宋佳琨,陈耀登,陈丹. 2021. 气象-气溶胶资料联合同化对秋季PM2.5模拟的影响研究[J]. 气象学报, (0):-, doi:10.11676/qxxb2021.026
气象-气溶胶资料联合同化对秋季PM2.5模拟的影响研究
Study of meteorology-aerosol joint data assimilation on autumn PM2.5 simulation
投稿时间:2020-09-29  修订日期:2020-12-10
DOI:10.11676/qxxb2021.026
中文关键词:  WRF/Chem,GSI,PM2.5,气象-气溶胶联合资料同化,气象条件,华北平原
英文关键词:WRF/Chem,GSI,PM2.5,meteorology-aerosol joint data assimilation,meteorology condition,North China Plain
基金项目:国家重点基础研究发展计划
作者单位邮编
宋佳琨 南京信息工程大学大气科学学院 210044
陈耀登 南京信息工程大学大气科学学院 210044
陈丹 北京城市气象研究院 100089
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中文摘要:
      [目的]相比于冬季大范围静稳条件下的污染堆积过程,秋季气象条件更为复杂和局地,气象条件模拟不确定性给秋季气溶胶模拟带来了更大难度,且目前研究较少考虑气溶胶-气象在线模拟和联合同化。[资料和方法]使用WRF/Chem模式和GSI三维变分同化系统,进行了2015年10月为期一个月的气象-气溶胶资料联合同化及模拟试验,并基于此讨论了气象-气溶胶资料联合同化对秋季PM2.5模拟的影响。[结果]结果表明,WRF/Chem模式可以模拟出我国区域秋季污染天气过程,但在华北平原和中东部存在着高估,西北部存在低估;同化地面PM2.5观测可以改进对PM2.5的模拟,上述地区两个方向的偏差均得到订正,6小时预报偏差均降低至6 μg/m3以内;重点针对华北地区分析表明,秋季PM2.5污染过程与特殊气象条件(湿度增加、风场辐合、区域输送)密切相关,因此在地面PM2.5同化基础上增加常规气象资料同化,能进一步提高华北平原气象-污染过程表达,PM2.5预报相关系数从0.86提高至0.89。[结论]气象-气溶胶联合资料同化能更加准确地模拟中国地区秋季气溶胶污染过程,为更好地开展污染成因和在气象预报框架下开展气溶胶-气象相互影响研究提供了基础。
英文摘要:
      Compared with the pollution accumulation process under the stable conditions in winter, the autumn meteorological conditions are more complex and local. The uncertainty of the meteorological condition simulation brings greater difficulty to the autumn aerosol simulation, and the online meteorology-aerosol joint assimilation are rarely considered in the current model simulation. WRF/Chem model and GSI three dimensions variational data assimilation system were used to carry out 4 groups of simulation and assimilation experiments (in 6-hour cycle frequency) for October 2015, and the influences of meteorology-aerosol joint data assimilation on autumn aerosol simulation were discussed. Results showed that WRF/Chem could simulate the regional air pollution events in autumn in China, but there were overestimates/underestimates in the Middle East/Northwest China. Assimilation of PM2.5 observation improved the simulation results, and the 6-hour forecast deviation was reduced to less than 6μg/m3. For the North China Plain,PM2.5 pollution in autumn was closely related to special meteorological conditions, e.g. high humidity, convergence of wind field, and regional transport. Therefore, the assimilation of conventional meteorological data in addition to surface PM2.5 assimilation better captured the meteorology-pollution process and the correlation coefficient of PM2.5 forecast was increased from 0.86 to 0.89. Joint meteorology-aerosol data assimilation can help to more accurately simulate autumn aerosol pollution process in China, thus better serving scientific researches about pollution mechanism and meteorology-aerosol interaction under the framework of meteorological forecast.
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