Articles | Volume 10, issue 1
Atmos. Meas. Tech., 10, 333–349, 2017

Special issue: Ten years of Ozone Monitoring Instrument (OMI) observations...

Atmos. Meas. Tech., 10, 333–349, 2017

Research article 27 Jan 2017

Research article | 27 Jan 2017

Accounting for the effects of surface BRDF on satellite cloud and trace-gas retrievals: a new approach based on geometry-dependent Lambertian equivalent reflectivity applied to OMI algorithms

Alexander Vasilkov1, Wenhan Qin1, Nickolay Krotkov2, Lok Lamsal3, Robert Spurr4, David Haffner1, Joanna Joiner2, Eun-Su Yang1, and Sergey Marchenko1 Alexander Vasilkov et al.
  • 1Science Systems and Applications Inc., Lanham, MD, USA
  • 2NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 3Universities Space Research Association, Columbia, MD, USA
  • 4RT Solutions, Cambridge, MA, USA

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.

Short summary
We show how the surface reflection can vary day to day in the blue part of the sun's spectrum where we measure the pollutant gas nitrogen dioxide using a satellite instrument called OMI. We use information from an imaging spectrometer on another satellite, MODIS, to estimate the angular surface effects. We can then use models of how the sunlight travels through the atmosphere to predict how the angle-dependent surface reflection will impact the values of pollutant levels inferred by OMI.