日本地球惑星科学連合2019年大会

講演情報

[J] 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-AS04] 大気化学

2019年5月30日(木) 13:45 〜 15:15 ポスター会場 (幕張メッセ国際展示場 8ホール)

コンビーナ:中山 智喜(長崎大学 大学院水産・環境科学総合研究科)、岩本 洋子(広島大学 生物圏科学研究科)、豊田 栄(東京工業大学物質理工学院)、江口 菜穂(Kyushu University)

[AAS04-P28] Global inverse analysis of CH4 fluxes using NICAM-TM 4D-Var

*丹羽 洋介1,2伊藤 昭彦1町田 敏暢1笹川 基樹1遠嶋 康徳1梅澤 拓1森本 真司3青木 周司3澤 庸介2坪井 一寛2松枝 秀和2Ed Dlugokencky4Christina Harth5Paul Krummel6Ray Langenfelds6Zoe Loh6Jens Mühle5Simon O’Doherty7Ronald Prinn8Michel Ramonet9Peter Salameh5Colm Sweeney4Ray Weiss5Dickon Young7Simona Castaldi10,11Sergio Noce12Marielle Saunois9Ann Stavert13 (1.国立環境研究所、2.気象研究所、3.東北大学、4.Earth System Research Laboratory, National Oceanic and Atmospheric Administration、5.Scripps Institution of Oceanography, University of California、6.Climate Science Centre, CSIRO Oceans and Atmosphere、7.School of Chemistry, University of Bristol、8.Massachusetts Institute of Technology、9.Laboratoire des Sciences du Climat et de l’Environnement, LSCE-IPSL (CEA-CNRS-UVSQ)、10.DISTABIF, Università degli studi della Campania Luigi Vanvitelli、11.Department Landscape Design & Sustainable Ecosystems RUDN University、12.IAFES, Euro-Mediterranean Center on Climate Change、13.Global Carbon Project, CSIRO Oceans and Atmosphere)

キーワード:メタン、逆解析

Atmospheric methane (CH4) is the most important greenhouse gas after carbon dioxide. Because CH4 has a relatively short lifetime due to chemical losses in the atmosphere, it is expected that reducing CH4 emissions would mitigate global warming in a relatively short timeframe. However, sources of atmospheric CH4 are associated with a wide variety of processes such as fossil fuel production and consumption, agriculture, natural wetlands, and biomass burning, and our understanding of the full CH4 budget is limited. To better understand CH4 sources, an inverse analysis is one prominent methodology that estimates spatiotemporal variations of CH4 sources consistent with their prior estimates and atmospheric observations within specified uncertainties. In this study, we performed a long-term inverse analysis of CH4 fluxes with an inversion system named NICAM-TM 4D-Var (Niwa et al., 2017a,b). The inversion system is based on the atmospheric transport model NICAM-TM (Niwa et al., 2011), which has a homogeneous icosahedral grid system and mass conserving property. The horizontal model grid resolution was set to 223 km and the CH4 flux estimation was performed at the same resolution, though some spatial error correlations were introduced. The prior flux dataset includes wetland/rice cultivation emission and soil uptake estimated by the terrestrial ecosystem model VISIT (Ito and Inatomi, 2012). The other emission categories are provided from the ongoing Global Carbon Project (GCP)–CH4. In the inversion, several emission categories are separately estimated according to their seasonal and interannual variabilities. Compared with the prior estimates, the inverse analysis with ground-based station data estimated smaller emissions from East Asia and Europe, larger and smaller northern summer emissions from West Siberia and Hudson Bay Lowlands, respectively, and larger emissions from Bengal and Indochina areas. These changes estimated by the inversion are attributed to emissions from anthropogenic categories (mainly fossil fuel related), natural wetlands, and rice cultivation, respectively. The presentation will also address the reliability of the inversion estimates using independent aircraft data and examine the independence of each category emission estimate.


References
Niwa et al. (2011), Journal of the Meteorological Society of Japan. Ser. II, 89(3), 255–268.
Ito and Inatomi (2012), Biogeoscience, 9:759-773.
Niwa et al. (2017a), Geoscientific Model Development, 10(3), 1157–1174.
Niwa et al. (2017b), Geoscientific Model Development, 10(6), 2201–2219.

Acknowledgement
This study is supported by the Environment Research and Technology Development Fund (2-1701) of the Ministry of the Environment, Japan. The authors acknowledge the Global Carbon Project–CH4 for providing the prior flux dataset, some of which is made under the support of the RUDN project "5-100". The authors also acknowledge Doug Worthy of Environmental Canada, Juha Hatakka of Finnish Meteorological Institute, Camille Yver Kwok of Laboratoire des Sciences du Climat et de l’Environnement, Sebastien Conil of Andra, and Kazuyuki Saito and other members of Japan Meteorological Agency for providing observational data of atmospheric CH4. This study used observational data of Advanced Global Atmospheric Gases Experiment (AGAGE). Operations of the AGAGE network are principally supported by the NASA Upper Atmospheric Research Program in the US, by the Department for Business, Energy & Industrial Strategy (BEIS) in the UK, by the Commonwealth Scientific and Industrial Research Organization (CSIRO) and the Bureau of Meteorology (Australia) in Australia, with additional support from the National Oceanographic and Atmospheric Administration (NOAA) in the US. Yosuke Niwa sincerely thanks the members of the NICAM team for developing and maintaining the codes of NICAM.