In this study,the Chinese carbon cyle dataassimilation system Tan-Tracker is developed based on the atmospheric chemical transport model(GEOS-Chem)platform.Tan-Tracker is a dual-pass data-assimilation system in which ...In this study,the Chinese carbon cyle dataassimilation system Tan-Tracker is developed based on the atmospheric chemical transport model(GEOS-Chem)platform.Tan-Tracker is a dual-pass data-assimilation system in which both CO2concentrations and CO2fluxes are simultaneously assimilated from atmospheric observations.It has several advantages,including its advanced data-assimilation method,its highly efficient computing performance,and its simultaneous assimilation of CO2concentrations and CO2fluxes.Preliminary observing system simulation experiments demonstrate its robust performance with high assimilation precision,making full use of observations.The Tan-Tracker system can only assimilate in situ observations for the moment.In the future,we hope to extend Tan-Tracker with functions for using satellite measurements,which will form the quasioperational Chinese carbon cycle data-assimilation system.展开更多
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 eva...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.展开更多
基金supported by the Strategic Priority Research Program-Climate Change: Carbon Budget and Relevant Issues (XDA05040200)the National High Technology Research and Development Program of China (Grant No. 2013AA122002)+1 种基金the National Natural Science Foundation of China (41075076)the Knowledge Innovation Program of the Chinese Academy of Sciences (KZCX2-EW-QN207)
文摘In this study,the Chinese carbon cyle dataassimilation system Tan-Tracker is developed based on the atmospheric chemical transport model(GEOS-Chem)platform.Tan-Tracker is a dual-pass data-assimilation system in which both CO2concentrations and CO2fluxes are simultaneously assimilated from atmospheric observations.It has several advantages,including its advanced data-assimilation method,its highly efficient computing performance,and its simultaneous assimilation of CO2concentrations and CO2fluxes.Preliminary observing system simulation experiments demonstrate its robust performance with high assimilation precision,making full use of observations.The Tan-Tracker system can only assimilate in situ observations for the moment.In the future,we hope to extend Tan-Tracker with functions for using satellite measurements,which will form the quasioperational Chinese carbon cycle data-assimilation system.
基金partially supported by the National High Technology Research and Development Program of China[grant number 2013AA122002]the National Natural Science Foundation of China[grant numbers 41575100 and 91437220]+1 种基金the Knowledge Innovation Program of the Chinese Academy of Sciences[grant number KZCX2-EW-QN207]the Special Fund for Meteorological Scientific Research in Public Interest[grant number GYHY201506002]
文摘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.
