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Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH4 data with weak-constraint four-dimensional variational data assimilation

Stanevich, Ilya; Jones, Dylan B. A.; Strong, Kimberly; Keller, Martin; Henze, Daven K.; Parker, Robert J.; Boesch, Hartmut; Wunch, Debra; Notholt, Justus; Petri, Christof; Warneke, Thorsten; Sussmann, Ralf 1; Schneider, Matthias 2; Hase, Frank 2; Kivi, Rigel; Deutscher, Nicholas M.; Velazco, Voltaire A.; Walker, Kaley A.; Deng, Feng
1 Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT)
2 Institut für Meteorologie und Klimaforschung Atmosphärische Spurengase und Fernerkundung (IMKASF), Karlsruher Institut für Technologie (KIT)

Abstract:

We examined biases in the global GEOS-Chem chemical transport model for the period of February–May 2010 using weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation and dry-air mole fractions of CH4 (XCH4) from the Greenhouse gases Observing SATellite (GOSAT). The ability of the observations and the WC 4D-Var method to mitigate model errors in CH4 concentrations was first investigated in a set of observing system simulation experiments (OSSEs). We then assimilated the GOSAT XCH4 retrievals and found that they were capable of providing information on the vertical structure of model errors and of removing a significant portion of biases in the modeled CH4 state. In the WC 4D-Var assimilation, corrections were added to the modeled CH4 state at each model time step to account for model errors and improve the model fit to the assimilated observations. Compared to the conventional strong-constraint (SC) 4D-Var assimilation, the WC method was able to significantly improve the model fit to independent observations. Examination of the WC state corrections suggested that a significant source of model errors was associated with discrepancies in the model CH4 in the stratosphere. ... mehr

Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU)
Institut für Meteorologie und Klimaforschung (IMK)
Institut für Meteorologie und Klimaforschung Atmosphärische Spurengase und Fernerkundung (IMKASF)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 1680-7324
KITopen-ID: 1000134465
HGF-Programm 12.11.13 (POF IV, LK 01) Long-term trends of global atmospheric composition
Erschienen in Atmospheric chemistry and physics
Verlag European Geosciences Union (EGU)
Band 21
Heft 12
Seiten 9545–9572
Vorab online veröffentlicht am 24.06.2021
Nachgewiesen in Dimensions
Scopus
Web of Science

Verlagsausgabe §
DOI: 10.5445/IR/1000134465
Veröffentlicht am 28.06.2021
Originalveröffentlichung
DOI: 10.5194/acp-21-9545-2021
Scopus
Zitationen: 11
Web of Science
Zitationen: 10
Dimensions
Zitationen: 17
Seitenaufrufe: 154
seit 29.06.2021
Downloads: 94
seit 29.06.2021
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