ALBEDO below aerosol

From a satellites perspective reflection from below the aerosol layer contaminates the aerosol signal. It is most desirable to eliminate these contributions. However, multi-spectral and dual-direction viewing methods have not yet become operational to provide monthly statistics (ATSR-2, MISR) and polarization methods are still in experimental stages (POLDER, see below). If impacts of surface reflectance have to be included, than it is desirable that the values for surface reflectance are small (higher sensitivity to a scattering aerosol signal) and accurate - and if possible invariant. As a rule, a 1% albedo error roughly corresponds to a visible optical depth retrieval error of 0.1. This is of the same order as the aerosol optical depth itself. Accurate surface reflectance values have to consider surface conditions (e.g.

soil, moisture, canopy, topography) and the dependence on viewing geometry. In addition, multi-spectral retrievals require information on spectral dependencies.

Over land, surface conditions (e.g. types of vegetation, snow, water, urban) and their associated reflectance are usually highly variable (spatially and temporally) within the footprint of a satellite pixel. Adding the dependence on viewing geometry, an accurate assessment of surface contributions to the detected signal is quite difficult. Somewhat successful are multi-spectral dark pixel methods that utilize for aerosol retrievals the low reflectance of green vegetation in the visible spectral region. Vegetation pixels are identified by retrievals at longer wavelengths, where contributions of (small) aerosol fade in the satellite signal. These methods are of limited success, because they assume fixed solar spectral reflectance relationships. In addition, spatial coverage of green vegetation for cloud-free scenes is usually very sparse. Other methods over land take advantage of a low surface reflectance in the ultraviolet, but requirements for data on aerosol altitude introduce added uncertainty. And, as already mentioned, polarization measurements are tested, as changes to polarization are less sensitive to surface contributions.

Over water, surface albedos are less variable and small, if sun-glint viewing geometries are avoided and if shallow water regions with uncertain sub-surface reflections are excluded. Then, retrieval algorithms (based on minimum reflection maps, as function of location, season, near-surface winds and viewing geometry) permit reliable estimates for surface contributions to the satellite signal.

Most current (thus, non-so) global satellite retrievals provide aerosol properties only over water. And it is usually left to models to fill the gaps over land, although over land the aerosol concentration and aerosol optical depths are largest.

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