Abstract
Abstract. Satellite-based cloud, aerosol, and trace-gas retrievals from ultraviolet (UV) and visible (Vis) wavelengths depend on the accurate representation of surface reflectivity. Current UV and Vis retrieval algorithms typically use surface reflectivity climatologies that do not account for variation in satellite viewing geometry or surface roughness. The concept of geometry-dependent surface Lambertian-equivalent reflectivity (GLER) is implemented for water surfaces to account for surface anisotropy using a Case 1 water optical model and the Cox–Munk slope distribution for ocean surface roughness. GLER is compared with Lambertian-Equivalent reflectivity (LER) derived from the Ozone Monitoring Instrument (OMI) for clear scenes at 354, 388, 440, and 466 nm. We show that GLER compares well with the measured LER data over the open ocean and captures the directionality effects not accounted for in climatological LER databases. Small biases are seen when GLER and the OMI-derived LER are compared. GLER is biased low by up to 0.01–0.02 at Vis wavelengths and biased high by around 0.01 in the UV, particularly at 354 nm. Our evaluation shows that GLER is an improvement upon climatological LER databases as it compares well with OMI measurements and captures the directionality effects of surface reflectance.
Highlights
Satellite retrievals of clouds, aerosols, and trace gases rely on the accurate representation of surface reflectivity
Our evaluation shows that geometry-dependent surface Lambertian-equivalent reflectivity (GLER) is an improvement upon climatological LambertianEquivalent reflectivity (LER) databases as it compares well with Ozone Monitoring Instrument (OMI) measurements and captures the directionality effects of surface reflectance
Previous work Qin et al (2019) introduced the GLER product for land surfaces based on bidirectional reflectance distribution function (BRDF) input from Moderate Resolution Imaging Spectroradiometer (MODIS)
Summary
Aerosols, and trace gases rely on the accurate representation of surface reflectivity. Whereas the land product described in Qin et al (2019) used a model of BRDF with input from MODIS, GLER for ocean scenes is produced solely by modeling of waterleaving radiance and surface reflection. These surfaceleaving radiance contributions are geometry-dependent, and the anisotropic nature of light backscattered by the ocean has been studied in many papers (see, e.g., Gordon , 1989; Morel and Gentili, 1991, 1993, 1996; Park and Ruddick, 2005; Lee et al, 2013). PACE’s spectral coverage from the UVA to green wavelength region and in the red to near-infrared will enable unparalleled evaluation of ocean ecosystem properties in optically complex waters and in regions of increasing eutrophication (Cetinic et al, 2018)
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