Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa 277-8568, Japan.
Institute of Physics of National Academy of Sciences of Belarus, 68 Prospekt Nezavisimosti, Minsk BY-220072, Belarus.
Sensors (Basel). 2019 Mar 12;19(5):1262. doi: 10.3390/s19051262.
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.
光子路径长度概率密度函数-同步（PPDF-S）算法可有效地从温室气体观测卫星（GOSAT）在短波红外（SWIR）谱中检索二氧化碳（XCO₂）和甲烷（XCH₄）的柱平均浓度。使用该方法，根据 PPDF 参数修改大气透过率来表示归因于大气云和/气溶胶光反射/散射的光程修正。我们针对不同的气溶胶类型和地表反照率进行了模拟研究，优化了 PPDF 参数，以在气溶胶密集条件下更准确地检索 XCO₂。我们发现，通过将 CO₂浓度的垂直廓线作为稳定解的度量，PPDF 参数具有更合适的值。结果表明，代表气溶胶光反射效应的 PPDF 参数的约束条件弱到不会对 XCO₂产生不利影响。通过优化约束条件，可以获得稳定的 XCO₂解。新的优化应用于在西西伯利亚测量的 GOSAT 数据的检索分析。首先，我们假设晴空条件，并从目标区域叶卡捷琳堡附近获得的 GOSAT 数据中检索 XCO₂。通过与叶卡捷琳堡观测点的地面傅里叶变换光谱仪（FTS）测量值进行比较，对检索到的 XCO₂进行了验证。验证结果表明，检索精度是合理的。接下来，我们将优化方法应用于生物质燃烧活跃时的密集气溶胶条件。结果表明，即使在烟雾弥漫的情况下，优化也能进行检索，并且检索到的数据总数增加了约 70%。此外，模拟研究和 GOSAT 数据分析的结果表明，通过 PPDF 参数值可以识别影响 CO₂分析的大气气溶胶类型。我们期望在识别大气气溶胶类型后，能够提出进一步改进的算法。
