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Ability of the 4-D-Var analysis of the GOSAT BESD XCO₂ retrievals to characterize atmospheric CO₂ at large and synoptic scales

Massart, S.; Agusti-Panareda, A.; Heymann, J.; Buchwitz, M.; Chevallier, F.; Reuter, M.; Hilker, M.; Burrows, J.P.; Deutscher, N.M.; Feist, D.G.; Hase, F.; Sussmann, R.; Desmet, F.; Dubey, M.K.; Griffith, D.W.T.; Kivi, R.; Petri, C.; Schneider, M.; Velazco, V.A.

This study presents results from the European Centre for Medium-Range Weather Forecasts (ECMWF) carbon dioxide (CO₂) analysis system where the atmospheric CO₂ is controlled through the assimilation of column-averaged dry-air mole fractions of CO₂ (XCO₂) from the Greenhouse gases Observing Satellite (GOSAT). The analysis is compared to a free-run simulation (without assimilation of XCO₂), and they are both evaluated against XCO₂ data from the Total Carbon Column Observing Network (TCCON). We show that the assimilation of the GOSAT XCO₂ product from the Bremen Optimal Estimation Differential Optical Absorption Spectroscopy (BESD) algorithm during the year 2013 provides XCO₂ fields with an improved mean absolute error of 0.6 parts per million (ppm) and an improved station-to-station bias deviation of 0.7  ppm compared to the free run (1.1 and 1.4  ppm, respectively) and an improved estimated precision of 1  ppm compared to the GOSAT BESD data (3.3  ppm). We also show that the analysis has skill for synoptic situations in the vicinity of frontal systems, where the GOSAT retrievals are sparse due to cloud contamination. We finally computed the 10-day forecast from each analysis at 00:00  UTC, and we demonstrate that the CO₂ forecast shows synoptic skill for the largest-scale weather patterns (of the order of 1000  km) even up to day 5 compared to its own analysis.

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Volltext §
DOI: 10.5445/IR/1000053165
DOI: 10.5194/acp-16-1653-2016
Zitationen: 20
Web of Science
Zitationen: 19
Zitationen: 19
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)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2016
Sprache Englisch
Identifikator ISSN: 1680-7316
KITopen-ID: 1000053165
HGF-Programm 12.03.01 (POF III, LK 01) Long term observations of tropospheric
Erschienen in Atmospheric Chemistry and Physics
Verlag European Geosciences Union (EGU)
Band 16
Heft 3
Seiten 1653-1671
Nachgewiesen in Scopus
Web of Science
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