Next Article in Journal
3-D Convolution-Recurrent Networks for Spectral-Spatial Classification of Hyperspectral Images
Next Article in Special Issue
Increase of Atmospheric Methane Observed from Space-Borne and Ground-Based Measurements
Previous Article in Journal
Towards Uniform Point Density: Evaluation of an Adaptive Terrestrial Laser Scanner
Previous Article in Special Issue
Analysis of Four Years of Global XCO2 Anomalies as Seen by Orbiting Carbon Observatory-2
Article Menu
Issue 7 (April-1) cover image

Export Article

Open AccessArticle

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

Finnish Meteorological Institute, 00560 Helsinki, Finland
Karlsruhe Institute of Technology (KIT), IMK-IFU, 82467 Garmisch-Partenkirchen, Germany
SRON, Netherlands Institute for Space Research, 3584 CA Utrecht, The Netherlands
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong NSW 2522, Australia
NOAA ESRL Global Monitoring Division, Boulder, CO 80305-3328, USA
Karlsruhe Institute of Technology (KIT), IMK-ASF, 76021 Karlsruhe, Germany
Finnish Meteorological Institute, 99600 Sodankylä, Finland
National Institute for Environmental Studies (NIES), Tsukuba 305-0053, Japan
Institute of Environmental Physics, University of Bremen, 28359 Bremen, Germany
National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder, Omakau 9352, New Zealand
California Institute of Technology, Pasadena, CA 91125, USA
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), B-1180 Brussels, Belgium
Department of Physics, University of Toronto, Toronto, ON M5S 1A7, Canada
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(7), 882;
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)
PDF [7525 KB, uploaded 12 April 2019]
  |     |  


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

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

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.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top