Optimization of the photon path length probability density function-simultaneous (PPDF-S) method and evaluation of CO 2 retrieval performance under dense aerosol conditions
| Autor: | Andrey Bril, Chisa Iwasaki, Sergey Oshchepkov, Tatsuya Yokota, Vyacheslav I. Zakharov, K. G. Gribanov, Ryoichi Imasu, Yukio Yoshida, Nikita Rokotyan |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
photon path length probability density function (PPDF)
010504 meteorology & atmospheric sciences PROBABILITY DENSITY FUNCTION RETRIEVAL PERFORMANCE PHOTON PATH LENGTH PROBABILITY DENSITY FUNCTION (PPDF) SHORT-WAVELENGTH INFRARED lcsh:Chemical technology PHOTONS 01 natural sciences Biochemistry Analytical Chemistry carbon dioxide (CO2) CARBON DIOXIDE lcsh:TP1-1185 Instrumentation retrieval Atomic and Molecular Physics and Optics Wavelength PROBABILITY LIGHT REFLECTION Infrared window Cirrus FOURIER TRANSFORM SPECTROMETERS GREENHOUSE GASES SPACECRAFT INSTRUMENTS ATMOSPHERIC TRANSMITTANCE GREENHOUSE GASES OBSERVING SATELLITE (GOSAT) RETRIEVAL CONSTRAINT CONDITIONS Probability density function 010309 optics ATMOSPHERIC THERMODYNAMICS SHORT WAVELENGTH INFRARED (SWIR) Path length AEROSOLS GREENHOUSE GASES OBSERVING SATELLITES 0103 physical sciences Electrical and Electronic Engineering DENSITY OF GASES PHOTON PATH LENGTH 0105 earth and related environmental sciences Remote sensing greenhouse gases observing satellite (GOSAT) FOURIER TRANSFORM INFRARED SPECTROSCOPY Scattering Aerosol INFRARED RADIATION ATMOSPHERIC AEROSOLS Environmental science Satellite short wavelength infrared (SWIR) aerosols CARBON DIOXIDE (CO 2 ) |
| Zdroj: | Sensors (Switzerland) Sensors, Vol 19, Iss 5, p 1262 (2019) Sensors Volume 19 Issue 5 |
| Popis: | The photon path length probability density function-simultaneous (PPDF-S) algorithm is effective for retrieving column-averaged concentrations of carbon dioxide (XCO 2 ) and methane (XCH 4 ) 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 XCO 2 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 CO 2 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 XCO 2 adversely. By optimizing the constraint, it was possible to obtain a stable solution of XCO 2 . The new optimization was applied to retrieval analysis of the GOSAT data measured in Western Siberia. First, we assumed clear sky conditions and retrieved XCO 2 from GOSAT data obtained near Yekaterinburg in the target area. The retrieved XCO 2 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 CO 2 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. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. Russian Science Foundation: 18-11-00024 Acknowledgments: The v3.0 ACOS/OCO-2 absorption coefficient (ABSCO) tables, used for the calculation of gas absorption coefficients, were provided by NASA and the ACOS/OCO-2 project. Vyacheslav Zakharov, Konstantin Gribanov, and Nikita Rokotyan thank the Russian Science Foundation for support of their research under the framework of grant 18-11-00024. |
| Databáze: | OpenAIRE |
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