Research on Adjusting Effect for Different Mathematical Model of Precipitation Series

Based on the model of successive multiple linear regression, one-variate linear regression, ratio value method and aggregate method the analyses and tests of precipitation series correction are carried out by using the data observed at thirty-one stations in twenty-five Provinces of China. The results show that: the correction effect of multiple linear regression method for annual precipitation data series is better than those of other methods, the average relative fitting error is less than 0.08, and the other is more than 0.11 for monthly data series; if the relative fitting error is less than 0.10, the time of paralled data requested in the equation should be longer than 10 years, the correlation coefficient above 0.05; if the precipitation is above 300mm, the error is less than 0.10 and if below 300 mm, the error is more than 0.11