, I., Velazco, V. et al (2017). EOF-based regression algorithm for the fast retrieval of atmospheric CO2 total column amount from the GOSAT observations. Journal of Quantitative Spectroscopy and Radiative Transfer, 189 258-266.EOF-based regression algorithm for the fast retrieval of atmospheric CO2 total column amount from the GOSAT observations 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.Keywords amount, eof-based, regression, algorithm, fast, gosat, retrieval, observations, atmospheric, co2, total, column
Disciplines
Medicine and Health Sciences | Social and Behavioral Sciences
Publication DetailsBril, A., Maksyutov, S., Belikov, D., Oshchepkov, S., Yoshida, Y., Deutscher, N. M., Griffith, D., Hase, F., Kivi, R., Morino, I., Velazco, V. et al (2017). EOF-based regression algorithm for the fast retrieval of atmospheric CO2 total column amount from the GOSAT observations. IMK-IFU, Garmisch-Partenkirchen 82467, Germany *Corresponding author: andrey.bril@gmail.com 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 2 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.