Constraints on local-to-regional anthropogenic combustion from satellite retrievals of combustion-related trace gases: Implications to verifying sources of anthropogenic CO2

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Monday, 5 January 2015: 2:15 PM
124A (Phoenix Convention Center - West and North Buildings)
Avelino F. Arellano Jr., University of Arizona, Tucson, AZ; and A. Raman and A. Chatterjee

The onset of near-global and long-term measurements of chemical constituents from space, in conjunction with recent advances in atmospheric modeling and data assimilation offers a unique opportunity to improve our capability to predict and assess chemical weather and air quality. Here, we present data assimilation experiments to assess the information gain in using current satellite observations of chemical constituents that are co-emitted during a combustion process. In particular, OSSEs will be conducted to investigate synergistic information from satellite retrievals of CO2 from GOSAT (and OCO-2), CO from MOPITT (and IASI), and NO2 from OMI in constraining sources of anthropogenic combustion at city-, state- and regional-level spatiotemporal scales. These experiments will be carried out using an ensemble-based data assimilation (DA) system comprising of a regional air quality/weather model, WRF-Chem, global climate/chemistry model, CAM-Chem, and a data assimilation software package, DART. The ensemble-based DA system, which mimics a numerical weather prediction with chemistry, provides a means to statistically estimate local sensitivities across modeled meteorological and chemical states (CO2, CO, NO2, and related species) and model parameters (including surface fluxes) using the ensemble statistics derived from dynamical, physical, and chemical perturbations in the model. We take advantage of these sensitivities in fully exploiting the synergistic information provided by the enhancement ratios that are indicative of the anthropogenic combustion characteristic of a given location sampled by these space-based observations. We evaluate the impact of each observations within an OSSE framework, where one realization of simulated atmosphere (with known forcings and fluxes) is assumed to be the ‘truth'. Synthetic observations are then derived from this atmosphere using sampling and error characteristics of the retrievals. The assimilation of these synthetic observations will be evaluated based on how well the analysis can reproduce the ‘true' chemical states and sources from anthropogenic combustion, including anthropogenic CO2.