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| Improving the Seasonal Forecast of Summer Precipitation in China Using a Dynamical-Statistical Approach |
| JIA Xiao-Jing,ZHU Pei-Jun |
| Department of Earth Sciences, Zhejiang University, Hangzhou, Zhejiang 310027, China,Department of Earth Sciences, Zhejiang University, Hangzhou, Zhejiang 310027, China |
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Abstract A dynamical-statistical post-processing approach is applied to seasonal precipitation forecasts in China during the summer. The data are ensemble-mean seasonal forecasts in summer (June-August) from four atmospheric general circulation models (GCMs) in the second phase of the Canadian Historical Forecasting Project (HFP2) from 1969 to 2001. This dynamical-statistical approach is designed based on the relationship between the 500 geopotential height (Z500) forecast and the observed sea surface temperature (SST) to calibrate the precipitation forecasts. The results show that the post-processing can improve summer precipitation forecasts for many areas in China. Further examination shows that this post-processing approach is very effective in reducing the model-dependent part of the errors, which are associated with GCMs. The possible mechanisms behind the forecast's improvements are investigated.
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Received: 25 December 2009
Revised: 06 February 2010
Accepted: 05 March 2010
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