Incoming solar radiation is the primary source of energy for plant photosynthesis. Solar radiation also plays a key role in evapotranspiration. Visible observations from satellites provide an excellent source of information about the amount of solar radiation reaching the plant canopy. A measurement of solar energy reflected to space from earth-atmosphere system immediately specifies the maximum amount of solar energy that can be absorbed at the surface. Incoming solar radiation can be known by adjusting the amount absorbed. Hence, for the computation of downwelling solar radiation, the albedo of the surface must be known. This is especially important over the regions of high reflectivity such as snow and desert. Tarpley (1979) used a statistical regression technique to obtain surface fluxes over the land from Visible channel observations from geostationary satellites. In this model, cloud amount is estimated for a given location from satellite visible data. Three separate regression equations are then used to estimate solar radiation for three categories of clouds. This method provides an accuracy of 10% for clear sky, 30% for partly cloudy and 50% for overcast conditions. Other algorithms like those by Moser and Raschke (1984), and Pinker and Ewing (1985) used physical approaches, and treated the interaction of incoming and reflected solar radiation with the atmosphere and land surfaces in physical manner. The transmittance of solar radiation in these approaches is solved by the use of radiative transfer equations that take into account the concentration profile of different atmospheric components. These physical schemes also take into account the cloudiness and atmospheric water vapor. These methods provide relatively higher accuracy. However, statistical techniques have remained the choice for operational use. These methods require coincident satellite and ground (pyranometer) observations to develop the coefficients in the regression equations. These methods produce daily total insolation, based on hourly estimates made from geostationary satellite data between 0800 and 1600 LST, with interpolation used toward both sunrise and sunset and for any other missing hourly values.
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Do we really want the one thing that gives us its resources unconditionally to suffer even more than it is suffering now? Nature, is a part of our being from the earliest human days. We respect Nature and it gives us its bounty, but in the recent past greedy money hungry corporations have made us all so destructive, so wasteful.