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Open AccessArticle

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

1
Finnish Meteorological Institute, 00560 Helsinki, Finland
2
Karlsruhe Institute of Technology (KIT), IMK-IFU, 82467 Garmisch-Partenkirchen, Germany
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SRON, Netherlands Institute for Space Research, 3584 CA Utrecht, The Netherlands
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Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong NSW 2522, Australia
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NOAA ESRL Global Monitoring Division, Boulder, CO 80305-3328, USA
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Karlsruhe Institute of Technology (KIT), IMK-ASF, 76021 Karlsruhe, Germany
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Finnish Meteorological Institute, 99600 Sodankylä, Finland
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National Institute for Environmental Studies (NIES), Tsukuba 305-0053, Japan
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Institute of Environmental Physics, University of Bremen, 28359 Bremen, Germany
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National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder, Omakau 9352, New Zealand
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California Institute of Technology, Pasadena, CA 91125, USA
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Royal Belgian Institute for Space Aeronomy (BIRA-IASB), B-1180 Brussels, Belgium
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Department of Physics, University of Toronto, Toronto, ON M5S 1A7, Canada
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(7), 882; https://doi.org/10.3390/rs11070882
Received: 22 February 2019 / Revised: 25 March 2019 / Accepted: 9 April 2019 / Published: 11 April 2019
(This article belongs to the Special Issue Remote Sensing of Carbon Dioxide and Methane in Earth’s Atmosphere)
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. View Full-Text
Keywords: greenhouse gas; remote sensing; methane; seasonal cycle; trend; GOSAT; TCCON greenhouse gas; remote sensing; methane; seasonal cycle; trend; GOSAT; TCCON
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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.

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