Articles | Volume 21, issue 12
Atmos. Chem. Phys., 21, 9545–9572, 2021
https://doi.org/10.5194/acp-21-9545-2021
Atmos. Chem. Phys., 21, 9545–9572, 2021
https://doi.org/10.5194/acp-21-9545-2021

Research article 24 Jun 2021

Research article | 24 Jun 2021

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

Ilya Stanevich et al.

Data sets

Assessing 5 years of GOSAT Proxy XCH4 data and associated uncertainties (http://cci.esa.int/ghg) R. J. Parker, H. Boesch, K. Byckling, A. J. Webb, P. I. Palmer, L. Feng, P. Bergamaschi, F. Chevallier, J. Notholt, N. Deutscher, T. Warneke, F. Hase, R. Sussmann, S. Kawakami, R. Kivi, D. W. T. Griffith, and V. Velazco https://doi.org/10.5194/amt-8-4785-2015

2014 TCCON Data Archive Total Carbon Column Observing Network (TCCON) https://tccondata.org/2014

Atmospheric Methane Dry Air Mole Fractions from the NOAA ESRL Carbon Cycle Cooperative Global Air Sampling Network, 1983-2015 E. J. Dlugokencky, P. Lang, A. Crotwell, J. Mund, M. Crotwell, and K. Thoning ftp://aftp.cmdl.noaa.gov/data/trace_gases/ch4/flask/surface/

HIAPER Pole-to-Pole Observations (HIPPO): fine-grained, global-scale measurements of climatically important atmospheric gases and aerosols S. C. Wofsy, H. S. Team, C. Modellers, and S. Teams https://www.eol.ucar.edu/field_projects/hippo/

ACE-FTS version 3.0 data set: validation and data processing update (https://databace.scisat.ca/level2/ace_v3.5_v3.6/) C. Waymark, K. Walker, C. Boone, and P. Bernath https://doi.org/10.4401/ag-6339

Model code and software

Development of the adjoint of GEOS-Chem (http://wiki.seas.harvard.edu/geos-chem/index.php/GEOS-Chem_Adjoint) D. K. Henze, A. Hakami, and J. H. Seinfeld https://doi.org/10.5194/acp-7-2413-2007

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Short summary
We explore the utility of a weak-constraint (WC) four-dimensional variational (4D-Var) data assimilation scheme for mitigating systematic errors in methane simulation in the GEOS-Chem model. We use data from the Greenhouse Gases Observing Satellite (GOSAT) and show that, compared to the traditional 4D-Var approach, the WC scheme improves the agreement between the model and independent observations. We find that the WC corrections to the model provide insight into the source of the errors.
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