Multi‐Season Evaluation of CO₂ Weather in OCO‐2 MIP Models

Abstract

The ability of current global models to simulate the transport of CO 2 by mid-latitude, synopticscale weather systems (i.e., CO 2 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 CO 2 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 CO 2 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 CO 2 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 CO 2 data used in the inversion. The metrics presented here provide new benchmarks regarding the ability of atmospheric inversion systems to reproduce the CO 2 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.Plain Language Summary Global flux estimate systems use CO 2 observations, atmospheric transport models, CO 2 flux models (emissions and absorption), and mathematical optimization methods to estimate biosphere-atmosphere CO 2 exchange. Accurate representation of atmospheric transport is important for a reliable optimization of fluxes in these systems. We use intensive aircraft measurements of wind speed, boundary layer height, and horizontal and vertical differences of CO 2 concentrations within 27 mid-latitude cyclones collected by the Atmospheric Carbon Transport (ACT)-America mission to evaluate the performance of ten global flux estimate systems from the Orbiting Carbon Observatory-2 model intercomparison project (OCO-2 MIP). We find the models can simulate observed horizontal CO 2 differences between the warm and cold parts of cyclones with different degrees of success in summer and spring, but often underestimate the observed cross-frontal and vertical differences in CO 2 in winter and autumn. The models may underestimate the CO 2 differences between the boundary layer and the free troposphere due to model errors in boundary layer height and surface fluxes. These weather-oriented CO 2 metrics provide benchmarks for testing simulations of the CO 2 structure within cyclones. Future efforts are needed to link these metrics more directly to the accuracy of CO 2 flux esti...

Evaluating Global Atmospheric Inversions of Terrestrial Net Ecosystem Exchange CO2 Over North America on Seasonal and Sub‐Continental Scales

“…Our results show that the overall OCO-2 v9 MIP models underestimate the seasonal amplitude of NEE across central and eastern US ecosystems, regardless of data source. These results are consistent with the results of other studies using ACT-America observations (Cui et al, 2021;Feng et al, 2021;Zhang et al, 2022) but independent 2021) and this study for summer, fall, and spring, while an opposite sign of the mean bias estimates for winter likely due to the underestimates of ABL in WRF simulations of Cui et al (2021). Zhang et al (2022) co-sampled the ACT-America data in the posterior CO 2 fields of the OCO-2 v9 MIP.…”

“…These results are consistent with the results of other studies using ACT-America observations (Cui et al, 2021;Feng et al, 2021;Zhang et al, 2022) but independent 2021) and this study for summer, fall, and spring, while an opposite sign of the mean bias estimates for winter likely due to the underestimates of ABL in WRF simulations of Cui et al (2021). Zhang et al (2022) co-sampled the ACT-America data in the posterior CO 2 fields of the OCO-2 v9 MIP. They found seasonal model-data mismatch patterns in boundary layer CO 2 from the OCO-2 v9 MIP which are largely consistent with an underestimate in seasonal NEE magnitudes.…”

“…This does not rule out the possibility that all atmospheric transport systems available to us at this time might be biased. Zhang et al (2022) also found that the magnitudes of posterior, seasonally-and sectorally-averaged ABL-Free troposhere (FT) vertical CO 2 differences over the ACT-America flight domain were underestimated in the OCO-2 v9 MIP inversion systems, a result that could be consistent with either underestimated seasonal amplitudes of NEE, overestimated vertical mixing, or some combination of those factors. Zhang et al (2022) evaluated mean wind speed and ABL depths in the inversion systems and did not find persistent biases.…”

“…The OCO-2 v9 MIP released a suite of gridded CO 2 flux inversions from 10 global inversion models encompassing the years 2015-2018. Details of the OCO-2 v9 MIP are described by Peiro et al (2022) and Zhang et al (2022) and in Table S1 of Supporting Information S1. The different inversion systems are standardized in the sense that they are required to assimilate the same four sets of atmospheric observations.…”

Airborne Lidar Measurements of XCO2 in Synoptically Active Environment and Associated Comparisons With Numerical Simulations

“…Using airborne in situ measurements of CO 2 fields obtained during the ACT-America RFs, Gerken et al (2021) exploited the performance of both mesoscale (WRF-Chem) and global scale (CT) models using identical surface fluxes and found reasonable agreement with observations in all four seasons. Additionally, for frontal RFs, Zhang et al (2022) also found that OCO-2 MIP models were capable of simulating observed CO 2 frontal contrasts with varying degrees of success in summer and spring, and frequent underestimation of frontal contrasts in winter and autumn.…”