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Evaluation and Analysis of the Seasonal Cycle and Variability of the Trend from GOSAT Methane Retrievals

Kivimäki, Ella and Lindqvist, Hannakaisa and Hakkarainen, Janne and Laine, Marko and Sussmann, Ralf and Tsuruta, Aki and Detmers, Rob and Deutscher, Nicholas M. and Dlugokencky, Edward J. and Hase, Frank and Hasekamp, Otto and Kivi, Rigel and Morino, Isamu and Notholt, Justus and Pollard, David F. and Roehl, Coleen and Schneider, Matthias and Sha, Mahesh Kumar and Velazco, Voltaire A. and Warneke, Thorsten and Wunch, Debra and Yoshida, Yukio and Tamminen, Johanna (2019) Evaluation and Analysis of the Seasonal Cycle and Variability of the Trend from GOSAT Methane Retrievals. Remote Sensing, 11 (7). Art. No. 882. ISSN 2072-4292. https://resolver.caltech.edu/CaltechAUTHORS:20190415-093533763

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Abstract

Methane (CH_4) is a potent greenhouse gas with a large temporal variability. To increase the spatial coverage, methane observations are increasingly made from satellites that retrieve the column-averaged dry air mole fraction of methane (XCH_4). To understand and quantify the spatial differences of the seasonal cycle and trend of XCH_4 in more detail, and to ultimately help reduce uncertainties in methane emissions and sinks, we evaluated and analyzed the average XCH_4 seasonal cycle and trend from three Greenhouse Gases Observing Satellite (GOSAT) retrieval algorithms: National Institute for Environmental Studies algorithm version 02.75, RemoTeC CH_4 Proxy algorithm version 2.3.8 and RemoTeC CH_4 Full Physics algorithm version 2.3.8. Evaluations were made against the Total Carbon Column Observing Network (TCCON) retrievals at 15 TCCON sites for 2009–2015, and the analysis was performed, in addition to the TCCON sites, at 31 latitude bands between latitudes 44.43°S and 53.13°N. At latitude bands, we also compared the trend of GOSAT XCH_4 retrievals to the NOAA’s Marine Boundary Layer reference data. The average seasonal cycle and the non-linear trend were, for the first time for methane, modeled with a dynamic regression method called Dynamic Linear Model that quantifies the trend and the seasonal cycle, and provides reliable uncertainties for the parameters. Our results show that, if the number of co-located soundings is sufficiently large throughout the year, the seasonal cycle and trend of the three GOSAT retrievals agree well, mostly within the uncertainty ranges, with the TCCON retrievals. Especially estimates of the maximum day of XCH_4 agree well, both between the GOSAT and TCCON retrievals, and between the three GOSAT retrievals at the latitude bands. In our analysis, we showed that there are large spatial differences in the trend and seasonal cycle of XCH_4. These differences are linked to the regional CH_4 sources and sinks, and call for further research.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.3390/rs11070882DOIArticle
http://www.temis.nl/climate/methane.htmlRelated ItemTropospheric Emission Monitoring Internet Service
https://doi.org/10.14291/tccon.archive/1348407DOITCCON Data Archive
https://github.com/mjlaine/dlmRelated ItemMatlab codes for DLM
https://github.com/mjlaine/mcmcstatRelated ItemMatlab codes MCMC
ORCID:
AuthorORCID
Deutscher, Nicholas M.0000-0002-2906-2577
Dlugokencky, Edward J.0000-0003-0612-6985
Morino, Isamu0000-0003-2720-1569
Pollard, David F.0000-0001-9923-2984
Roehl, Coleen0000-0001-5383-8462
Velazco, Voltaire A.0000-0002-1376-438X
Warneke, Thorsten0000-0001-5185-3415
Wunch, Debra0000-0002-4924-0377
Yoshida, Yukio0000-0002-3515-1488
Additional Information:© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Received: 22 February 2019; Accepted: 9 April 2019; Published: 11 April 2019. This study was partially funded by the Finnish Meteorological Institute, the Academy of Finland’s Carbon Balance under Changing Processes of Arctic and Subarctic Cryosphere (CARB-ARC) project (285630), the Academy of Finland’s Centre of Excellence in Inverse Modelling and Imaging (312125), and European Union’s Horizon 2020 Gap Analysis for Integrated Atmospheric ECV CLImate Monitoring (GAIA-CLIM) project (No 640276). Ella Kivimäki acknowledges funding from Tiina and Antti Herlin Foundation (Project No. 20180222). Hannakaisa Lindqvist acknowledges funding from the Academy of Finland via project number 285421. Rob Detmers acknowledges funding from the ESA Climate Change Initiative Greenhouse Gases project. The TCCON site at Réunion Island is operated by the Royal Belgian Institute for Space Aeronomy with financial support in 2014, 2015, 2016, and 2017 under the EU project ICOS-Inwire and the ministerial decree for ICOS (FR/35/IC2) and local activities supported by LACy/UMR8105—Université de La Réunion. TCCON work at Sodankylä has been supported by the ESA FRM4GHG, EU GAIA-CLIM and EU RINGO projects. Nicholas Deutscher is funded by Australian Research Council, grants DE140100178 and FT180100327. TCCON measurements at Wollongong and Darwin are supported by ARC grants LE0668470, DP0879467, DP110103118, DP140101552 and DP160101598, with further support from NASA grants NAG6-12247 and NNGOS-GDO7G. We greatly thank all of the data providers. NIES Level 2 observations are available through the GOSAT RA project. The RemoTeC retrievals were provided by Tropospheric Emission Monitoring Internet Service hosted by KNMI, from website at http://www.temis.nl/climate/methane.html. TCCON data were obtained from the TCCON Data Archive, hosted by CaltechDATA, California Institute of Technology, CA (US), doi:10.14291/tccon.archive/1348407. We thank Shuji Kawakami for providing the XCH4 data from Saga. The Matlab codes for DLM and MCMC analyses are available at https://github.com/mjlaine/dlm and https://github.com/mjlaine/mcmcstat, respectively. We acknowledge Laura Thölix for potential vorticity calculations for Sodankylä. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
Funders:
Funding AgencyGrant Number
Finnish Meteorological InstituteUNSPECIFIED
Academy of Finland285630
Academy of Finland312125
European Research Council (ERC)640276
Tiina and Antti Herlin Foundation20180222
Academy of Finland285421
European Space Agency (ESA)UNSPECIFIED
Royal Belgian Institute for Space AeronomyUNSPECIFIED
European UnionFR/35/IC2
Université de La RéunionLACy/UMR8105
European Space Agency (ESA)FRM4GHG
Australian Research CouncilDE140100178
Australian Research CouncilFT180100327
Australian Research CouncilLE0668470
Australian Research CouncilDP0879467
Australian Research CouncilDP110103118
Australian Research CouncilDP140101552
Australian Research CouncilDP160101598
NASANAG6-12247
NASANNGOS-GDO7G
Subject Keywords:greenhouse gas; remote sensing; methane; seasonal cycle; trend; GOSAT; TCCON
Issue or Number:7
Record Number:CaltechAUTHORS:20190415-093533763
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190415-093533763
Official Citation:Kivimäki, E.; Lindqvist, H.; Hakkarainen, J.; Laine, M.; Sussmann, R.; Tsuruta, A.; Detmers, R.; Deutscher, N.M.; Dlugokencky, E.J.; Hase, F.; Hasekamp, O.; Kivi, R.; Morino, I.; Notholt, J.; Pollard, D.F.; Roehl, C.; Schneider, M.; Sha, M.K.; Velazco, V.A.; Warneke, T.; Wunch, D.; Yoshida, Y.; Tamminen, J. Evaluation and Analysis of the Seasonal Cycle and Variability of the Trend from GOSAT Methane Retrievals. Remote Sens. 2019, 11, 882
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:94701
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:16 Apr 2019 21:48
Last Modified:09 Mar 2020 13:19

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