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Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003-2018) for carbon and climate applications

Reuter, Maximilian; Buchwitz, Michael; Schneising, Oliver; Noël, Stefan; Bovensmann, Heinrich; Burrows, John P.; Boesch, Hartmut; Di Noia, Antonio; Anand, Jasdeep; Parker, Robert J.; Somkuti, Peter; Wu, Lianghai; Hasekamp, Otto P.; Aben, Ilse; Kuze, Akihiko; Suto, Hiroshi; Shiomi, Kei; Yoshida, Yukio; Morino, Isamu; Crisp, David; ... mehr

Abstract:
Satellite retrievals of column-averaged dry-air mole fractions of carbon dioxide (CO$_{2}$) and methane (CH$_{4}$), denoted XCO$_{2}$ and XCH$_{4}$, respectively, have been used in recent years to obtain information on natural and anthropogenic sources and sinks and for other applications such as comparisons with climate models. Here we present new data sets based on merging several individual satellite data products in order to generate consistent long-term climate data records (CDRs) of these two Essential Climate Variables (ECVs). These ECV CDRs, which cover the time period 2003–2018, have been generated using an ensemble of data products from the satellite sensors SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT and (for XCO$_{2}$) for the first time also including data from the Orbiting Carbon Observatory 2 (OCO-2) satellite. Two types of products have been generated: (i) Level 2 (L2) products generated with the latest version of the ensemble median algorithm (EMMA) and (ii) Level 3 (L3) products obtained by gridding the corresponding L2 EMMA products to obtain a monthly 5°x5°data product in Obs4MIPs (Observations for Model Intercomparisons Project) format. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000117820
Veröffentlicht am 20.03.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung - Atmosphärische Spurenstoffe und Fernerkundung (IMK-ASF)
Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 1867-8548
KITopen-ID: 1000117820
Erschienen in Atmospheric measurement techniques
Band 13
Heft 2
Seiten 789–819
Vorab online veröffentlicht am 19.02.2020
Nachgewiesen in Web of Science
Scopus
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