摘要
China’s Fengyun-3D meteorological satellite launched in December 2016 carries the high-resolution greenhouse-gases absorption spectrometer(GAS)aimed at providing global observations of carbon dioxide(CO_(2)).To date,GAS is one of the few instruments measuring CO_(2) from the near-infrared spectrum.On orbit,the oxygen(O_(2))A band suffers a disturbance,and the signal-to-noise ratio(SNR)is significantly lower than the nominal specification.This leads to difficulties in the retrieval of surface pressure and hence a degradation of the retrieval of the column-averaged CO_(2) dry air mole fraction(XCO_(2))if a full physics retrieval algorithm is used.Thus,a fast CO_(2) inverse method,named semi-physical statistical algorithm,was developed to overcome this deficiency.The instrument characteristics,the semi-physical statistical algorithm,and the results of comparison with ground-based measurements over land were introduced in this paper.XCO_(2) can be obtained from three bands,namely,the O_(2) A,weak CO_(2),and strong CO_(2) bands,with compensation from the Medium Resolution Spectral Imager-2(MERSI-2)products,ECMWF Reanaly-sis v5(ERA-5)data,and Total Carbon Column Observing Network(TCCON)data.The eigenvectors of covariance matrices and the least square fits were used to derive retrieval coefficients and yield cloud-free solutions.In addition to the GAS radiance,some key factors necessary for the accurate estimations of XCO_(2) were also taken as input information(e.g.,air mass,surface pressure,and a priori XCO_(2)).The global GAS XCO_(2) restricted over land was compared against the simultaneously collocated observations from TCCON.The retrieval algorithm can mitigate the issue caused by the low SNR of the O_(2) A band to a certain extent.Overall,through site-by-site comparisons,GAS XCO_(2) agreed well with the average precision(1σ)of 1.52 ppm and bias of−0.007 ppm.The seasonal variation trends of GAS XCO_(2) can be clearly seen at TCCON sites on the 1-yr timescale.
基金
Supported by the Civil Aerospace Technology Pre Research Project(D040301)。