Precipitation is a function of many topographical features as well as geographical locations. The correlations between precipitation and topographical and geographical features can be used to improve estimation of precipitation distribution. In this paper, we built seasonal precipitation model based on GIS techniques in Zhejiang Province in southeastern China. Terrain variables derived from the 1 km resolution DEM are used as predictors of the seasonal precipitation, using a regression-based approach. Variables used for model development include: longitude, latitude, elevation, and distance from the nearest coast, direction to the nearest coast, slope, aspect, and the ratio of land to sea within given radii. Seasonal precipitation data, for the observation period 1971 to 2000, were assembled from 59 meteorological stations. Precipitation data from 52 meteorological stations were used to initialize the regression model. The data from the other 7 stations were retained for model validation. Seasonal precipitation surfaces were constructed using the regression equations, and refined by kriging the residuals from the regression model and subtracting the result from the predicted surface. Latitude, elevation and distance from the sea are found to be the most effective predictors of local seasonal precipitation. Validation determined that regression plus kriging predicts mean seasonal precipitation with a coefficient of determination (R2), between the estimated and observed values, of 0.546 (winter) and 0.895 (spring). A simple regression model without kriging yields less accurate results in all seasons.
The previous studies on the effects of artificial oases to the climatic environment were mainly based on the comparison of the observed data from very few sites in short periods (for several days or several months) and the analysis on the differences of the climatic factors between oases and deserts as well as the mechanism of energy exchange. In this paper, the representative series reflecting the climatic background change and the climatic series representing the different oases are developed by carefully selecting the observed data from some meteorological stations where the change of the observation environment is slight, the regions are sparsely populated, and the large-scale water and land exploitations are not undertaken yet. The change ratio differences of the interannual change trends of 10 climatic factors, such as the air temperature, precipitation, vapor pressure, evaporation and wind speed, are analyzed, and the compositive effects of oasis development to the long-term climate change are researched. The results show that the climatic environmental effects caused by oasis development are significant in affecting the local long-term climate change trend. In summer, the increase trend of the mean air temperature in the oases is lower than that of the background change trend, and the change trends of air temperature are in a slight decrease status in some oases, such as in the oases in the Turpan-Shanshan-Toksun Basin and the Yarkant River watershed. The oases play an obvious restraining role in the increase trend of the maximum temperature, in which the change trends of the maximum temperature are in a slight decrease status in the oases in the Yarkant River watershed and the middle reaches of Tarim River. The oases play a certain active role in increasing the minimum temperature, and the oasis effects make the diurnal-nocturnal temperature difference become smaller and smaller. In summer, the oases play an obvious role in increasing the air vapor pressure, and make the evaporation potential become lower and lower and the precipitation be increased to a certain extent. The most significant aspect of the oasis effects is the change of wind speed, that is the average wind speed and the occurring days of gales are sharply reduced in the oases.