| The global warming caused by the greenhouse effect has always been a hot spot to the international community.Carbon dioxide(CO2)in the atmosphere as the main greenhouse gas is an important factor that causes the greenhouse effect.In order to study the distribution of atmospheric CO2 and global CO2 changes and formulate a reasonable CO2 emission reduction policy,high-precision CO2 detection is required.Ground-based detection methods have high measurement accuracy,but they have problems with space-based detection,such as narrow detection range and insufficient data volume,so ground-based and space-based observation methods cannot meet the global atmospheric CO2 measurement requirements.Satellite-based remote sensing methods based on space-based measurements can achieve high-frequency worldwide detection with their orbit altitude and revisit time.At present,a number of atmospheric greenhouse gas remote sensing satellites have been launched internationally for greenhouse gas monitoring and climate change research.To meet the actual application requirements,the measurement accuracy of satellite remote sensing must be higher than 1%.Therefore,high-precision CO2 inversion is the key to the application of remote sensing satellites.Environmental parameters such as atmospheric aerosols,surface reflectivity and cloud pollution are important factors that affect the accuracy of CO2 inversion.For remote sensing data of satellites in orbit,the detected data must be effectively screened.Based on the remote sensing of the Greenhouse gases Monitoring Instrument(GMI)carried on the China's GF-5 satellite,this paper develops a screening technology for atmospheric conditions and cloud pollution data based on data quality requirements to screen out remote sensing data suitable for CO2 retrieval.Secondly,the technology of acquiring and matching external environmental parameters necessary for CO2 inversion such as surface reflectance and atmospheric environmental was developed.At the same time,in order to meet the needs of high-quality inversion,the spectral correction and radiation quantization of the remote sensing spectrum were processed.On this basis,construct a CO2 inversion method.In order to realize the demand for GMI massive remote sensing data inversion and application,based on the technical characteristics of the satellite remote sensing ground data processing system,complete the design of each algorithm module,the corresponding CO2 inversion software was developed in combination with the above inversion methods.This articles uses the ground station points of the Total Carbon Column Observing Network(TCCON),the Greenhouse gases Observing Satellite(GOSAT)currently in orbit and the Orbiting Carbon Observatory-2(OCO-2)verified the GMI inversion results and selected the observation data from August 2018 to March 2019 for comparison.The results show that the GMI SWIR XCO2 is biased low by-1.21±2.26ppm(-0.3±0.55%)and the inversion accuracy is within 1%.From the correlation comparison between GMI and GOSAT satellites,it can be concluded that the overall average deviation of the measurement data is 0.19ppm,the correlation is 0.65,and the overall average deviation of the GMI and OCO-2 satellite measurement data is-0.12ppm,the correlation is 0.62.For the GMI load,the atmospheric CO2 inversion results constructed by the research method of this paper can meet the related research needs. |
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