Datensatz

Zusammenfassung

Aerosol remote sensing from space is predominantly based on sensor data of reflected sunlight in solar spectral regions, where the attenuation by trace-gases can be neglected or easily accounted for. But even at these spectral regions retrievals of aerosol properties are by no means a simple task, as explained in the previous chapters of this book. This is mostly due to the following major reasons:1.Cloud contamination. The solar light reflection attributed to aerosol is small compared to that of clouds and identifying cloud-free and cloud-influence-free regions is a challenge, especially with sensor limitations to spatial resolution. Also at low sun-elevations retrievals near clouds are complicated by cloud shadow scene darkening or side-scatter scene brightening.2.Surface contributions. The solar reflection attributed to aerosol can be smaller than surface signals. Thus, surface albedo (also as function of the sun-elevation) needs to be known to high accuracy. To minimize the surface albedo problem innovative methods are applied. They rely on spectral dependencies (Kaufman et al., 1997), multi-angular views (Martonchik et al., 1998), polarization (Deuzé et al., 1999) or retrievals in the UV (Torres et al., 2002). Higher and variable surface albedos still remain the major reason that most aerosol satellite products have no or only limited coverage over land.3.A-priori assumptions. The relationship that associates changes of solar reflection to aerosol amount in cloud-free conditions is modulated by aerosol composition and even atmospheric environment. Even when combining different sensor data sources, any potential solution is under-determined in the context of dependencies to aerosol amount, particle size, shape and composition. Thus, a-priori assumptions are required. Some of these assumptions, usually to absorption, size and shape, have been locally and/or seasonally validated, but their regional (or even global) and annual application in the context of aerosol temporal and spatial variability is rarely justifiable.