Characterization of Regional‐Scale CO2 Transport Uncertainties in an Ensemble with Flow‐Dependent Transport Errors. Issue 7 (10th April 2019)

• Record Type: Journal Article
• Authors: Chen, Hans W.; Zhang, Fuqing; Lauvaux, Thomas; Davis, Kenneth J.; Feng, Sha; Butler, Martha P.; Alley, Richard B.
• Is Part Of: Geophysical research letters. Volume 46:Issue 7(2019)
• Page Start: 4049
• Page End: 4058
• Publication Date: 2019-04-10
• Subjects: Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2018GL081341
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Inference of CO2 surface fluxes using atmospheric CO2 observations in atmospheric inversions depends critically on accurate representation of atmospheric transport. Here we characterize regional‐scale CO2 transport uncertainties due to uncertainties in meteorological fields using a mesoscale atmospheric model and an ensemble of simulations with flow‐dependent transport errors. During a 1‐month summer period over North America, transport uncertainties yield an ensemble spread in instantaneous CO2 at 100 m above ground level comparable to the CO2 uncertainties resulting from 48% relative uncertainty in 3‐hourly natural CO2 fluxes. Temporal averaging reduces transport uncertainties but increases the influence of CO2 uncertainties from the lateral boundaries. The influence of CO2 background uncertainties is especially large for column‐averaged CO2 . These results suggest that transport errors and CO2 background errors limit regional atmospheric inversions at two distinct timescales and that the error characteristics of transport and background errors should guide the design of regional inversion systems. Plain Language Summary: Accurate estimates of regional‐scale CO2 surface fluxes are essential to improve our understanding of the carbon cycle and to verify human CO2 emission inventories. CO2 surface fluxes can be inferred from atmospheric CO2 measurements through inversion methods, which use atmospheric transport models to relate CO2 concentration to fluxes. However, previous studies have shown that inversion results can be sensitive to errors in the simulated atmospheric transport. To better understand how to account for such transport errors, we characterize the uncertainties in simulated CO2 concentration due to uncertainties in atmospheric transport by running an ensemble of perturbed transport simulations in a regional atmospheric model. Our results show that CO2 uncertainties due to transport uncertainties are about half the magnitude as uncertainties due to erroneous CO2 surface fluxes while displaying similar spatial and temporal patterns. Transport uncertainties are reduced when CO2 is time averaged, but at the same time the influence of uncertainties in the CO2 background concentration is increased at longer timescales. Thus, the flux signals in regional inversions are degraded by transport errors and CO2 background errors at different timescales, and it is imperative to properly account for these errors to obtain reliable regional‐scale CO2 flux estimates. Key Points: We quantify CO2 transport uncertainties due to uncertainties in meteorological fields at the regional scale and submonthly timescales Atmospheric CO2 estimates that are strongly influenced by CO2 surface fluxes tend to also have large transport uncertainties The signal‐to‐noise ratio in in situ CO2 is limited by transport errors at subweekly timescales and CO2 background errors at longer scales