A PREDICTING DROUGHT MODEL WITH AN INTEGRATION OF MULTI-SCALE IN NORTH CHINA

Based on the significant interdecadal and interannual variations of the drought in North China, a new modeling technique of the drought prediction is proposed, i. e., the drought change is regarded as a composition of the interdecadal variation, the interannual variation and a noise. The technique is composed of modeling both the climate trend, to be represented with the interdecaeal variation, and the interannual variation plus the antecedent strong signal. The sum of predictions made with two models is taken as a final prediction of the drought. The prediction experiments for winter, spring, summer and autumn with one to two seasons ahead are made. The results show that the modeling technique can catch the change in drought well in North China. The prediction model differs from the previous modeling, which based on computing correlation between the drought index and the atmospheric and oceanic elements, then considering the correlation be invariable. Hereby the concept of dynamic strong signal is suggested, it is the observation series in some regions where the remarkable difference between the recent atmospheric and oceanic anomaly and the multi-year mean occurs. The strong signals varies with different years in which the serious drought occurs, and their spatial, positions and intensities varies too. An extra season hind cast for 1996 to 2002 shows that the modeling is capable of fitting the drought trend and exhibits a higher prediction skill.