The performances of various dynamical models from the Asia-Pacific Economic Cooperation（APEC） Climate Center（APCC） multi-model ensemble（MME） in predicting station-scale rainfall in South China（SC） in June were...The performances of various dynamical models from the Asia-Pacific Economic Cooperation（APEC） Climate Center（APCC） multi-model ensemble（MME） in predicting station-scale rainfall in South China（SC） in June were evaluated.It was found that the MME mean of model hindcasts can skillfully predict the June rainfall anomaly averaged over the SC domain.This could be related to the MME＇s ability in capturing the observed linkages between SC rainfall and atmospheric large-scale circulation anomalies in the Indo-Pacific region.Further assessment of station-scale June rainfall prediction based on direct model output（DMO） over 97 stations in SC revealed that the MME mean outperforms each individual model.However,poor prediction abilities in some in-land and southeastern SC stations are apparent in the MME mean and in a number of models.In order to improve the performance at those stations with poor DMO prediction skill,a station-based statistical downscaling scheme was constructed and applied to the individual and MME mean hindcast runs.For several models,this scheme can outperform DMO at more than 30 stations,because it can tap into the abilities of the models in capturing the anomalous Indo-Paciric circulation to which SC rainfall is considerably sensitive.Therefore,enhanced rainfall prediction abilities in these models should make them more useful for disaster preparedness and mitigation purposes.展开更多
A possible reason for the unreasonable simula- tion of maximum rainfall location, intensity and seasonal evolution over eastern China in CCM3 has been investigated. The analyses focus on the relationship between the s...A possible reason for the unreasonable simula- tion of maximum rainfall location, intensity and seasonal evolution over eastern China in CCM3 has been investigated. The analyses focus on the relationship between the simulated East Asian subtropical westerly jet biases and the seasonal evolution of rainbelt over eastern China. Comparisons of the simulated and observed precipitation distributions indicate that the simulated maximum rainfall location, intensity and seasonal evolution are inconsistent with reality. The simu- lated westerly jet center is located to the north of 40°N, which shifts eastward and northward and strengthens, com- pared with NCEP/NCAR reanalysis. The correlation analysis shows that there exists a significant positive correlation be- tween the maximum rainfall amount and zonal wind at 200 hPa over the Great Bend of the Huanghe River. Thus the simulated unrealistic heavy precipitation in the inland area of western China is related to the biases in the location and intensity of the East Asian subtropical westerly jet. Further analysis indicates that the temperature differences from south to north in the lower troposphere and the larger sensi- ble heating over the southeast Tibetan Plateau are responsi- ble for the westerly jet location and intensity biases. There- fore, much more attention should be paid to the accurate simulation of the surface heating near the Tibetan Plateau and the location and intensity of the East Asian subtropical westerly jet for the improvement of precipitation simulation over East Asia.展开更多
基金supported by the City University of Hong Kong(Grant No.9360126)
文摘The performances of various dynamical models from the Asia-Pacific Economic Cooperation（APEC） Climate Center（APCC） multi-model ensemble（MME） in predicting station-scale rainfall in South China（SC） in June were evaluated.It was found that the MME mean of model hindcasts can skillfully predict the June rainfall anomaly averaged over the SC domain.This could be related to the MME＇s ability in capturing the observed linkages between SC rainfall and atmospheric large-scale circulation anomalies in the Indo-Pacific region.Further assessment of station-scale June rainfall prediction based on direct model output（DMO） over 97 stations in SC revealed that the MME mean outperforms each individual model.However,poor prediction abilities in some in-land and southeastern SC stations are apparent in the MME mean and in a number of models.In order to improve the performance at those stations with poor DMO prediction skill,a station-based statistical downscaling scheme was constructed and applied to the individual and MME mean hindcast runs.For several models,this scheme can outperform DMO at more than 30 stations,because it can tap into the abilities of the models in capturing the anomalous Indo-Paciric circulation to which SC rainfall is considerably sensitive.Therefore,enhanced rainfall prediction abilities in these models should make them more useful for disaster preparedness and mitigation purposes.
基金supported jointly by the National Natural Science Foundation of China(Grant No.40333026)the Knowledge Innovation Program of the Chinese Academy of Sciences(Grant No.ZKCX2-SW-210)
文摘A possible reason for the unreasonable simula- tion of maximum rainfall location, intensity and seasonal evolution over eastern China in CCM3 has been investigated. The analyses focus on the relationship between the simulated East Asian subtropical westerly jet biases and the seasonal evolution of rainbelt over eastern China. Comparisons of the simulated and observed precipitation distributions indicate that the simulated maximum rainfall location, intensity and seasonal evolution are inconsistent with reality. The simu- lated westerly jet center is located to the north of 40°N, which shifts eastward and northward and strengthens, com- pared with NCEP/NCAR reanalysis. The correlation analysis shows that there exists a significant positive correlation be- tween the maximum rainfall amount and zonal wind at 200 hPa over the Great Bend of the Huanghe River. Thus the simulated unrealistic heavy precipitation in the inland area of western China is related to the biases in the location and intensity of the East Asian subtropical westerly jet. Further analysis indicates that the temperature differences from south to north in the lower troposphere and the larger sensi- ble heating over the southeast Tibetan Plateau are responsi- ble for the westerly jet location and intensity biases. There- fore, much more attention should be paid to the accurate simulation of the surface heating near the Tibetan Plateau and the location and intensity of the East Asian subtropical westerly jet for the improvement of precipitation simulation over East Asia.
