EOF-based regression algorithm for the fast retrieval of atmospheric CO2 total column amount from the GOSAT observations. (March 2017) - Bril, Аndrey; Maksyutov, Shamil; Belikov, Dmitry; Oshchepkov, Sergey; Yoshida, Yukio; Deutscher, Nicholas M.; Griffith, David; Hase, Frank; Kivi, Rigel; Morino, Isamu; Notholt, Justus; Pollard, David F.; et al.
Abstract: This paper presents a novel retrieval algorithm for the rapid retrieval of the carbon dioxide total column amounts from high resolution spectra in the short wave infrared (SWIR) range observations by the Greenhouse gases Observing Satellite (GOSAT). The algorithm performs EOF (Empirical Orthogonal Function)-based decomposition of the measured spectral radiance and derives the relationship of limited number of the decomposition coefficients in terms of the principal components with target gas amount and a priori data such as airmass, surface pressure, etc. The regression formulae for retrieving target gas amounts are derived using training sets of collocated GOSAT and ground-based observations. The precision/accuracy characteristics of the algorithm are analyzed by the comparison of the retrievals with those from the Total Carbon Column Observing Network (TCCON) measurements and with the modeled data, and appear similar to those achieved by full-physics retrieval algorithms. Highlights: An algorithm is developed for rapid CO2 retrieval from the reflected Sun light spectra. Gas amounts are derived from the principal components of the measured spectra. The algorithm is adapted for the Greenhouse gases Observing Satellite data processing. The algorithm precision and accuracy are similar to ones of the full-physics algorithms.