Geography Reference
In-Depth Information
Table 6.1
Schemes of the simulation test
Test
Test time
Land cover data used in WRF
Control test
2030.01.01-2040.12.31
Land cover data of 2010
Sensitivity test
2030.01.01-2040.12.31
Land cover data of 2030
Table 6.2 Configuration of
the physical parameterization
schemes in WRF
Physical processes
Scheme option
Microphysics scheme
Lin et al.
Cumulus scheme
Grell-Decenyi ensemble
Land surface process
Noah land surface model
Short wave radiation
CAM scheme
Long-wave radiation
CAM scheme
has the higher accuracy and spatial resolution, but also involves more kinds of
environmental variables. The data of future force filed were from the fifth phase of
the Coupled Model Intercomparison Project (CMIP5) which produces a state-of-
the-art multimodel dataset. The model output analyzed by researches forms the
basis for the Fifth Assessment Report of the Intergovernmental Panel on Climate
Change (Taylor et al. 2012 ), and two time scales of projections of future climate
change are provided. The first one is the near term (out to about 2035), and the
other one is the long term (out to 2100 and beyond). Model output of the RCP 6.0
such as air temperature, specific humidity, sea level pressure, eastward wind,
northward wind, geopotential height from 2010 to 2040 were used as the atmo-
spheric forcing dataset of WRF model.
Urban land use data, which were extracted from Landsat TM images in 1995
and Landsat ETM, images from the China-Brazil Earth Resources satellite
(CBERS) in 2005 (Liu et al. 2003 , 2010 ), was acquired from the data center of the
Chinese Academy of Sciences. The land use change during 1995-2005 has been
described Table 6.3 . The predicted land use and land cover data in 2030 were
derived from the database of Representative Concentration Pathway (RCP6.0).
The new urban area pixels during 2010-2030 derived from RCP 6.0 was overlaid
to the map of baseline underlying surface, then the underlying surface data in 2030
was transformed to grid data of 30*30 km of USGS data by resampling.
6.1.2 Results and Discussion
6.1.2.1 Spatiotemporal Pattern of Urban Expansion Since 1995
Urban expansion is one of the key characteristics of land use change in the Great
Beijing area from 1995 to 2005, the spatiotemporal pattern of which was analyzed
according to remote sensing data (Table 6.3 ). During 1995 and 2005, the total area
of cultivated land and forests decreased by 0.98 and 2.15 %, respectively, while
the urban land area increased by 3.34 %, with an average annual rate of 0.33 %.
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