Abstract
Abstract. Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun–sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox–Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.
Highlights
Satellite ultraviolet and visible (UV–vis) nadir backscattered sunlight trace-gas, aerosol, and cloud retrieval algorithms must accurately estimate the reflection by the Earth’s surface in order to produce high-quality data sets
Because reflection of incoming direct and diffuse solar light from non-Lambertian surfaces depends on satellite observational geometry, the same area observed at different geometries can have different Lambertian equivalent reflectivity (LER)
We developed a new concept of geometry-dependent surface LER and provided a means for computing it
Summary
Satellite ultraviolet and visible (UV–vis) nadir backscattered sunlight trace-gas, aerosol, and cloud retrieval algorithms must accurately estimate the reflection by the Earth’s surface in order to produce high-quality data sets. Surface reflectivity climatologies used in most current algorithms are typically gridded monthly Lambertian equivalent reflectivities (LERs) that have been derived from satellite observations (e.g., Herman and Celarier, 1997; Kleipool et al, 2008; Russell et al, 2011; Popp et al, 2011) These climatologies generally have no dependence on the observation geometry. Vasilkov et al.: Effects of surface BRDF on UV–vis cloud and trace-gas algorithms ity because sometimes different definitions have been used for similar or the same quantities This dependence is described by the bidirectional reflectance distribution function (BRDF), mathematically expressed as BRDF (ωi, ωr)
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