Many studies havebeen performed to clarify the growth mechanism ofglaciers in that region. From observational studies,
it is said that the glaciers around the south easternedge of the Plateau grow with the precipitation of
the Asian summer monsoon. On the other hand,around the western part of the Plateau, the glaciers
grow with the precipitation associated with thewestern disturbances developed in the early spring.
However, there still exists no climatic study by using
the numerical model.
The research using Regional Climate Models(RCMs) is one of the dynamical downscaling
method, and expected to represent the distributionof the mesoscale precipitation which cannot berepresented with ordinary General Circulation
Models (GCMs). Especially we can improve theorographical precipitation by using higher resolution
models, because it mainly depends on theresolution of the mountain range. Especially we
can expect the advantage of using RCMs inforecasting snow accumulation.
Many studies have applied RCMs to snow
accumulation in the arctic region. Lynch et al.
(1998) drove a RCM coupled with several kinds ofland surface schemes, and pointed out theimportance of snow albedo, in the snow melting
process. Dethloff et al. (2002) and Box and Rinke(2002) investigated the formation mechanism ofGreenland ice sheet. Because ice sheet is an
integral value of precipitation minus evaporation, it
diminishes the error coming from short term
fluctuation.
They succeeded to explain thedistribution of ice sheet in Greenland, using
seasonal forecast of RCMs.
In this study, we try to investigate the mechanismof snow accumulation around Tibetan Plateau, byusing MRI-RCM driven by MRI-CGCM2.2.

2. Models and experiments
Here we use Meteorological Research Institute’sRegional Climate Model (MRI-RCM) (Murazaki etal., 2002). The horizontal grid spacing is 60km,and it has 36 levels in the vertical direction. The
area covers Indian subcontinent, Tibetan plateau,
Indochina peninsular, and Japan Islands. Fig.1
shows the topography of the model only around theTibetan Plateau.
The RCM is integrated
continuously for 10 years, nested in MRI-CGCM2.2(Yukimoto et al., 2001) by using Spectral BoundaryMethod (SBC) (Sasaki et al., 1995). Rajendran etal. (2004) showed that MRI-CGCM2.2 successfullyreproduced the climate around the south and east
Asian monsoon region.

Fig.1: Topography of MRI-RCM (m). Only aroundthe Tibetan Plateau is indicated.

Fig.4: Same as in Fig.3 but for FMA.

3. Land Surface
MRI-RCM

Fig.2: Snow equivalent water content (mH2O) ofMRI-RCM. 10 years average of August.

Fig.3: Surface precipitation of MRI-RCM. Meanvalue of JJAS of 10 years, in mm/mon.

model

coupledwithWe developed a new land surface scheme andcoupled it with the MRI-RCM for long termintegration. The land surface scheme solves (1)the land surface heat budget using the 1st soil layer(4cm deep), (2) the heat conduction equation to get
the soil temperature and (3) diffusion equation (theDarcy’s law) to get the soil water content. We
adopt the code of SSiB (Xue et al., 1991) for (3).
As described in Takayabu (2001), there are many
types of numerical model of snow accumulation andmelting processes. Here, the temperature of themodel lowest layer is used to decide if theprecipitation is snow or rain. The snow begins toaccumulate after the 1st soil layer saturates withwater. The degree day method is applied in themodel. The heat capacity of the model is notconserved, because the snow does not melt
through the downward shortwave radiation.
Originally the degree day method uses the daily
average temperature to melt the snow. In themodel, we use the temperature at every time step.
The density of the snow is assumed to be 0.4g/cm3,and the snow melting speed is set 5.5mm/deg/day.
These values are the typical ones, adopted in theoriginal degree day method model. The melt water
infiltrates into the soil. The physical characteristicsof the soil are changed to the values of snow, while
the soil surface is buried under the snow.
The soil water stops to move while the soil
temperature is below the freezing temperature.
However, the evaporation from the snow surface iscounted. The evaporation stops when there is nosnow on the ground surface. We increase theheat capacity of the soil when the soil water freezes

or the frozen soil melt, to include the effect of water
freeze or ice melt.

4. Results4.1. The glaciers represented in the model
In the model we don’t parameterize the glacier.
So, the eternal snow piles up at the same grid point.
Therefore, we can take the heavy snow
accumulated region for the glacier. Fig.2 indicatesmean snow equivalent water (in mH2O) of thewarmest month (August). We decide the grid points
with snow over 1mH2O area as glaciers in themodel. When we compare with the topography ofthe model (Fig.1), we can find glaciers over almost
all the mountain ranges.
This has goodcorrespondence with the existing glaciers, as
shown in Shi (1980).

caused by the western disturbances evolving inMarch.
These characteristics have goodcorrespondence to the field studies.

Acknowledgements
Part of this study was supported by “Water
Resources and Variability in Asia in the 21stCentury” of the Special Coordination Funds for
Promoting Science and Technology of the Ministryof Education, Culture, Sports, Science andTechnology (MEXT), supervised by Dr. A. Kitoh at
the Meteorological Research Institute of Japan
Meteorological Agency.

References
Box, J. E. and A. Rinke, 2003: Evaluation of Greenland
ice sheet surface climate in the HIRHAM regional
climate model using automatic weather station data.

4.2. The growth of glaciersFig. 3 indicates the monthly mean precipitation of
the Asian summer monsoon season (from June toSeptember). Compare the figure with Fig.2, we
can find that all glaciers to the east of 75E
correspond to the area of much precipitation of thisseason. This suggests that all the glaciers of thatarea grow through the summer monsoon sesons
precipitation.
Fig. 4 indicates the monthly mean precipitationfrom February to April. This figure shows us thatthe glaciers over Hindu Kush Mountains and Pamir
Hights grow with the precipitation in this season.
As shown by Lang and Barros (2004), the western
disturbances approach these regions several times
in this season, and the precipitation comes from thepassage of these disturbances.

J. Climate, 16, 1302-1319.
Dethoff, K., M. Schwager, J. H. Christensen, S. Kilsholm,A. Rinke, W. Doen, F. Jung-Rohtenhaeusler, H.
Fisher, S. Kipfstuhl and H. Miller, 2002: Recent
Greenland accumulation estimated from regional
climate model simulations and ice core analysis. J.
Climate, 15, 2821-2832.
Lang, T. J. and A. P. Barros, 2004: Winter storms in theCentral Himalayas, J. Meteor. Soc. Japan, 82,829-844.
Lynch, A. H., D. L. McGinnis and D. A. Bailey, 1998:
Snow-albedo feedback and the spring transition in aregional climate model (RegCM2), J. Geophys. Res.
105, 29565-29557.
Murazaki, K, H. Sasaki and Y. Sato, 2002: A present
climate simulation using a regional climate model (inJapanese). Proc. 2002 Fall meeting of the Japan
Meteorological Society, Sapporo, Japan. Japan

5. Conclusion
To investigate the hydrological cycle of Asianregion, we developed a regional climate model andintegrated it for 10 years continuously, nested into a
general circulation model. A simple snow model isadded into the regional climate model, and we
succeed to reproduce the seasonal change of thesnow cover area over Asian region realistically. The
accumulation mechanism around Tibetan Plateau isinvestigated using that regional climate model. At
the southern periphery of the plateau, the main
source of snow is the summer monsoon
precipitation.
However, around the western
periphery, we have another precipitation maximum,

Meteorological Society, 82.
Rajendran, K., A. Kitoh and S. Yukimoto, 2004: South andEast Asian summer monsoon climate and variationin MRI coupled model (MRI-CGCM2), J. Climate, 17,763-782.
Sasaki, H., H. Kida, T. Koide and M. Chiba, 1995: The
performance of long-term integrations of a limitedarea model with the spectral boundary coupling
method. J. Meteor. Soc. Japan, 73, 165-181.
Shi, Y., 1980: Some achievements on mountain glacier
researches in China. Seppyo, 42, 215-228.
Takayabu, I., K. Takata, T. Yamazaki, K. Ueno, H. Yabuki
and S. Haginoya, 2001: Comparison of the four land
surface models driven by a common forcing dataprepared from GAME/Tibet POP’97 products –2001: The new Meteorological Research InstituteSnow accumulation and soil freezing processes -, J.

coupled GCM (MRI-CGCM2) – Model climate andMet. Soc. Japan, 79, 535-554.

variability -. Pap. Meteor. Geophys. 51, 47-88.

Xue, Y., P. J. Sellers, J. J. Kinter and J. Shukla, 1991: A
simplified biosphere model for global climate studies,J. Climate, 4, 345-364.
Yukimoto, S., A. Noda, A. Kitoh, M. Sugi, Y. Kitamura, M.
Hosaka, K. Shibata, S. Maeda and T. Uchiyama,