This paper provides a comprehensive assessment of Asian summer monsoon prediction skill as a function of lead time and its relationship to sea surface temperature prediction using the seasonal hindcasts of the Beijing...This paper provides a comprehensive assessment of Asian summer monsoon prediction skill as a function of lead time and its relationship to sea surface temperature prediction using the seasonal hindcasts of the Beijing Climate Center Climate System Model, BCC_CSM1. l（m）. For the South and Southeast Asian summer monsoon, reasonable skill is found in the model＇s forecasting of certain aspects of monsoon climatology and spatiotemporal variability. Nevertheless, deficiencies such as significant forecast errors over the tropical western North Pacific and the eastern equatorial Indian Ocean are also found. In particular, overestimation of the connections of some dynamical monsoon indices with large-scale circulation and precipitation patterns exists in most ensemble mean forecasts, even for short lead-time forecasts. Variations of SST, measured by the first mode over the tropical Pacific and Indian oceans, as well as the spatiotemporal features over the Nifio3.4 region, are overall well predicted. However, this does not necessarily translate into successful forecasts of the Asian summer monsoon by the model. Diagnostics of the relationships between monsoon and SST show that difficulties in predicting the South Asian monsoon can be mainly attributed to the limited regional response of monsoon in observations but the extensive and exaggerated response in predictions due partially to the application of ensemble average forecasting methods. In contrast, in spite of a similar deficiency, the Southeast Asian monsoon can still be forecasted reasonably, probably because of its closer relationship with large-scale circulation patterns and E1 Nifio-Southern Oscillation.展开更多
Using hindcasts of the Beijing Climate Center Climate System Model, the relationships between interannual variability （IAV） and intraseasonal variability （ISV） of the Asian-western Pacific summer monsoon are diagn...Using hindcasts of the Beijing Climate Center Climate System Model, the relationships between interannual variability （IAV） and intraseasonal variability （ISV） of the Asian-western Pacific summer monsoon are diagnosed. Predictions show reasonable skill with respect to some basic characteristics of the ISV and IAV of the western North Pacific summer monsoon （WNPSM） and the Indian summer monsoon （ISM）. However, the links between the seasonally averaged ISV （SAISV） and seasonal mean of ISM are overestimated by the model. This deficiency may be partially attributable to the overestimated frequency of long breaks and underestimated frequency of long active spells of ISV in normal ISM years, although the model is capable of capturing the impact of ISV on the seasonal mean by its shift in the probability of phases. Furthermore, the interannual relationships of seasonal mean, SAISV, and seasonally averaged long-wave variability （SALWV; i.e., the part with periods longer than the intraseasonal scale） of the WNPSM and ISM with SST and low-level circulation are examined. The observed seasonal mean, SAISV, and SALWV show similar correlation patterns with SST and atmospheric circulation, but with different details. However, the model presents these correlation distributions with unrealistically small differences among different scales, and it somewhat overestimates the teleconnection between monsoon and tropical central-eastern Pacific SST for the ISM, but underestimates it for the WNPSM, the latter of which is partially related to the too-rapid decrease in the impact of E1 Nifio-Southern Oscillation with forecast time in the model.展开更多
ABSTRACT The abilities of BCC-AGCM2.1 and BCC_AGCM2.2 to simulate the annual-mean cloud vertical structure （CVS） were evaluated through comparison with GCM-Oriented CALIPSO Cloud Product （CALIPSO-GOCCP） data. BCC...ABSTRACT The abilities of BCC-AGCM2.1 and BCC_AGCM2.2 to simulate the annual-mean cloud vertical structure （CVS） were evaluated through comparison with GCM-Oriented CALIPSO Cloud Product （CALIPSO-GOCCP） data. BCC-AGCM2.2 has a dynamical core and physical processes that are consistent with BCC-AGCM2.1, but has a higher horizontal resolution. Results showed that both BCC-AGCM versions underestimated the global-mean total cloud cover （TCC）, middle cloud cover （MCC） and low cloud cover （LCC）, and that BCC_AGCM2.2 underestimated the global-mean high cloud cover （HCC）. The global-mean cloud cover shows a systematic decrease from BCCA-GCM2.1 to BCC_AGCM2.2, especially for HCC. Geographically, HCC is significantly overestimated in the tropics, particularly by BCC_AGCM2,1, while LCC is generally overestimated over extra-tropical lands, but significantly underestimated over most of the oceans, especially for subtropical marine stratocumulus clouds. The leading EOF modes of CVS were extracted. The BCC_AGCMs perform well in reproducing EOF1, but with a larger variance explained. The two models also capture the basic features of EOF3, except an obvious deficiency in eigen- vector peaks. EOF2 has the largest simulation biases in both position and strength of eigenvector peaks. Furthermore, we investigated the effects of CVS on relative shortwave and longwave cloud radiative forcing （RSCRF and RLCRF）. Both BCC_AGCM versions successfully reproduce the sign of regression coefficients, except for RLCRF in PC1. However, the RSCRF relative contributions from PC1 and PC2 are overestimated, while the relative contribution from PC3 is underes timated in both BCC_AGCM versions. The RLCRF relative contribution is underestimated for PC2 and overestimated for PC3.展开更多
基金supported by the National Basic Research Program of China (Grant Nos. 2015CB453200 and 2014CB953900)China Meteorological Special Program (Grant Nos. GYHY 201206016 and GYHY201306020)+1 种基金the National Natural Science Foundation of China (Grant Nos. 41305057, 41275076, and 41375081)the Jiangsu Collaborative Innovation Center for Climate Change, China
文摘This paper provides a comprehensive assessment of Asian summer monsoon prediction skill as a function of lead time and its relationship to sea surface temperature prediction using the seasonal hindcasts of the Beijing Climate Center Climate System Model, BCC_CSM1. l（m）. For the South and Southeast Asian summer monsoon, reasonable skill is found in the model＇s forecasting of certain aspects of monsoon climatology and spatiotemporal variability. Nevertheless, deficiencies such as significant forecast errors over the tropical western North Pacific and the eastern equatorial Indian Ocean are also found. In particular, overestimation of the connections of some dynamical monsoon indices with large-scale circulation and precipitation patterns exists in most ensemble mean forecasts, even for short lead-time forecasts. Variations of SST, measured by the first mode over the tropical Pacific and Indian oceans, as well as the spatiotemporal features over the Nifio3.4 region, are overall well predicted. However, this does not necessarily translate into successful forecasts of the Asian summer monsoon by the model. Diagnostics of the relationships between monsoon and SST show that difficulties in predicting the South Asian monsoon can be mainly attributed to the limited regional response of monsoon in observations but the extensive and exaggerated response in predictions due partially to the application of ensemble average forecasting methods. In contrast, in spite of a similar deficiency, the Southeast Asian monsoon can still be forecasted reasonably, probably because of its closer relationship with large-scale circulation patterns and E1 Nifio-Southern Oscillation.
基金supported by the National Natural Science Foundation of China (Grant Nos.41305057, 41275076, 41105069, and 41375081)the National Basic Research Program of China (Grant Nos.2010CB951903 and 2014CB953900)the LCS Youth Fund (2014)
文摘Using hindcasts of the Beijing Climate Center Climate System Model, the relationships between interannual variability （IAV） and intraseasonal variability （ISV） of the Asian-western Pacific summer monsoon are diagnosed. Predictions show reasonable skill with respect to some basic characteristics of the ISV and IAV of the western North Pacific summer monsoon （WNPSM） and the Indian summer monsoon （ISM）. However, the links between the seasonally averaged ISV （SAISV） and seasonal mean of ISM are overestimated by the model. This deficiency may be partially attributable to the overestimated frequency of long breaks and underestimated frequency of long active spells of ISV in normal ISM years, although the model is capable of capturing the impact of ISV on the seasonal mean by its shift in the probability of phases. Furthermore, the interannual relationships of seasonal mean, SAISV, and seasonally averaged long-wave variability （SALWV; i.e., the part with periods longer than the intraseasonal scale） of the WNPSM and ISM with SST and low-level circulation are examined. The observed seasonal mean, SAISV, and SALWV show similar correlation patterns with SST and atmospheric circulation, but with different details. However, the model presents these correlation distributions with unrealistically small differences among different scales, and it somewhat overestimates the teleconnection between monsoon and tropical central-eastern Pacific SST for the ISM, but underestimates it for the WNPSM, the latter of which is partially related to the too-rapid decrease in the impact of E1 Nifio-Southern Oscillation with forecast time in the model.
基金jointly supported by the National Natural Science Foundation of China (Grant Nos.41275077 and 41105054)the National Basic Research Program of China (973 Program:2010CB951902)+1 种基金the China Meteorological Administration (Grant Nos.GYHY201106022 and GYHY201306048)the Sun Yat-sen University "985 Project", Phase 3
文摘ABSTRACT The abilities of BCC-AGCM2.1 and BCC_AGCM2.2 to simulate the annual-mean cloud vertical structure （CVS） were evaluated through comparison with GCM-Oriented CALIPSO Cloud Product （CALIPSO-GOCCP） data. BCC-AGCM2.2 has a dynamical core and physical processes that are consistent with BCC-AGCM2.1, but has a higher horizontal resolution. Results showed that both BCC-AGCM versions underestimated the global-mean total cloud cover （TCC）, middle cloud cover （MCC） and low cloud cover （LCC）, and that BCC_AGCM2.2 underestimated the global-mean high cloud cover （HCC）. The global-mean cloud cover shows a systematic decrease from BCCA-GCM2.1 to BCC_AGCM2.2, especially for HCC. Geographically, HCC is significantly overestimated in the tropics, particularly by BCC_AGCM2,1, while LCC is generally overestimated over extra-tropical lands, but significantly underestimated over most of the oceans, especially for subtropical marine stratocumulus clouds. The leading EOF modes of CVS were extracted. The BCC_AGCMs perform well in reproducing EOF1, but with a larger variance explained. The two models also capture the basic features of EOF3, except an obvious deficiency in eigen- vector peaks. EOF2 has the largest simulation biases in both position and strength of eigenvector peaks. Furthermore, we investigated the effects of CVS on relative shortwave and longwave cloud radiative forcing （RSCRF and RLCRF）. Both BCC_AGCM versions successfully reproduce the sign of regression coefficients, except for RLCRF in PC1. However, the RSCRF relative contributions from PC1 and PC2 are overestimated, while the relative contribution from PC3 is underes timated in both BCC_AGCM versions. The RLCRF relative contribution is underestimated for PC2 and overestimated for PC3.
