Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
846968 | Optik - International Journal for Light and Electron Optics | 2016 | 4 Pages |
The global carbon dioxide hyperspectral remote sensing inversion system GF_VRTM is established for the greenhouse gas carbon dioxide remote sensing detection of GF-5 satellite. The validation and error analysis of global inversion is performed by using GF_VRTM with 21 June 2013 observation data of GOSAT-FTS in this study. The simulation results show that the CO2 averaged column concentrations (XCO2) overall trends are basically identical between GF_VRTM retrievals and GOSAT-FTS observations. There are 138 exposure points in whole observation points, and the relative error less than 2% is about 85%. The mean square error is 5.00 ppm, but the global average error is 1.09 ppm. If the assumption that GOSAT-FTS observation data is true, GF_VRTM satisfies the average precision requirements (less than 1%) of XCO2 global inversion. For the results of the comparison, the minimum error scenario and maximum error scenario are selected for error analysis. Error sources are smooth error, measurement noise error, the forward model parameter error and forward model error, respectively. For the minimum error scenario and maximum error scenario, the relative error of XCO2 inversion caused by smooth error and measurement noise error are 0.44% and −1.62%, respectively, and the relative error of XCO2 inversion caused by the forward model parameter error are −0.43% and −1.53%, respectively. At the same time, the forward model error is ignored.