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http://dx.doi.org/10.14191/Atmos.2015.25.1.117

Analyses of the OMI Cloud Retrieval Data and Evaluation of Its Impact on Ozone Retrieval  

Choi, Suhwan (Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University)
Bak, Juseon (Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University)
Kim, JaeHwan (Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University)
Baek, KangHyun (Department of Atmospheric Sciences, Division of Earth Environmental System, Pusan National University)
Publication Information
Atmosphere / v.25, no.1, 2015 , pp. 117-127 More about this Journal
Abstract
The presences of clouds significantly influence the accuracy of ozone retrievals from satellite measurements. This study focuses on the influence of clouds on Ozone Monitoring instrument (OMI) ozone profile retrieval based on an optimal estimation. There are two operational OMI cloud products; OMCLDO2, based on absorption in $O_2-O_2$ at 477 nm, and OMCLDRR, based on filling in Fraunhofer lines by rotational Raman scattering (RRS) at 350 nm. Firstly, we characterize differences between $O_2-O_2$ and RRS effective cloud pressures using MODIS cloud optical thickness (COT), and then compare ozone profile retrievals with different cloud input data. $O_2-O_2$ cloud pressures are significantly smaller than RRS by ~200 hPa in thin clouds, which corresponds to either low COT or cloud fraction (CF). On the other hand, the effect of Optical centroid pressure (OCP) on ozone retrievals becomes significant at high CF. Tropospheric ozone retrievals could differ by up to ${\pm}10$ DU with the different cloud inputs. The layer column ozone below 300 hPa shows the cloud-induced ozone retrieval error of more than 20%. Finally, OMI total ozone is validated with respect to Brewer ground-based total ozone. A better agreement is observed when $O_2-O_2$ cloud data are used in OMI ozone profile retrieval algorithm. This is distinctly observed at low OCP and high CF.
Keywords
OMI; $O_2-O_2$ cloud algorithm; RRS cloud algorithm; optimal estimation; ozone profile algorithm;
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