its margin area during 1990 to 2001 are selected from China 
monthly average meteorological data in China. The average 
annual temperature, highest annual temperature, lowest annual 
temperature and annual precipitation indexes are calculated by 
the 69 meteorological data. 
3.1 Temperature data process 
Considered the Vertical Lapse Effect of temperature, while 
dealing with the temperature data, firstly each station 
temperature data are rectified to the temperature at the sea level 
(Vertical Lapse Rate of temperature r=0.65/100m). Secondly, 
according to the Kriging Optimization Interpolation Method, 
based on the 1,100m grid size, after annual spatial interpolation 
to the every station meteorological data, the grid data of 
temperature disposal at the sea level height in headstream 
region of Yellow River is gained. Then referring to 1:250,000 
DEM data of headstream region of Yellow River, temperature 
disposal grid data gained above are rectified to the real height 
above seal level and annual temperature spatial disposal data 
from 1990 to 2001 in headstream region of Yellow River are 
obtained. 
Average Annual Average Temperature 
Average Annual Maximum Temperature 
Average Annual Precipitation 
Average Annual Minimum Temperature 
Fig.2 Meteorologic Parameters Change of Headwater Region of Chinese Yellow River 
3.2 Precipitation data process 
Based on the series climate data of 67 meteorological 
stations from 1990 to 2001,the spatial and temporal structure of 
precipitation in Headwater Region of Chinese Yellow River 
was analyzed by using Kriging method and 1100m grid size. 
3.3 Statistical analysis of meteorological data 
Distributive feature of space-time and change trend on air 
temperature and precipitation in source region of the Yellow 
River was analyzed using the data of air temperature and 
precipitation in 1990-2001 in this region. The results are listed 
in fig 2. 
In fig.2, line A, B, C, D are the linear fitting of Average Annual 
Average Temperature, Average Annual Maximum 
Temperature, Average Annual Minimum Temperature, and 
Average Annual Precipitation in ordinary. As showed in 
graphs, maybe the change of temperature and precipitation are 
different in each year. However during 1990-2001, in the 
headstream region of Yellow River, the trend of precipitation 
change is declining while the temperature is opposite. This is 
coincident with the trend of the global climatic change which 
indicates that the region is affected and controlled by the global 
climatic change. In addition, Statistical Characteristics of 
different meteorological index are different. (Tab.l, AAAT 
refers to Average Annual Average Temperature; A AM- axT 
refers to Average Annual Maximum Tern- perature; AAMinT 
refers to Average Annual Minimum Temperature; AAAP refers 
to Average Annual Precipitation ) The average annual 
temperature change is light with trend of increase. The average 
annual precipitation change is 30 mm. 
Minimum 
Maximum 
Mean 
Std. Deviation 
AAAT 
-3.3944 
-1.6043 
-2.420325 
.5287374 
AAMaxT 
13.911 
17.175 
15.25125 
1.048143 
AAMinT 
-24.921 
-21.073 
-23.20967 
1.188685 
AAP 
425.7420 
509.7998 
469.559150 
30.0536530 
Tab.l Statistics Characters of Meteorologic Parameters