BCC-AGCM-Chem0模式对20世纪对流层臭氧变化趋势的模拟研究

Variations of Tropospheric Ozone in the 20^(th) Century Simulated by BCC-AGCM-ChemO Model

利用IPCC第5阶段试验计划(CMIP5)整理提供的全球臭氧(O_3)分析资料和全球O_3和紫外线辐射数据中心(WOJDC)提供的O_3台站观测资料评估了国家气候中心最新发展的全球大气化学环流模式BCC-AGCM-Chem0对对流层大气O_3变化趋势的模拟能力。结果表明,BCC-AGCM—Chem0模式对对流层O_3的变化趋势具有较好的模拟能力,具体表现在:(1)BCC-AGCM—Chem0模式可以较好地模拟出1871-1999年全球对流层不同高度O_3浓度逐渐升高的基本特征;(2)BCC—AGCM-Chem0模式对1871-1999全球对流层O_3柱浓度纬圈平均异常变化的模拟与CMIP5资料一致,北半球升高趋势明显大于南半球,且升高最大区域的中心位置和强度也与CMIP5资料一致;(3)BCC-AGCM—Chem0模式对1000~300 hPa整体O_3柱浓度变化趋势模拟较好,对O_3柱浓度快速上升的区域和上升速度的模拟都与CMIP5资料一致,但对低层O_3柱浓度升高模拟偏强,对高层O_3柱浓度变化模拟偏弱;(4)与台站观测资料对比,在对流层中低层模拟结果在亚洲Sapporo站和欧洲Hohenpeissenberg站与实际观测比较接近,并与CMIP5资料相似,均呈升高趋势。对流层中高层模式模拟的O_3浓度异常存在明显的周期变化,与台站观测结果一致。

The global chemistry-general circulation model BCC-AGCM-Chem0,newly developed in Beijing Climate Center,is evaluated using the data provided by CMIP5 and WOUDC.BCC-AGCM-Chem0 can simulate the variations of tropospheric ozone well.The increasing trend of ozone concentration at different heights in the troposphere simulated by BCC-AGCM-Chem0 is in a good agreement with the CMIP5 data.BCC-AGCMChem0 can well capture zonal mean of concentration of ozone column anomalies in the troposphere from 1871 to1999.Increasing trend in the Northern Hemisphere is higher than that in the Southern Hemisphere,the location and intensity of the strongest increasing trend are agree with CMIP5 data.Spatial distributions of the trend of the concentration of ozone column integrated from 1000 to 300 hPa from 1871 to 1999 are also well reproduced.In comparison with the CMIP5 data,BCC-AGCM-Chem0 overestimated the trend of the concentration of ozone column at lower troposphere,and underestimated it at higher troposphere.The ozone concentrations show increasing trends at Sapporo station in Asia and Hohenpeissenberg station in Europe at lower troposphere,the model results are closed to the ground-based data,and closed to CMIP5 data as well.In the upper and middle troposphere,ozone concentrations anomalies simulated by BCC-AGCM-Chem0 show distinct periodic variations,consistent with the ground-based data.