Extended range simulations of the extreme snow storms over southern China in early 2008 with the BCC_AGCM2.1 model. Issue 15 (5th August 2013) - Huang, Anning; Zhang, Yaocun; Wang, Zaizhi; Wu, Tongwun; Huang, Danqing; Zhou, Yang; Zhao, Yong; Huang, Ying; Kuang, Xueyuan; Zhang, Lujun; Fang, Yongjie; Guo, Yan
Abstract : [1] The 10–30 day extended range potential predictability of the Beijing Climate Center Atmospheric General Circulation Model version 2.1 (BCC_AGCM2.1) model with high horizontal resolution has been evaluated, and the associated influencing factors and possible physical mechanisms have been discussed through a case study of the long‐lasting extreme snow storms over southern China in early 2008. Comparison with meteorological observations suggests that the BCC_AGCM2.1 model forced by the real daily sea surface temperature (SST) well reproduced the extraordinarily frequent and long‐lasting heavy snow storm process over southern China in early 2008 including the spatial distribution and temporal evolution of the 2 m air temperature and snow rainfall but produced relatively larger errors in precipitation. Overall, the BCC‐AGCM2.1 model forced by the real daily SST shows good potential predictability on 10–30 day extended range time scale to some extent, at least from this extreme snow storm case study. Further analysis of the associated influencing factors and possible physical mechanisms indicates that the SST forcing is not as important as the initial conditions for the weather forecast within around 2 weeks in advance which is the upper limit of the daily weather forecast. However, the SST forcing with relatively larger day‐to‐day variability plays an important role in the potential predictability of the BCC_AGCM2.1 model on 10–30 day extended forecasting time scale through affecting the atmospheric variability. Results from this study provide us some necessary and valuable information for further development of an operational 10–30 day extended range forecasting system. Key Points: BCC_AGCM2.1 model forced by real SST shows good extended range predictability The SCP subseasonal variability correlates with the SST day‐to‐day variability The SST day‐to‐day variability plays a key role in the extended range forecasts