Impact of model errors in convective transport on CO source estimates inferred from MOPITT CO retrievals

Abstract

[1] Estimates of surface fluxes of carbon monoxide (CO) inferred from remote sensing observations or free tropospheric trace gas measurements using global chemical transport models can have significant uncertainties because of discrepancies in the vertical transport in the models, which make it challenging to unequivocally relate the observations back to the surface fluxes in the models. The new Measurement of Pollution in the Troposphere (MOPITT) version 5 retrievals provide greater sensitivity to lower tropospheric CO over land relative to the previous versions and are, therefore, useful for evaluating vertical transport in models. We have assimilated the new MOPITT CO retrievals, using the Goddard Earth Observing System (GEOS)-Chem model, to study the influence of vertical transport errors on inferred CO sources. We compared the source estimates obtained by assimilating the CO profiles, the column amounts, and the surface level retrievals for June-August 2006. The three different inversions produced large differences in the source estimates in regions of convection and strong CO emissions. The inversion using the CO profiles suggested an 85% increase in emissions in India/Southeast Asia, which exacerbated the model bias in the lower and middle troposphere, whereas using the surface level retrievals produced a 37% decrease in Indian/Southeast Asian emissions, which exacerbated the underestimate of CO in the upper troposphere. Globally, the inversion with the surface retrievals suggested a 22% reduction in emissions from the a priori estimate of 161 Tg CO/month (from combustion and the oxidation of biogenic volatile organic compounds), averaged in June-August 2006. The analysis results were validated with independent surface CO measurements from NOAA Global Monitoring Division (GMD) network and upper troposphere CO measurements from the Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrumented Container (CARIBIC). We found that the inversion with the surface retrievals agreed best with surface CO data but produced the largest discrepancy with the CARIBIC aircraft data in the upper troposphere, suggesting the influence of vertical transport errors in the model. Our results show that the comparison of the a posteriori CO distributions obtained from the inversions using the surface and profile retrievals provides a means of characterizing the potential impact of the vertical transport biases on the source estimates and the CO distribution.

Regional data assimilation of multi-spectral MOPITT observations of CO over North America

“…Although the MOPITT surface-level retrievals have peak sensitivity to CO near the boundary layer, their sensitivity extend up to the middle troposphere (see Fig. 1a of Jiang et al, 2013). Consequently, the inversion analyses could be sensitive to chemical aging of air in the North American anticyclone.…”

“…Model errors in long-range transport, vertical convective transport, diffusion, and chemistry (e.g. Arellano Jr. et al, 2006;Fortems-Cheiney et al, 2011;Locatelli et al, 2013;Worden et al, 2013;Jiang et al, 2011Jiang et al, , 2013Jiang et al, , 2015 all adversely impact the inverse modeling of CO and other trace constituents (such as methane), and mitigating these errors in global models is challenging.…”

“…In an earlier study, Jiang et al (2013) noted that when comparing source estimates inferred from in situ surface data and from satellite observations, "in the absence of transport bias, the surface and satellite data should provide consistent constraints on the sources, if the data coverage is representative of the spatiotemporal variability in CO". They were the first to show a large discrepancy in the Asian source estimates obtained from the MOPITT surface-level and profile retrievals, and they argued that it was due to errors in convective transport over Asia associated with the Asian summer monsoon.…”

“…3 can be considered to be the residual bias in the a posteriori simulation that cannot be effectively removed within the 1-month assimilation period by adjusting only the surface emissions. The most significant feature is the positive residual bias along the Intertropical Convergence Zone (ITCZ), suggesting errors in convective transport in the model (e.g., Jiang et al, 2013;Worden et al, 2013).…”

Top-down estimates of biomass burning emissions of black carbon in the Western United States

“…In recent years, there has been an increasing emphasis on the use of inverse methods to characterize the temporal and spatial variability of emissions. Top-down inversions have been widely used for estimating emission fluxes of long-lived trace gases such as carbon dioxide (e.g., Pickett-Heaps et al, 2011;Chevallier et al, 2007;Gloor et al, 1999), methane (e.g., Wecht et al, 2012;Meirink et al, 2008;Hein et al, 1997), and carbon monoxide based on observations from surface stations (e.g., Bergamaschi et al, 2000;Kasibhatla et al, 2002), aircraft (e.g., Palmer et al, 2003Palmer et al, , 2006, and satellites (Jiang et al, 2011(Jiang et al, , 2013Jones et al, 2009;Stavrakou and Müller, 2006;Arellano et al, 2004Arellano et al, , 2006, when the atmospheric concentrations are linearly or weakly non-linearly dependent on their emissions (Müller and Stavrakou, 2005). Top-down inversions, by nature, are a way to examine the consistency of model results with observations.…”