Quantifying the Impact of Atmospheric Transport Uncertainty on CO Surface Flux Estimates.
Andrew E Schuh, Andrew R Jacobson, Sourish Basu, Brad Weir, David Baker, Kevin Bowman, Frédéric Chevallier, Sean Crowell, Kenneth J Davis, Feng Deng, Scott Denning, Liang Feng, Dylan Jones, Junjie Liu, Paul I Palmer
Author Information
Andrew E Schuh: Cooperative Institute for Research in the Atmosphere Colorado State University Fort Collins CO USA. ORCID
Andrew R Jacobson: University of Colorado Boulder and NOAA Earth System Research Laboratory Boulder CO USA.
Sourish Basu: University of Colorado Boulder and NOAA Earth System Research Laboratory Boulder CO USA.
Brad Weir: Global Modeling and Assimilation Office NASA Goddard Space Flight Center Greenbelt MD USA. ORCID
David Baker: Cooperative Institute for Research in the Atmosphere Colorado State University Fort Collins CO USA.
Kevin Bowman: Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA. ORCID
Frédéric Chevallier: Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, L'Orme des Merisiers, GifsurYvette Paris France. ORCID
Sean Crowell: School of Meteorology University of Oklahoma Norman OK USA. ORCID
Kenneth J Davis: Department of Meteorology and Atmospheric Science Pennsylvania State University University Park PA USA. ORCID
Feng Deng: Department of Physics University of Toronto Toronto Ontario Canada. ORCID
Scott Denning: Department of Atmospheric Sciences Colorado State University Fort Collins CO USA.
Liang Feng: School of GeoSciences University of Edinburgh Edinburgh UK.
Dylan Jones: Department of Physics University of Toronto Toronto Ontario Canada. ORCID
Junjie Liu: Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA. ORCID
Paul I Palmer: School of GeoSciences University of Edinburgh Edinburgh UK. ORCID
We show that transport differences between two commonly used global chemical transport models, GEOS-Chem and TM5, lead to systematic space-time differences in modeled distributions of carbon dioxide and sulfur hexafluoride. The distribution of differences suggests inconsistencies between the transport simulated by the models, most likely due to the representation of vertical motion. We further demonstrate that these transport differences result in systematic differences in surface CO flux estimated by a collection of global atmospheric inverse models using TM5 and GEOS-Chem and constrained by in situ and satellite observations. While the impact on inferred surface fluxes is most easily illustrated in the magnitude of the seasonal cycle of surface CO exchange, it is the annual carbon budgets that are particularly relevant for carbon cycle science and policy. We show that inverse model flux estimates for large zonal bands can have systematic biases of up to 1.7 PgC/year due to large-scale transport uncertainty. These uncertainties will propagate directly into analysis of the annual meridional CO flux gradient between the tropics and northern midlatitudes, a key metric for understanding the location, and more importantly the processes, responsible for the annual global carbon sink. The research suggests that variability among transport models remains the largest source of uncertainty across global flux inversion systems and highlights the importance both of using model ensembles and of using independent constraints to evaluate simulated transport.
