Da Liu, L. Lei, Min Liu, Lijie Guo, Qian Wang, Nian Bie
{"title":"Effectiveness analysis of ACOS-Xco2 bias correction method with GEOS-Chem model results","authors":"Da Liu, L. Lei, Min Liu, Lijie Guo, Qian Wang, Nian Bie","doi":"10.1117/12.2204821","DOIUrl":null,"url":null,"abstract":"Satellite observations and model simulations are of two important data sources to study atmospheric carbon dioxide concentration. For analyzing and evaluating the bias correction method of ACOS dry-air column averaged CO2 (Xco2) product, the GEOS-Chem Xco2 simulations are selected according to observing time and locations of the ACOS product. The GEOS-Chem simulations of CO2 profiles are transformed to Xco2 data by convolving with satellite averaging kernels and pressure weighting functions. The GEOS-Chem Xco2 data are then compared with both bias uncorrected and bias corrected satellite retrievals of ACOS. The comparisons show that the bias uncorrected ACOS retrievals are on average 1.12ppm higher than the model Xco2 data, while the corrected ACOS retrievals are only on average 0.06ppm lower than the model Xco2 data. By assuming consistency between model Xco2 simulations and true atmospheric Xco2, this study indicates that the bias can be obvious decreased through the bias correction method, and the correction is effective and necessary for satellite Xco2 retrievals.","PeriodicalId":340728,"journal":{"name":"China Symposium on Remote Sensing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"China Symposium on Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2204821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Satellite observations and model simulations are of two important data sources to study atmospheric carbon dioxide concentration. For analyzing and evaluating the bias correction method of ACOS dry-air column averaged CO2 (Xco2) product, the GEOS-Chem Xco2 simulations are selected according to observing time and locations of the ACOS product. The GEOS-Chem simulations of CO2 profiles are transformed to Xco2 data by convolving with satellite averaging kernels and pressure weighting functions. The GEOS-Chem Xco2 data are then compared with both bias uncorrected and bias corrected satellite retrievals of ACOS. The comparisons show that the bias uncorrected ACOS retrievals are on average 1.12ppm higher than the model Xco2 data, while the corrected ACOS retrievals are only on average 0.06ppm lower than the model Xco2 data. By assuming consistency between model Xco2 simulations and true atmospheric Xco2, this study indicates that the bias can be obvious decreased through the bias correction method, and the correction is effective and necessary for satellite Xco2 retrievals.