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Megretskaia, Inna

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Megretskaia

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Inna

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Megretskaia, Inna

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  • Publication

    Global Estimates of CO Sources with High Resolution by Adjoint Inversion of Multiple Satellite Datasets (MOPITT, AIRS, SCIAMACHY, TES)

    (European Geosciences Union, 2010) Kopacz, M.; Jacob, Daniel; Fisher, John; Logan, Jennifer; Zhang, L.; Megretskaia, Inna; Yantosca, Robert; Singh, K.; Henze, D. K.; Burrows, J. P.; Buchwitz, M.; Khlystova, I.; McMillan, W. W.; Gille, J. C.; Edwards, D. P.; Eldering, A.; Thouret, V.; Nedelec, P.

    We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004–April 2005) global inversion of CO sources at 4°×5° spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is (1350 Tg a^{−1}). This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.

  • Publication

    First Directly Retrieved Global Distribution of Tropospheric Column Ozone from GOME: Comparison with the GEOS-CHEM Model

    (American Geophysical Union, 2006) Liu, Xiong; Chance, Kelly; Sioris, Christopher E.; Kurosu, Thomas; Spurr, Robert J.D.; Martin, Randall V.; Fu, Tzung-May; Logan, Jennifer; Jacob, Daniel; Palmer, Paul I.; Newchurch, Michael J.; Megretskaia, Inna; Chatfield, Robert B.

    We present the first directly retrieved global distribution of tropospheric column ozone from Global Ozone Monitoring Experiment (GOME) ultraviolet measurements during December 1996 to November 1997. The retrievals clearly show signals due to convection, biomass burning, stratospheric influence, pollution, and transport. They are capable of capturing the spatiotemporal evolution of tropospheric column ozone in response to regional or short time-scale events such as the 1997–1998 El Niño event and a 10–20 DU change within a few days. The global distribution of tropospheric column ozone displays the well-known wave-1 pattern in the tropics, nearly zonal bands of enhanced tropospheric column ozone of 36–48 DU at 20°S–30°S during the austral spring and at 25°N–45°N during the boreal spring and summer, low tropospheric column ozone of <30 DU uniformly distributed south of 35°S during all seasons, and relatively high tropospheric column ozone of >33 DU at some northern high-latitudes during the spring. Simulation from a chemical transport model corroborates most of the above structures, with small biases of <±5 DU and consistent seasonal cycles in most regions, especially in the southern hemisphere. However, significant positive biases of 5–20 DU occur in some northern tropical and subtropical regions such as the Middle East during summer. Comparison of GOME with monthly-averaged Measurement of Ozone and Water Vapor by Airbus in-service Aircraft (MOZAIC) tropospheric column ozone for these regions usually shows good consistency within 1σ standard deviations and retrieval uncertainties. Some biases can be accounted for by inadequate sensitivity to lower tropospheric ozone, the different spatiotemporal sampling and the spatiotemporal variations in tropospheric column ozone.