Open AccessSurface reflectivity from the Ozone Monitoring Instrument using the Moderate Resolution Imaging Spectroradiometer to eliminate clouds: Effects of snow on ultraviolet and visible trace gas retrievals
Author(s) -
O'Byrne G.,
Martin R. V.,
van Donkelaar A.,
Joiner J.,
Celarier E. A.
Publication year - 2010
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2009jd013079
Subject(s) - snow , ozone monitoring instrument , environmental science , aerosol , spectroradiometer , total ozone mapping spectrometer , atmospheric sciences , albedo (alchemy) , moderate resolution imaging spectroradiometer , remote sensing , trace gas , satellite , irradiance , troposphere , meteorology , reflectivity , geology , ozone layer , geography , physics , optics , stratosphere , art , astronomy , performance art , art history
Satellite retrievals of tropospheric composition from measurements of solar backscatter require accurate information about surface reflectivity. We use clear‐sky data from the Ozone Monitoring Instrument (OMI) to determine global surface reflectivity under both snow‐covered and snow‐free conditions at 354 nm. Clear‐sky scenes are determined using cloud and aerosol data from the Moderate Resolution Imaging Spectroradiometer/Aqua satellite instrument that flies 12 min ahead of OMI/Aura. The result is a database of OMI‐observed Lambertian equivalent reflectivity (LER) that does not rely on statistical methods to eliminate cloud and aerosol contamination. We apply this database to evaluate previous climatologies of surface reflectivity. Except for regions of seasonal snow cover, agreement is best with a climatology from OMI, which selects the surface reflectivity from a histogram of observed LER (mean difference, 0.0002; standard deviation, 0.011). Three other climatologies of surface reflectivity from Total Ozone Mapping Spectrometer, Global Ozone Monitoring Experiment, and OMI, based on minimum observed LER, are less consistent with our cloud‐ and aerosol‐filtered data set (mean difference, −0.008, 0.012, and −0.002; standard deviation, 0.022, 0.026, and 0.033). Snow increases the sensitivity of solar backscatter measurements at ultraviolet and visible wavelengths to trace gases in the lower troposphere. However, all four existing LER climatologies poorly represent seasonal snow. Surface reflectivity over snow‐covered lands depends strongly on the vegetation type covering the surface. The monthly variation of snow‐covered reflectivity varies by less than 0.1 in fall and winter. Applying our snow‐covered surface reflectivity database to OMI NO 2 retrievals could change the retrieved NO 2 column by 20%–50% over large regions with seasonal snow cover.