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.
WANG FangXIN XiaogeWANG ZaizhiCHENG YanjieZHANG JieYANG Song
The historical simulation of phase five of the Coupled Model Intercomparison Project （CMIP5） ex- periments performed by the Beijing Climate Center cli- mate system model （BCC_CSM1.1） is evaluated regard- ing the time evolutions of the global and China mean sur- face air temperature （SAT） and surface climate change over China in recent decades. BCC CSM1.1 has better capability at reproducing the time evolutions of the global and China mean SAT than BCC_CSM1.0. By the year 2005, the BCC_CSM1.1 model simulates a warming am- plitude of approximately I℃ in China over the 1961- 1990 mean, which is consistent with observation. The distributions of the warming trend over China in the four seasons during 1958-2004 are basically reproduced by BCC CSM1.1, with the warmest occurring in winter. Al- though the cooling signal of Southwest China in spring is partly reproduced by BCC_CSM1.1, the cooling trend over central eastern China in summer is omitted by the model. For the precipitation change, BCC_CSM1.1 has good performance in spring, with drought in Southeast China. After removing the linear trend, the interannual correlation map between the model and the observation shows that the model has better capability at reproducing the summer SAT over China and spring precipitation over Southeast China.
