Journal of Geophysical Research Atmospheres · 2007 · 917 citations · 46 references
Natural SciencesEarth SciencesEnvironmental SciencesAtmospheric ChemistryAtmospheric RadiationAtmospheric ScienceAerosol Remote SensingAtmospheric AbsorptionAtmospheric OpticsSolar RadiationUltraviolet SpectroscopyUltraviolet-visible SpectroscopyAbsorption CapacityAbsorption Optical DepthAerosol Absorption RetrievalAerosol IndexAerosol Optical PropertiesAerosol PropertiesOptical DepthOzone Monitoring
Aerosol properties are derived from two independent algorithms. We present an overview of the theoretical and algorithmic aspects of the Ozone Monitoring Instrument (OMI) aerosol and surface UV algorithms. The near‑UV algorithm uses OMI 350–390 nm observations to retrieve aerosol absorption capacity, while a second algorithm employs the full UV‑to‑visible spectral coverage to derive spectral aerosol extinction optical depth. OMI provides aerosol absorption metrics such as the UV Aerosol Index and 388 nm absorption optical depth, surface UV products including erythemally weighted daily dose, erythemal dose rate, and noon spectral irradiances, and the paper discusses their advantages, limitations, and validation uncertainties.
We present an overview of the theoretical and algorithmic aspects of the Ozone Monitoring Instrument (OMI) aerosol and surface UV algorithms. Aerosol properties are derived from two independent algorithms. The nearUV algorithm makes use of OMI observations in the 350–390 nm spectral region to retrieve information on the absorption capacity of tropospheric aerosols. OMI‐derived information on aerosol absorption includes the UV Aerosol Index and absorption optical depth at 388 nm. The other algorithm makes use of the full UV‐to‐visible OMI spectral coverage to derive spectral aerosol extinction optical depth. OMI surface UV products include erythemally weighted daily dose as well as erythemal dose rate and spectral UV irradiances calculated for local solar noon conditions. The advantages and limitations of the current algorithms are discussed, and a brief summary of several validation and evaluation analysis carried out to assess the current level of uncertainty of these products is presented.
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