Abstract
Abstract. We apply a four-dimensional variational (4D-VAR) data assimilation system to optimize carbon monoxide (CO) emissions for 2003 and 2004 and to reduce the uncertainty of emission estimates from individual sources using the chemistry transport model TM5. The system is designed to assimilate large (satellite) datasets, but in the current study only a limited amount of surface network observations from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA/ESRL) Global Monitoring Division (GMD) is used to test the 4D-VAR system. By design, the system is capable to adjust the emissions in such a way that the posterior simulation reproduces background CO mixing ratios and large-scale pollution events at background stations. Uncertainty reduction up to 60 % in yearly emissions is observed over well-constrained regions and the inferred emissions compare well with recent studies for 2004. However, with the limited amount of data from the surface network, the system becomes data sparse resulting in a large solution space. Sensitivity studies have shown that model uncertainties (e.g., vertical distribution of biomass burning emissions and the OH field) and the prior inventories used, influence the inferred emission estimates. Also, since the observations only constrain total CO emissions, the 4D-VAR system has difficulties in separating anthropogenic and biogenic sources in particular. The inferred emissions are validated with NOAA aircraft data over North America and the agreement is significantly improved from the prior to posterior simulation. Validation with the Measurements Of Pollution In The Troposphere (MOPITT) instrument version 4 (V4) shows a slight improved agreement over the well-constrained Northern Hemisphere and in the tropics (except for the African continent). However, the model simulation with posterior emissions underestimates MOPITT CO total columns on the remote Southern Hemisphere (SH) by about 10 %. This is caused by a reduction in SH CO sources mainly due to surface stations on the high southern latitudes.
Highlights
Understanding the budget of carbon monoxide (CO) is important, because by reaction with the radical OH, CO influences the oxidizing capacity of the atmosphere significantly (Logan et al, 1981)
We present the posterior emission estimates and their uncertainties aggregated over continental scale regions as yearly totals, because the monthly emission estimates on grid-scale level are highly variable as a consequence of the loose prior error settings and the small amount of observations
Since the distribution of OH and its north-south gradient remains uncertain, we investigate the influence of the tropospheric OH distribution on the inferred emissions by using an OH field computed from a full-chemistry simulation with TM5 (Huijnen et al, 2010) and scaled by a factor 1.02 to obtain comparable CO and methyl chloroform lifetimes as for the OH field used in the base inversion
Summary
Understanding the budget of carbon monoxide (CO) is important, because by reaction with the radical OH, CO influences the oxidizing capacity of the atmosphere significantly (Logan et al, 1981). In the current study we apply a 4D-VAR system for CO based on the earlier work for methane (Meirink et al, 2008a,b; Bergamaschi et al, 2009) This system is designed to assimilate large observational datasets, it will be tested in this first study by only assimilating surface observations from a limited number of NOAA stations to optimize monthly mean CO emissions for a period of two years. This approach is followed to obtain a benchmark characterization of the system for future assimilation of satellite data.
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