日本地球惑星科学連合2016年大会

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インターナショナルセッション(ポスター発表)

セッション記号 A (大気水圏科学) » A-AS 大気科学・気象学・大気環境

[A-AS01] Global Carbon Cycle Observation and Analysis

2016年5月24日(火) 17:15 〜 18:30 ポスター会場 (国際展示場 6ホール)

コンビーナ:*三枝 信子(国立環境研究所)、Patra Prabir(Research Institute for Global Change, JAMSTEC)、町田 敏暢(国立環境研究所)、茶谷 聡(国立環境研究所)

17:15 〜 18:30

[AAS01-P08] Validation of GOSAT SWIR XCO2 and XCH4 retrieved by PPDF-S method

*岩﨑 千沙1林田 佐智子2今須 良一1横田 達也3森野 勇3吉田 幸生3 (1.東京大学大気海洋研究所、2.奈良女子大学、3.国立環境研究所)

キーワード:GOSAT, retrieval, carbon dioxide, methane

We focused on column averaged dry air mole fraction of atmospheric CO2 and CH4 (XCO2 and XCH4, respectively) retrievals from Greenhouse gases Observing Satellite (GOSAT) measurements through the photon path length probability density function (PPDF-S) based retrieval method that simultaneously retrieves target gas abundance and PPDF parameters. This method is used for an effective retrieval algorithm even under high concentration of clouds and aerosols. First, we validated PPDF-S XCO2 and XCH4 retrievals by comparing them with ground-based observations provided by the Total Carbon Column Observing Network (TCCON) from June 2009 to May 2014. For comparison, we also validate retrievals through another algorithm using full physics (FP)-based retrieval method. PPDF-S and FP retrieval methods are different in way to account for light scattering effect. All these XCO2 and XCH4 retrievals are provided by the National Institute for Environmental Studies (NIES). PPDF-S retrievals have positive biases (0.47 ± 2.11 ppm for XCO2 and 0.76 ± 15.49 ppb for XCH4), on the other hand, FP retrievals have negative biases (-0.28 ± 2.34 ppm for XCO2 and -2.16 ± 13.26 ppb for XCH4). Next, we compare global maps of XCO2 and XCH4 mean value, standard deviation and number of data between PPDF-S and FP retrievals. Over the ocean, PPDF-S method can retrieve large number of data whose standard deviation is larger than FP method. These PPDF-S retrievals over the ocean include data which are eliminated in post-screening process for FP method to exclude data that are strongly affected by clouds and aerosol.