摘要
Based on the analysis of persistent features of drought strength in NorthChina, a new technique to predict the drought strength with an integration of both the droughtytrend and the dynamic strong signal is proposed. Considering the prominent interdecadal andinterannual variations of drought strength, which can be separated by means of a nonlinear dynamicreconstruction, the two models with different time scale to predict droughty trend are establishedrespectively and integrated at last. In the course of model building, a concept of dynamic strongsignal is introduced, and the strong signal of observable difference between previous fields ofatmosphere and ocean and multi-year average values is introduced into the prediction model. It isindicated that the abnormal variations of atmosphere and ocean in the near future may influence thedrought. The extraseasonal hindcasts from 1996 to 2002 show that the prediction model represents thedroughty trend preferably and exhibits higher prediction skill.
Based on the analysis of persistent features of drought strength in NorthChina, a new technique to predict the drought strength with an integration of both the droughtytrend and the dynamic strong signal is proposed. Considering the prominent interdecadal andinterannual variations of drought strength, which can be separated by means of a nonlinear dynamicreconstruction, the two models with different time scale to predict droughty trend are establishedrespectively and integrated at last. In the course of model building, a concept of dynamic strongsignal is introduced, and the strong signal of observable difference between previous fields ofatmosphere and ocean and multi-year average values is introduced into the prediction model. It isindicated that the abnormal variations of atmosphere and ocean in the near future may influence thedrought. The extraseasonal hindcasts from 1996 to 2002 show that the prediction model represents thedroughty trend preferably and exhibits higher prediction skill.
基金
This work is jointly supported by the President Foundation of Chinese Academy of Meteorological Sciences and the NationalNatural Science Foundation of China under Grant No. 40275020.
