大气环境数值模拟研究新进展

近五年来，中国科学院大气物理研究所(简称大气所)在大气环境数值模拟方面取得了丰硕的成果，通过自主发展和引进，建立了完备的多尺度、多成分的大气环境数值模式，包括全球大气化学输送模式、区域和城市空气质量预报模式。大气所利用这些模式研究各种空间尺度上污染物浓度时空分布以及污染物的输送和演变，研究了多种污染过程的成因和污染变化规律，在污染物输送、低对流层臭氧高污染、区域及城市污染等方面取得了很多成果，并对区域或城市空气质量进行业务化实时预报。大气所还拓展了我国大气环境模拟研究的新领域:大气化学资料同化、污染模式集合预报、污染源反演新方法。初步建立了空气质量模式的资料同化系统(分别基于最优插值技术和集合卡曼滤波技术)和多模式集合预报体系，提高了模式预报水平；在污染源反演新方法方面进行了初步的探索。结合我国目前仍然面临着的大气环境问题，对今后大气环境数值模式的发展方向进行了展望。

IAP Progress in Atmospheric Environment Modeling Research

This paper provides a comprehensive,critical review of the most important research progress in atmospheric environment modeling research in the Institute of Atmospheric Physics,Chinese Academy of Sciences(IAP/CAS) during recent five years.Multi-scale,mixed compositions atmospheric environment models have been independently developed or introduced,which include the global atmospheric chemical transport model,the regional and urban air quality model.Distribution,transportation and evolution of pollutants at different spatial scales are explored with these models.Understandings of natural and anthropogenic pollutants' transport,surface high ozone episode,and regional or urban pollution are improved.The real-time forecast model system for air quality is developed and used in a region or cities.It is firstly concerned in China that atmospheric chemical assimilation,chemical transport model ensemble forecast,ensemble estimation method for inversing modeling of pollution emissions.Data assimilation systems for nested air quality prediction model based on the optimal interpolation approach and Ensemble Kalman Filter(EnKF),respectively,and a multi-model ensemble forecast system are developed,improving the forecast skill.Some new ensemble estimation methods for inversing modeling of pollution emissions are introduced.A prospect is given about numerical simulation of atmospheric environment.