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Dynamical downscaling of urban climate using CReSiBUC with inclusion of
detailed land surface parameters
Kenji Tanaka 1 , Kazuyoshi Souma 2 , Takahiro Fujii 1 and Makoto Yamauchi 1
1 WRRC, DPRI, Kyoto University, Gokasho Uji, 611-0011, Japan, E-mail: tanaka@wrcs.dpri.kyoto-u.ac.jp
2 IPRC, SOEST, University of Hawaii, 1680 East West Road, POST Bldg., 4th Floor, Honolulu, HI 96822 U.S.A.
1. Introduction
Recently, a sense of impending crisis for the global warming
came to be realized, and the social needs for the concrete
description of future climate has been increasing. Regional
climate model (RCM) might be indispensable on predicting
detailed characteristics of climate change. Although RCMs
have accomplished remarkable development in recent years,
the requirement from user side on the resolution and the
accuracy has been increasing more and more. Thus, there is
still a gap between precision realized by models and that
required from users.
The research project of S-5-3 "Multi-model ensemble and
downscaling for global warming impact assessment study"
is an ongoing project under the global environment research
fund of Japanese Ministry of Environment. The final goal of
S-5-3 is to provide the detailed and reliable future climate
scenario around Japan for climate change impact assessment
community. Since most of populations are concentrated in
the city area, concrete description of future urban climate is
an important issue. In this study, dynamical downscaling is
performed by the non-hydrostatic meteorological model
CReSiBUC (Moteki et al., 2005) to include the effect of
urban area as realistically as possible.
processes are calculated with empirical constant values of
albedo, evaporation efficiency, and roughness for
simplifying calculations. To the contrary, the SiBUC
calculates budgets of radiation, heat, water, and
momentum while changing parameters for the surface
condition. For example, for an urban area in the SiBUC,
irregularity associated with buildings is considered on the
basis of the urban canyon concept. As shown in Figure 2,
roof height distribution in one model grid cell can be
directly incorporated as geometrical information of urban
area. Additionally, the SiBUC adopts a "mosaic"
approach. In case that a horizontal grid of the CReSS is
including a number of various land use categories, values
on each category are calculated and a value averaged for
these is returned to the CReSS. This mosaic scheme is an
effective facility especially for the domain where multiple
artificial landuse categories of urban, paddy, etc. are
mixed as like Japan.
story
Roof height distribution
1.0
Example for r(1)=0.6, r(2)=0.3, r(3)=0.1
0.6 0.3 0.1
CReSiBUC
3
2
1
r(1) r(2) r(3)
fraction
Figure 2. Roof height distribution in urban canopy.
CReSS
Cloud Resolving
Storm Simulator
SiBUC
Simple Biosphere including
Urban Canopy
Figure 1. Coupled model of CReSS and SiBUC.
2. CReSiBUC
Figure 1 shows a schematic image of a coupling of the nonhydrostatic
meteorological model CReSS (Cloud Resolving
Storm Simulator) and the precise land surface model SiBUC
(Simple Biosphere model including Urban Canopy). The
CReSS is a non-hydrostatic meteorological model developed
in Hydrospheric Atmospheric Research Center, Nagoya
University (Tsuboki and Sakakibara, 2002). The CReSS has
a high calculation efficiency that satisfies a condition to use
the "Earth Simulator," which is one of the fastest super
computers in the world. The SiBUC is a land surface
processes model developed in Water Resources Research
Center, Disaster Prevention Research Institute, Kyoto
University (Tanaka, 2004). The SiBUC calculates surface
fluxes and related hydrological quantities considering
detailed processes. In the normal CReSS, the land surface
3. Land Surface Parameters
Various kind of land surface information must be prepared
to enable the realistic setting of land surface condition. As
for landuse and soil type, 100m resolution datasets are
provided from National and Regional Planning Bureau in
MLIT (http://nlftp.mlit.go.jp/ksj/). SPOT VEGETATION
Products (http://free.vgt.vito.be) are utilized for timevarying
vegetation parameters in 1km resolution.
Tokyo Metropolitan Governmental Office has established
the precise GIS database of urban geometrical information.
Figure 3 is an example of building floor number dataset
for Shinjuku area (about 5km x 5km area). As seen from
this figure, this is a vector data of individual buildings.
This information is converted into roof height distribution
in each model grid. Owing to this kind of precise
information, spatial distribution and its typical diurnal
cycle of anthropogenic heat can be estimated following the
method of Senoo et al.(2004). Figure 4 shows the spatial
distribution of anthropogenic heat around Tokyo at 12JST.
4. Initial and Boundary Conditions
In this S-5-3 project, dynamical downscaling of urban
climate is executed only for the summer season (July and
August). Then, initial condition of land surface state
variables (especially soil wetness) is a big issue when
accounting for the effect of the inter-annual variability
(wet summer & dry summer). Although there are
numerous surface weather observation sites in Japan, few
observe the state of the land surface. We have developed a