期刊
JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER
卷 189, 期 -, 页码 258-266出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jqsrt.2016.12.005
关键词
Carbon dioxide; Retrieval algorithm; Empirical orthogonal function; GOSAT; TCCON
资金
- Belarusian Republican Foundation for Fundamental Research (BRFFR) [F15CO-023]
- Tomsk State University Academic D.I. Mendeleev Fund Program under the Grant of the Ministry for Education and Science of the Russian Federation [5.628.2014/K]
- NASA [NNX14AI60G, NNX11AG01G, NAG5-12247, NNG05-GD07G]
- NASA Orbiting Carbon Observatory Program
- Australian Research Council [DP140101552, DP110103118, DP0879468, LP0562346]
- Australian Research Council-Discovery Early Career Researcher Award [DE140100178]
- Academy of Finland [140408]
- EU under project GAIA-CLIM [640276]
- EU within INGOS
- ESA ghg-cci project
- EU projects InGOS [284274]
- ICOS-INWIRE [313169]
- Senate of Bremen
- RAMCES team at LSCE
- NIVVA through New Zealand's Ministry of Business, Innovation and Employment
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. (C) 2016 Elsevier Ltd. All rights reserved.
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