Atmospheric Simulations of Total Column CO2 Mole Fractions from Global to Mesoscale within the Carbon Monitoring System Flux Inversion Framework
In: Atmosphere, Jg. 11 (2020-07-26), Heft 787, p 787
Online
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Zugriff:
Quantifying the uncertainty of inversion-derived CO 2 surface fluxes and attributing the uncertainty to errors in either flux or atmospheric transport simulations continue to be challenges in the characterization of surface sources and sinks of carbon dioxide ( CO 2 ). Despite recent studies inferring fluxes while using higher-resolution modeling systems, the utility of regional-scale models remains unclear when compared to existing coarse-resolution global systems. Here, we present an off-line coupling of the mesoscale Weather Research and Forecasting (WRF) model to optimized biogenic CO 2 fluxes and mole fractions from the global Carbon Monitoring System inversion system (CMS-Flux). The coupling framework consists of methods to constrain the mass of CO 2 introduced into WRF, effectively nesting our regional domain covering most of North America (except the northern half of Canada) within the CMS global model. We test the coupling by simulating Greenhouse gases Observing SATellite (GOSAT) column-averaged dry-air mole fractions ( XCO 2 ) over North America for 2010. We find mean model-model differences in summer of &sim
0.12 ppm, significantly lower than the original coupling scheme (from 0.5 to 1.5 ppm, depending on the boundary). While 85% of the XCO 2 values are due to long-range transport from outside our North American domain, most of the model-model differences appear to be due to transport differences in the fraction of the troposphere below 850 hPa. Satellite data from GOSAT and tower and aircraft data are used to show that vertical transport above the Planetary Boundary Layer is responsible for significant model-model differences in the horizontal distribution of column XCO 2 across North America.
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Atmospheric Simulations of Total Column CO2 Mole Fractions from Global to Mesoscale within the Carbon Monitoring System Flux Inversion Framework
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| Autor/in / Beteiligte Person: | Lauvaux, Thomas ; Bowman, Kevin W. ; Liu, Junjie ; Butler, M. P. ; Davis, Kenneth J. ; Feng, Sha ; Pennsylvania State University (Penn State) ; Penn State System ; Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE) ; Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) ; Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV) ; Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS) ; Jet Propulsion Laboratory (JPL) ; NASA-California Institute of Technology (CALTECH) ; National Aeronautics and Space Administration, NASA: NNX13AP34G NNZ15AG76G Ames Research Center, ARC ; This work was funded by the NASA Carbon Monitoring System (https://carbon.nasa.gov) project: Quantification of the sensitivity of NASA CMS-Flux inversions to uncertainty in atmospheric transport (grant NNX13AP34G). Partial support for M.P.B., T.L. and S.F. was also provided by ACT-America (Earth Venture Suborbital grant NNZ15AG76G). T.L. was also supported by the French National Program MOPGA (Make Our Planet Great Again) through the project CIUDAD. Acknowledgments: Resources supporting the CMS-Flux system products used in this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center. We thank P.O. Wennberg, D. Wunch, C. Roehl and G. Toon for making the Lamont TCCON data available. The ACOS-GOSAT v3.5 soundings were produced by the ACOS/OCO2 project at the Jet Propulsion Laboratory, California Institute of Technology from GOSAT column CO2 spectra, and were obtained from http://co2.jpl.nasa.gov. The ACOS v3.5 User Guide is also available at this site. CMS-Flux system products are available from J. Liu (Junjie.Liu@jpl.nasa.gov). The hourly WRF CO2 atmospheric mole fractions are archived as Lauvaux, T. and Butler, M.: CMS: Hourly Carbon Dioxide Estimated Using the WRF Model, North America, 2010 (http://dx.doi.org/10.3334/ORNLDAAC/1338). The NOAA archive of rawinsonde data were obtained at http://www.esrl.noaa.gov/raobs/fsl-format-new.cgi. Code for the boundary conditions interface to WRF-Chem is available at https://github.com/psu-inversion/WRF_Boundary_Coupling. The WRF model output is archived at the Pennsylvania State University Data Commons, https://doi.org/10.26208/deck-h130. Other data sources are cited in the text and references. ; ANR-17-MPGA-0008,CIUDAD,Quantification of urban greenhouse gas emissions(2017) ; Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ) ; Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ) |
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| Zeitschrift: | Atmosphere, Jg. 11 (2020-07-26), Heft 787, p 787 |
| Veröffentlichung: | Multidisciplinary Digital Publishing Institute, 2020 |
| Medientyp: | unknown |
| ISSN: | 2073-4433 (print) |
| DOI: | 10.3390/atmos11080787 |
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