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• W2898983111 abstract "We present further development of the empirical orthogonal functions (EOF)-based retrieval algorithm. The algorithm output is a regression formula that relates principal components of the reflected sunlight spectra with CO2 total column amount. The algorithm was implemented and tested for the observations from the Japanese satellite Greenhouse gases Observing Satellite (GOSAT). Training of the EOF-based algorithm with the collocated ground-based and space-borne data (e.g., Total Carbon Column Observing Network and GOSAT observations, respectively) was shown to impose some errors that were interpreted as a result of implicit averaging over the collocation area. Alternative training with the small subset (∼5 % to 10%) of the full-physics algorithm is free of such errors; however, this option requires additional filtering of the space-borne observations that are strongly affected by atmospheric light scattering. This filtering was implemented by the comparison of the EOF-regression estimates of surface pressure with corresponding meteorological data." @default.
• W2898983111 created "2018-11-09" @default.
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• W2898983111 date "2018-10-31" @default.
• W2898983111 modified "2023-10-03" @default.
• W2898983111 title "Development of the empirical orthogonal functions-based algorithm for the retrievals of atmospheric CO2 total column amount from space-borne observations of reflected sunlight" @default.
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• W2898983111 doi "https://doi.org/10.1117/1.jrs.12.046012" @default.
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