Real-data assimilation experiment with a joint data assimilation system: assimilating carbon dioxide mole fraction measurements from the Greenhouse gases Observing Satellite

The performance of a joint data assimilation system（Tan-Tracker）,which is based on the PODEn4 Dvar assimilation method,in assimilating Greenhouse gases Observing SATellite（GOSAT） carbon dioxide（CO2） data,was evaluated.Atmospheric 3D CO2 concentrations and CO2 surface fluxes（CFs） from2010 were simulated using a global chemistry transport model（GEOS-Chem）.TheTan-Tracker system used the simulated CO2 concentrations and fluxes as a background field and assimilated the GOSAT column average dry-air mole fraction of CO2（X（CO2）） data to optimize CO2 concentrations and CFs in the same assimilation window.Monthly simulated X（CO2）（X（CO2）Sim）） and assimilated X（CO2）（X（CO2）,TT） data retrieved at different satellite scan positions were compared with GOSAT-observed X（CO2）（X（CO2）,obs）data.The average RMSE between the monthly X（CO2）,TT and X（CO2）,Obs data was significantly（30%） lower than the average RMSE between X（CO2）,Sim and X（CO2）,Obs）.Specifically,reductions in error were found for the positions of northern Africa（the Sahara）,the Indian peninsula,southern Africa,southern North America,and western Australia.The difference between the correlation coefficients of the X（CO2）,Sim）and X（CO2）,Obs and those of the X（CO2）Π）,TT and X（CO2）,Obs was only small.In general,the Tan-Tracker system performed very well after assimilating the GOSAT data.

Tan-Tracker碳卫星资料联合数据同化系统是针对即将发射的中国的碳卫星TANSat,并基于先进数据同化算法PODEn4DVar,同时采用了联合数据同化的策略,紧扣碳卫星资料同化的这一国际前沿开发的面向科研和应用的碳卫星资料同化系统。本文设计运行了Tan-Tracker碳卫星资料联合数据同化系统同化GOSAT卫星CO_2浓度观测的真实同化实验,并评估了Tan-Tracker碳同化系统的可行性和有效性。经过同化后的结果与模式模拟结果同观测对比,均方根误差有了明显的下降(约30%),特别是在地面观测严重缺失的非洲北部、印度半岛、南部非洲、美国南部、澳大利亚西部等地;同时与观测的相关系数并无很大的差异。总体而言,Tan-Tracker碳同化系统成功完成真实数据同化并有较好的结果。