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Atmospheric Composition

From previous ROSES funding, we have developed an algorithm to retrieve ozone profiles from ultraviolet radiances measured by the GOME-1 and OMI instruments. This algorithm produces more accurate ozone profiles in the lower stratosphere and troposphere than standard algorithms. Comparisons with ozonesonde observations show that the retrieved tropospheric ozone columns are less noisy than those from tropospheric ozone residual methods, due to more accurate estimates of both stratospheric and total ozone columns, and have smaller model dependence than those from data assimilation methods. The Aura OMI project is currently implementing our algorithm in the OMI SIPS for producing ozone profiles on a routine basis. Once the OMI processing system becomes operational, NASA, in collaboration with NOAA, will use our algorithm to process MetOp/GOME-2 data. This will provide two global measurements per day, at around 9:30 am and 1:40 pm local times. We plan to apply this algorithm to process NPP/OMPS nadir profiler data using separate NASA funding. We propose a three-year study to continue our investigation to evaluate a multi-year dataset of tropospheric ozone derived from OMI and GOME-2 measurements in conjunction with the GMI Chemistry and Transport Model (CTM). We will first cross- evaluate the consistency between OMI/GOME-2 retrievals and GMI simulations on different time scales. Then we will diagnose the observation/model discrepancies, with ozone profiles from in-situ (e.g., ozonesonde, MOZAIC) or other satellites (e.g., TES, MLS, and IASI), ozone precursors (e.g., NO2 and HCHO from OMI/GOME-2 and CO from AIRS/MOPITT/TES/MLS) from both satellite observations and GMI model outputs, and meteorological fields (e.g., winds, potential vorticity). We will perform a careful comparison of observations and model simulations of ozone and its precursors, by considering the coarser vertical resolutions and vertical sensitivity of satellite retrievals and the coarser horizontal resolutions of the GMI simulation. The evaluation of both OMI and GOME-2 observations with the GMI CTM also allows us to study the morning/afternoon differences in tropospheric ozone and examine the capability of the GMI CTM to capture the morning/afternoon differences in satellite observations. After evaluating the consistency and understand the discrepancy between observations and model simulations, we will integrate observations, models and meteorological information to analyze the global distribution of tropospheric ozone on different time scales (e.g., daily, monthly, interannual) and improve our understanding of chemical and dynamical processes controlling tropospheric ozone, including the photochemical production of tropospheric ozone from different sources (e.g., anthropogenic pollution, biomass burning, lightning), transport of stratospheric ozone to the troposphere, transport of ozone and ozone precursors on regional and intercontinental scales, and transport of low-ozone tropical air to middle and high latitudes. Our proposed study addresses the objectives of ACMAP "oriented toward understanding the chemical, radiative, and dynamic processes controlling atmospheric composition of the troposphere and the stratosphere, through analysis of atmospheric composition observations and their use to rigorously test the theoretical understanding of the atmosphere that is expressed in atmospheric models." Our study of atmospheric processing controlling tropospheric ozone, which is the primary precursor to the oxidation capacity of the troposphere and is a major criteria pollutant, directly responds to the Area A of ACMAP solicitation "factors including tropospheric air quality include the emission, transport, and oxidation of hydrocarbons, carbon monoxide, and nitrogen oxides, aerosol processes, and exchange between the stratosphere and troposphere."

Project PI: Xiong Liu/University of Maryland Baltimore County

Harvard-Smithsonian Center for Astrophysics 60 Garden Street, MS-50 Cambridge, MA 02138

Phone: (617) 496-2136

Fax: (617) 496-2136

Email: xliu@cfa.harvard.edu

https://www.cfa.harvard.edu/~xliu/

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Started: Sep 03, 2010

Last Activity: Feb 02, 2011

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