Geography Reference
In-Depth Information
N
N
1992
2005
1992
2005
(km)
(km)
0
50
100
200
01
50
00
200
20
200
Province boundary
Urban and built-up land
Dryland cropland and pasture
Irrigated cropland and pasture
Grassland
Deciduous broadleaf forest
Water bodies
Wetland
Barren or sparsely vegetated land
Province boundary
Urban and built-up land
Dryland cropland and pasture
Irrigated cropland and pasture
Grassland
Deciduous broadleaf forest
Water bodies
Wetland
Barren or sparsely vegetated land
Fig. 4.9
The LUCC map after upscaling in 1992 and 2005
The LUCC data of the North China Plain in 1992 and 2005 are overlaid to
further analyze the conversion and inner change of each land cover type. The result
indicates that the LUCC is mainly characterized by the increase of the urban and
built-up land and decrease of the dryland cropland, the changing rate of which
reached 2.12 and 1.59 %, respectively. By contrast, the changing rates of other
land cover types are not more than 0.5 %. The result suggests that the newly
increased urban and built-up land is mainly located in the Beijing-Tianjin-Tang-
shan zone and large and around medium-sized cities, such as Shijiazhuang,
Zhengzhou, Ji'nan, Qingdao, and Lianyungang; besides, the newly increased urban
and built-up land mainly converted from the dryland cropland, accounts for
60.55 % of the conversion of the dryland cropland (Fig.
4.10
).
4.3.2.2 Ability of the WRF Model to Simulate the Temperature
Change in the North China Plain
The test results obtained with the standard WRF model is first compared with the
ground-based observation data to assess the ability of the WRF model to simulate
the climate in the North China Plain. The daily average temperature is calculated
as the average value of the temperature at 00:00, 06:00, 12:00, and 18:00 so as to
keep consistent with the ground-based observation criteria. The results indicate
that the WRF model can simulate the spatiotemporal change of temperature very
well (Fig.
4.11
). According to the monthly change of daily average temperature in
the whole study area, the highest temperatures in the observation data and
