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 ge...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.展开更多
The cold vortex is a major high impact weather system in northeast China during the warm season, its frequent activities also affect the short-term climate throughout eastern China. How to objectively and quantitative...The cold vortex is a major high impact weather system in northeast China during the warm season, its frequent activities also affect the short-term climate throughout eastern China. How to objectively and quantitatively predict the intensity trend of the cold vortex is an urgent and difficult problem for current short-term climate prediction. Based on the dynamical-statistical combining principle, the predicted results of the Beijing Climate Center＇s global atmosphereocean coupled model and rich historical data are used for dynamic-statistical extra-seasonal prediction testing and actual prediction of the summer 500-hPa geopotential height over the cold vortex activity area. The results show that this method can significantly reduce the model＇s prediction error over the cold vortex activity area, and improve the prediction skills. Furthermore, the results of the sensitivity test reveal that the predicted results are highly dependent on the quantity of similar factors and the number of similar years.展开更多
基金funded by the National Natural Sci-ence Foundation of China (Grant No. 40805018)
文摘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.
基金supported by the National Natural Science Foundation of China(Grant No.41375078)the National Basic Research Program of China(Grant Nos.2012CB955902 and 2013CB430204)the Special Scientific Research Fund of Public Welfare Profession of China(Grant No.GYHY201306021)
文摘The cold vortex is a major high impact weather system in northeast China during the warm season, its frequent activities also affect the short-term climate throughout eastern China. How to objectively and quantitatively predict the intensity trend of the cold vortex is an urgent and difficult problem for current short-term climate prediction. Based on the dynamical-statistical combining principle, the predicted results of the Beijing Climate Center＇s global atmosphereocean coupled model and rich historical data are used for dynamic-statistical extra-seasonal prediction testing and actual prediction of the summer 500-hPa geopotential height over the cold vortex activity area. The results show that this method can significantly reduce the model＇s prediction error over the cold vortex activity area, and improve the prediction skills. Furthermore, the results of the sensitivity test reveal that the predicted results are highly dependent on the quantity of similar factors and the number of similar years.
