HR: 0800h
AN: A11C-0602    [Abstracts]
TI: Joint Application of Concentrations and Isotopic Signatures to Investigate the Global Atmospheric Carbon Monoxide Budget: Inverse Modeling Approach
AU: * Park, K
EM: khpark@atmsci.msrc.sunysb.edu
AF: Institute for Terrestrial and Planetary Atmospheres (ITPA), School of Marine and Atmospheric Sciences (SoMAS), State University of New York at Stony Brook, Stony Brook, NY 11794-5000, United States
AU: Emmons, L K
EM: emmons@ucar.edu
AF: Atmospheric Chemistry Division (ACD), National Center for Atmospheric Research (NCAR), PO Box 3000, Boulder, CO 80307-3000, United States
AU: Mak, J E
EM: jemak@notes.cc.sunysb.edu
AF: Institute for Terrestrial and Planetary Atmospheres (ITPA), School of Marine and Atmospheric Sciences (SoMAS), State University of New York at Stony Brook, Stony Brook, NY 11794-5000, United States
AB: Carbon monoxide is not only an important component for determining the atmospheric oxidizing capacity but also a key trace gas in the atmospheric chemistry of the Earth's background environment. The global CO cycle and its change are closely related to both the change of CO mixing ratio and the change of source strength. Previously, to estimate the global CO budget, most top-down estimation techniques have been applied the concentrations of CO solely. Since CO from certain sources has a unique isotopic signature, its isotopes provide additional information to constrain its sources. Thus, coupling the concentration and isotope fraction information enables to tightly constrain CO flux by its sources and allows better estimations on the global CO budget. MOZART4 (Model for Ozone And Related chemical Tracers), a 3-D global chemical transport model developed at NCAR, MPI for meteorology and NOAA/GFDL and is used to simulate the global CO concentration and its isotopic signature. Also, a tracer version of MOZART4 which tagged for C¹⁶O and C¹⁸O from each region and each source was developed to see their contributions to the atmosphere efficiently. Based on the nine-year- simulation results we analyze the influences of each source of CO to the isotopic signature and the concentration. Especially, the evaluations are focused on the oxygen isotope of CO (δ¹⁸O), which has not been extensively studied yet. To validate the model performance, CO concentrations and isotopic signatures measured from MPI, NIWA and our lab are compared to the modeled results. The MOZART4 reproduced observational data fairly well; especially in mid to high latitude northern hemisphere. Bayesian inversion techniques have been used to estimate the global CO budget with combining observed and modeled CO concentration. However, previous studies show significant differences in their estimations on CO source strengths. Because, in addition to the CO mixing ratio, isotopic signatures are independent tracers that contain the source information, jointly applying the isotope and the concentration information is expected to provide more precise optimization results in CO budget estimation. Our accumulated long-term CO isotope measurement data contribute to having more confidence of the inversions as well. Besides the benefit of adding isotope data on the inverse modeling, a trait of each isotope of CO (oxygen and carbon isotope) contains another advantageous use in the top-down estimation of the CO budget. δ¹⁸O and δ¹³C has a distinctive isotopic signature on a specific source; combustion sources such as a fossil fuel use show clearly different values from other natural sources in the δ¹⁸O signatures and the methane source can be easily separated by using δ¹³C information. Therefore, inversions of the two major sources of CO respond with different sensitivity for the different isotopes. To maximize the strengths of using isotope data in the inverse modeling analysis, various coupling schemes combining [CO], δ¹⁸O and δ¹³C have been investigated to enhance the credibility of the CO budget optimization.
DE: 0365 Troposphere: composition and chemistry
DE: 0368 Troposphere: constituent transport and chemistry
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting