• 关键词：PM_2.5  WRF-Chem  气象因子  长三角地区  四维资料同化（FDDA）

• 基金项目：中国气象局西北人工影响天气工程能力建设项目（No.ZQC-R19081，ZQC-R19176）

• 熊一帆
• 南京信息工程大学大气物理学院，南京 210044;南京信息工程大学精细化区域地球模拟和信息中心，南京 210044

• 丁秋冀
• 南京信息工程大学大气物理学院，南京 210044;南京信息工程大学精细化区域地球模拟和信息中心，南京 210044

• 舒卓智
• 南京信息工程大学大气物理学院，南京 210044;南京信息工程大学精细化区域地球模拟和信息中心，南京 210044

• 刘玉宝
• 南京信息工程大学大气物理学院，南京 210044;南京信息工程大学精细化区域地球模拟和信息中心，南京 210044

• 赵天良
• 南京信息工程大学大气物理学院，南京 210044;南京信息工程大学精细化区域地球模拟和信息中心，南京 210044

• 摘要：细颗粒物（PM_2.5）累积主导着长三角地区冬季空气污染，其中，气象要素具有重要的作用.本文结合WRF-Chem模式和WRF-FDDA技术，针对2019年1月12—16日发生在长三角地区的一次典型PM_2.5污染过程进行数值模拟分析.通过敏感性试验，量化分析地面气象因素（温度、风速、相对湿度）对该地区PM_2.5浓度的影响，并利用对自动气象站观测资料的四维资料同化试验，探究气象场改进对PM_2.5模拟的改善.模拟结果表明，长三角地区PM_2.5污染受气象条件影响程度较为显著，PM_2.5浓度与风速和温度呈显著负相关，与相对湿度呈正相关.水平风速减少40%、温度增加3 ℃、相对湿度增加20%分别造成了+4.68%、-2.82%与+2.2%的PM_2.5浓度变化.而同化气象资料显著地改善了模拟的气象场 精度，其均方根误差（RMSE）统计项中相对湿度减小9.68%，温度减小1.02 ℃，风速减小0.35 m·s^-1，这也使得PM_2.5浓度的模拟效果有所改善，其中，模拟与观测PM_2.5浓度的相关系数提高了0.11，RMSE减小9.17 μg·m^-3.气象要素变化对大气污染物影响的量化研究，以及资料同化对PM_2.5模拟的改进，可促进大气污染的预报水平和有效控制.

• Abstract：Accumulation of fine particulate matter （PM_2.5） is responsible to winter air pollution in the Yangtze River Delta （YRD） region and meteorological factors play an important role. In this study， the chemistry version of the Weather Research and Forecasting model （WRF-Chem） and the four-dimensional data assimilation （WRF-FDDA） scheme were employed to simulate a typical heavy pollution event occurred in the YRD region from January 12 to 16， 2019. The impact of near-surface temperature， wind speed， and relative humidity disturbances on the surface PM_2.5 was analyzed by carrying out a series of sensitivity experiments. A four-dimensional data assimilation experiment with WRF-FDDA that assimilates automatic weather station observation data was also conducted to demonstrate the improvements of the meteorological field modeling as well as that of PM_2.5 concentration by the data assimilation process. The results show that in the YRD region， the PM_2.5 concentration has a negative correlation with wind speed and temperature， but a positive correlation with relative humidity. In the three sensitivity experiments with horizontal wind speed is decreased by 40%， temperature is increased by 3 ℃， and relative humidity is increased by 20% respectively， the corresponding PM_2.5 concentrations were affected by +4.68%， -2.82%， and +2.2%. By assimilating meteorological observations， the accuracy of the meteorological simulation is significantly improved. The root mean square error （RMSE） of relative humidity， temperature and wind speed decreases by 9.68%， 1.02 ℃， and 0.35 m·s^-1， respectively. The correlation coefficient between the observed and simulated PM_2.5 increased by 0.11 and RMSE decreased by 9.17 μg·m^-3. These results are valuable to further improve the forecast accuracy and support effective control of air pollution in the YRD region.

• Key words：PM_2.5  WRF-Chem  meteorological factors  Yangtze River Delta region  four-dimensional data assimilation（FDDA）

• 
  摘要点击次数： 266 全文下载次数： 367