1961—2005年中国区域性低温事件的观测、再分析与模拟的比较研究

Comparison Research of the Results in Observation, NCEP Reanalysis Data and BCC-CSM1.1 Modeling Data for China■s Regional Low Temperature Events During 1961-2005

利用1961—2005年观测、NCEP再分析资料和北京气候中心发展的气候系统模式1.1版本(BCC-CSM1.1)模拟的逐日最低气温资料,首先采用优选格点回归方法将网格资料降尺度到台站上,然后再应用区域性极端事件客观识别法对3套资料识别得到中国区域性低温事件。分析表明,NCEP再分析资料很好地再现了最低气温的实况;BCC-CSM1.1模式对日最低气温的模拟尽管总体上不如NCEP再分析资料,但模拟效果也较好。NCEP再分析资料在中国区域性低温事件的长期趋势、年际变化以及累积强度和发生频次的空间分布上都较好地再现了实况。BCC-CSM1.1模式对中国区域性低温事件的模拟结果显示,该模式较好地模拟出1961—2005年中国区域性低温事件在频次、极端强度、最大影响面积、持续时间、累积面积和综合强度等各项指标所表现出的一致的减小趋势;对事件累积强度和发生频次空间分布的模拟,总体上较好地反映了观测的主要特征,但对中心位置的模拟存在一定偏差。

Daily minimum temperature datasets of observation stations, the NCEP reanalysis data were used in this study to assess the BCC-CSMI. 1 modeling data over China. Firstly, the grid data were downscaled to observational stations with the Optimal Points Regression （OPR） method, and then China＇s regional low temperature events were identified from the three datasets using the Objective Identification Technique for Regional Extreme Events （OITREE）. Results show that the NCEP reanalysis data show very good consistency with the observational daily minimum temperatures, while the BCC-CSM1.1 generally also shows a good ability in modeling the daily minimum temperatures, although its modeled data are not as good as the NCEP reanalysis data. For China＇s regional low temperature events, the NCEP reanalysis data show very good consistency with the observations in the long-term trend and interannual variation, and the spatial distributions of accumulated intensity and frequency. Meanwhile, the BCC-CSM1.1 simulations show good consistency with the observations in the decreasing tendencies in frequency, extreme intensity, maximum impacted area, duration, accumulated impacted area and integrated index of China＇s regional low temperature events during 1961 2005. In addition, the BCC-CSM 1.1 model overall shows good ability in modeling the main characteristics of the spatial distributions of the accumulated intensity and frequency of China＇s regional low temperature events, but relatively poor ability in modeling the locations of the high-value centers.