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Optimization of the Photon Path Length Probability Density Function-Simultaneous (PPDF-S) Method and Evaluation of CO2 Retrieval Performance Under Dense Aerosol Conditions

1
Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa 277-8568, Japan
2
Institute of Physics of National Academy of Sciences of Belarus, 68 Prospekt Nezavisimosti, Minsk BY-220072, Belarus
3
National Institute for Environmental Studies, Onogawa 16-2, Tsukuba 305-8506, Japan
4
Laboratory of Climate and Environmental Physics, Ural Federal University, Lenina Ave. 51, Yekaterinburg 620083, Russia
5
Institute of Mathematics and Mechanics, UB RAS, S.Kovalevskay Street, 16, Yekaterinburg 620990, Russia
*
Author to whom correspondence should be addressed.
Department of Information Networking for Innovation and Design, Faculty of Information Networking for Innovation and Design, Toyo University, 1-7-11 Akabanedai, Kita-ku, Tokyo 115-0053, Japan.
Sensors 2019, 19(5), 1262; https://doi.org/10.3390/s19051262
Received: 10 November 2018 / Revised: 28 February 2019 / Accepted: 6 March 2019 / Published: 12 March 2019
(This article belongs to the Special Issue Advanced Hyper-Spectral Imaging, Sounding and Applications from Space)
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Abstract

The photon path length probability density function-simultaneous (PPDF-S) algorithm is effective for retrieving column-averaged concentrations of carbon dioxide (XCO2) and methane (XCH4) from Greenhouse gases Observing Satellite (GOSAT) spectra in Short Wavelength InfraRed (SWIR). Using this method, light-path modification attributable to light reflection/scattering by atmospheric clouds/aerosols is represented by the modification of atmospheric transmittance according to PPDF parameters. We optimized PPDF parameters for a more accurate XCO2 retrieval under aerosol dense conditions based on simulation studies for various aerosol types and surface albedos. We found a more appropriate value of PPDF parameters referring to the vertical profile of CO2 concentration as a measure of a stable solution. The results show that the constraint condition of a PPDF parameter that represents the light reflectance effect by aerosols is sufficiently weak to affect XCO2 adversely. By optimizing the constraint, it was possible to obtain a stable solution of XCO2. The new optimization was applied to retrieval analysis of the GOSAT data measured in Western Siberia. First, we assumed clear sky conditions and retrieved XCO2 from GOSAT data obtained near Yekaterinburg in the target area. The retrieved XCO2 was validated through a comparison with ground-based Fourier Transform Spectrometer (FTS) measurements made at the Yekaterinburg observation site. The validation results showed that the retrieval accuracy was reasonable. Next, we applied the optimized method to dense aerosol conditions when biomass burning was active. The results demonstrated that optimization enabled retrieval, even under smoky conditions, and that the total number of retrieved data increased by about 70%. Furthermore, the results of the simulation studies and the GOSAT data analysis suggest that atmospheric aerosol types that affected CO2 analysis are identifiable by the PPDF parameter value. We expect that we will be able to suggest a further improved algorithm after the atmospheric aerosol types are identified. View Full-Text
Keywords: aerosols; carbon dioxide (CO2); greenhouse gases observing satellite (GOSAT); photon path length probability density function (PPDF); retrieval; short wavelength infrared (SWIR) aerosols; carbon dioxide (CO2); greenhouse gases observing satellite (GOSAT); photon path length probability density function (PPDF); retrieval; short wavelength infrared (SWIR)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Iwasaki, C.; Imasu, R.; Bril, A.; Oshchepkov, S.; Yoshida, Y.; Yokota, T.; Zakharov, V.; Gribanov, K.; Rokotyan, N. Optimization of the Photon Path Length Probability Density Function-Simultaneous (PPDF-S) Method and Evaluation of CO2 Retrieval Performance Under Dense Aerosol Conditions. Sensors 2019, 19, 1262.

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