{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T10:46:11Z","timestamp":1774521971748,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T00:00:00Z","timestamp":1623196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003629","name":"Korea Meteorological Administration","doi-asserted-by":"publisher","award":["KMA2018-00222"],"award-info":[{"award-number":["KMA2018-00222"]}],"id":[{"id":"10.13039\/501100003629","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Understanding the temporal variability of atmospheric methane (CH4) and its potential drivers can advance the progress toward mitigating changes to the climate. To comprehend interannual variability and spatial characteristics of anomalous CH4 mole fractions and its drivers, we used integrated data from different platforms such as in situ measurements and satellites (TROPOspheric Monitoring Instrument (TROPOMI) and Greenhouse Gases Observing SATellite (GOSAT)) retrievals. A pronounced change of annual growth rate was detected at Anmyeondo (AMY), Republic of Korea, ranging from \u221216.8 to 31.3 ppb yr\u22121 as captured in situ through 2015\u20132020 and 3.9 to 16.4 ppb yr\u22121 detected by GOSAT through 2014\u20132019, respectively. High growth rates were discerned in 2016 (31.3 ppb yr\u22121 and 13.4 ppb yr\u22121 from in situ and GOSAT, respectively) and 2019 (27.4 ppb yr\u22121 and 16.4 ppb yr\u22121 from in situ and GOSAT, respectively). The high growth in 2016 was essentially explained by the strong El Ni\u00f1o event in 2015\u20132016, whereas the large growth rate in 2019 was not related to ENSO. We suggest that the growth rate that appeared in 2019 was related to soil temperature according to the Noah Land Surface Model. The stable isotopic composition of 13C\/12C in CH4 (\u03b413-CH4) collected by flask-air sampling at AMY during 2014\u20132019 supported the soil methane hypothesis. The intercept of the Keeling plot for summer and autumn were found to be \u221253.3\u2030 and \u221252.9\u2030, respectively, which suggested isotopic signature of biogenic emissions. The isotopic values in 2019 exhibited the strongest depletion compared to other periods, which suggests even a stronger biogenic signal. Such changes in the biogenic signal were affected by the variations of soil temperature and soil moisture. We looked more closely at the variability of XCH4 and the relationship with soil properties. The result indicated a spatial distribution of interannual variability, as well as the captured elevated anomaly over the southwest of the domain in autumn 2019, up to 70 ppb, which was largely explained by the combined effect of soil temperature and soil moisture changes, indicating a pixel-wise correlation of XCH4 anomaly with those parameters in the range of 0.5\u20130.8 with a statistical significance (p &lt; 0.05). This implies that the soil-associated drivers are able to exert a large-scale influence on the regional distribution of CH4 in Korea.<\/jats:p>","DOI":"10.3390\/rs13122266","type":"journal-article","created":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T14:16:04Z","timestamp":1623248164000},"page":"2266","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Interannual Variability of Atmospheric CH4 and Its Driver Over South Korea Captured by Integrated Data in 2019"],"prefix":"10.3390","volume":"13","author":[{"given":"Samuel Takele","family":"Kenea","sequence":"first","affiliation":[{"name":"Innovative Meteorological Research Department, National Institute of Meteorological Sciences (NIMS), 33, Seohobuk-ro, Seogwipo-si 63568, Jeju-do, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0121-8525","authenticated-orcid":false,"given":"Haeyoung","family":"Lee","sequence":"additional","affiliation":[{"name":"Innovative Meteorological Research Department, National Institute of Meteorological Sciences (NIMS), 33, Seohobuk-ro, Seogwipo-si 63568, Jeju-do, Korea"}]},{"given":"Sangwon","family":"Joo","sequence":"additional","affiliation":[{"name":"Innovative Meteorological Research Department, National Institute of Meteorological Sciences (NIMS), 33, Seohobuk-ro, Seogwipo-si 63568, Jeju-do, Korea"}]},{"given":"Shanlan","family":"Li","sequence":"additional","affiliation":[{"name":"Innovative Meteorological Research Department, National Institute of Meteorological Sciences (NIMS), 33, Seohobuk-ro, Seogwipo-si 63568, Jeju-do, Korea"}]},{"given":"Lev","family":"Labzovskii","sequence":"additional","affiliation":[{"name":"R&D Satellite and Observations Group, Royal Netherlands Meteorological Institute (KNMI), 3731GA De Bilt, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5330-9456","authenticated-orcid":false,"given":"Chu-Yong","family":"Chung","sequence":"additional","affiliation":[{"name":"Innovative Meteorological Research Department, National Institute of Meteorological Sciences (NIMS), 33, Seohobuk-ro, Seogwipo-si 63568, Jeju-do, Korea"}]},{"given":"Yeon-Hee","family":"Kim","sequence":"additional","affiliation":[{"name":"Innovative Meteorological Research Department, National Institute of Meteorological Sciences (NIMS), 33, Seohobuk-ro, Seogwipo-si 63568, Jeju-do, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wu, X., Zhang, X., Chuai, X., Huang, X., and Wang, Z. 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