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Multi-Season Evaluation of CO2 Weather in OCO-2 MIP Models
  • +13
  • Li Zhang,
  • Kenneth J. Davis,
  • Andrew E. Schuh,
  • Andrew Reed Jacobson,
  • Sandip Pal,
  • Yuyan Cui,
  • David F Baker,
  • Sean Crowell,
  • Frederic Chevallier,
  • Marine Remaud,
  • Junjie Liu,
  • Brad Weir,
  • Sajeev Philips,
  • Matthew S Johnson,
  • Feng Deng,
  • Sourish Basu
Li Zhang
The Pennsylvania State University

Corresponding Author:[email protected]

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Kenneth J. Davis
Pennsylvania State University
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Andrew E. Schuh
Colorado State University
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Andrew Reed Jacobson
NOAA Earth System Research Lab
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Sandip Pal
Department of Geosciences, Atmospheric Science Division, Texas Tech University
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Yuyan Cui
Penn State University
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David F Baker
Colorado State University
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Sean Crowell
University of Oklahoma
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Frederic Chevallier
Laboratoire des Sciences du Climat et de l'Environnement (LSCE)
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Marine Remaud
Laboratoire des Sciences du Climat et de l'Environnement (LSCE)
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Junjie Liu
Jet Propulsion Laboratory
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Brad Weir
USRA / NASA Goddard
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Sajeev Philips
NASA Ames Research Center
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Matthew S Johnson
NASA Ames Research Center
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Feng Deng
University of Toronto
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Sourish Basu
NASA GSFC / GMAO NASA Goddard Space Flight Center 8800 Greenbelt Road Code 610.1, Bldg 33, Rm G110 Greenbelt MD 20771 USA
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Abstract

The ability of current global models to simulate the transport of CO2 by mid-latitude, synoptic-scale weather systems (i.e. CO2 weather) is important for inverse estimates of regional and global carbon budgets but remains unclear without comparisons to targeted measurements. Here, we evaluate ten models that participated in the Orbiting Carbon Observatory-2 model intercomparison project (OCO-2 MIP version 9) with intensive aircraft measurements collected from the Atmospheric Carbon Transport (ACT)-America mission. We quantify model-data differences in the spatial variability of CO2 mole fractions, mean winds, and boundary layer depths in 27 mid-latitude cyclones spanning four seasons over the central and eastern United States. We find that the OCO-2 MIP models are able to simulate observed CO2 frontal differences with varying degrees of success in summer and spring, and most underestimate frontal differences in winter and autumn. The models may underestimate the observed boundary layer-to-free troposphere CO2 differences in spring and autumn due to model errors in boundary layer height. Attribution of the causes of model biases in other seasons remains elusive. Transport errors, prior fluxes, and/or inversion algorithms appear to be the primary cause of these biases since model performance is not highly sensitive to the CO2 data used in the inversion. The metrics presented here provide new benchmarks regarding the ability of atmospheric inversion systems to reproduce the CO2 structure of mid-latitude weather systems. Controlled experiments are needed to link these metrics more directly to the accuracy of regional or global flux estimates.