Development of CMAQ for East Asia CO_2 data assimilation under an EnKF framework: a first result  

作　　者：Zhekun Huang Zhen Peng Hongnian Liu Meigen Zhang Xiaoguang Ma Shu-Chih Yang Sang-Deok Lee Seung-Yeon Kim 

机构地区：[1]School of Atmospheric Sciences, Nanjing University [2]State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics,Chinese Academy of Sciences [3]RIKEN Advanced Institute for Computational Science,Kobe 650-0047, Japan [4]National Institute of Environmental Research, Incheon 404-708,Republic of Korea

出　　处：《Chinese Science Bulletin》2014年第25期3200-3208,共9页

基　　金：supported by the Strategic Priority Research Program–Climate Change: Carbon Budget and Relevant Issues (XDA05040404);the National Natural Science Foundation of China (41130528);the National High Technology Research and Development Program of China (2013AA122002);the National Basic Research Program of China (2010CB428501);the Priority Academic Program Development of Jiangsu Higher Education Institutions

摘　　要：Under an Ensemble Kalman Filter(EnKF)framework,Regional Atmospheric Modeling System and Models-3 Community Multi-scale Air Quality(RAMS–CMAQ)modeling system is developed to be a CO2data assimilation system EnKF–CMAQ,and the EnKF–CMAQ system is then applied to East Asia for validation with real continuous surface CO2concentration observations available in the study domain instead of using an observation simulation system experiment.Experiments with an experimental period of January 23 to February 7,2007 are conducted,and the experimental results of the EnKF–CMAQ system and the RAMS–CMAQ model are compared against continuous surface CO2observations from assimilation sites and independent reference sites.Distributions of daily mean CO2concentration increments show that the EnKF–CMAQ system confines the update of daily mean CO2within areas nearby and downwind of the assimilation sites.Both the CO2concentration ensemble spreads and background error covariances show flow-dependent patterns.The results indicate the crucial role of wind transport in the CO2data assimilation,which agrees with the previous studies.The average bias and the average root-mean-square error(RMSE)of daily mean CO2concentration at the assimilation sites are reduced by 1.00 and1.83 ppm,respectively,and those at the reference sites are reduced by 0.24 and 0.22 ppm,respectively.The results demonstrate the EnKF–CMAQ system is capable of assimilating the continuous surface CO2concentration observations to improve the simulation accuracy of the atmospheric CO2synoptic variation.Since growing CO2observations over East Asia are being available nowadays,this work is our first step to generate consistent spatial and temporal atmospheric CO2concentration fields over East Asia,particularly over China,using both in situ and satellite observations.Under an Ensemble Kalman Filter （EnKF） framework, Regional Atmospheric Modeling System and Models-3 Community Multi-scale Air Quality （RAMS- CMAQ） modeling system is developed to be a CO2 data assimilation system EnKF-CMAQ, and the EnKF-CMAQ system is then applied to East Asia for validation with real continuous surface CO2 concentration observations avail- able in the study domain instead of using an observation simulation system experiment, Experiments with an experimental period of January 23 to February 7, 2007 are conducted, and the experimental results of the EnKFCMAQ system and the RAMS-CMAQ model are compared against continuous surface CO2 observations from assimilation sites and independent reference sites. Distributions of daily mean COg concentration increments show that the EnKF-CMAQ system confines the update of daily mean CO2 within areas nearby and downwind of the assimilation sites. Both the CO2 concentration ensemble spreads and background error covariances show flow-dependent patterns. The results indicate the crucial role of wind transport in the CO2 data assimilation, which agrees with the previous studies. The average bias and the average root-mean-square error （RMSE） of daily mean CO2 concentration at the assimilation sites are reduced by 1.00 and 1.83 ppm, respectively, and those at the reference sites are reduced by 0.24 and 0.22 ppm, respectively. The results demonstrate the EnKF-CMAQ system is capable of assimilating the continuous surface CO2 concentration observations to improve the simulation accuracy of the atmospheric CO2 synoptic variation. Since growing CO2 observations over East Asia are being available nowadays, this work is our first step to generate consistent spatial and temporal atmospheric CO2 concentration fields over East Asia, particularly over China, using both in situ and satellite observations.

关 键 词：大气CO2浓度 卡尔曼滤波 数据同化 集合 区域大气模拟系统 东亚 框架 开发 

分 类 号：P435[天文地球—大气科学及气象学]