A new advanced model for estimation of surface solar irradiance from satellite.
The National Research Council has developed a new advanced model for estimation of surface solar irradiance from satellite (AMESIS). It is designed to estimate with better accuracy the incident solar radiation at the surface from the spinning enhanced visible and infrared imager (SEVIRI) satellite measurements.
The model developed takes into account the effect of aerosol, the overcast and partially cloudy coverage, and provides irradiance solar maps every 15 min both for monitoring purposes and for monthly, annual averages of surface solar irradiance. Depending on the scenario, the scheme evaluates the parameters to characterize the clouds and aerosols that are used to estimate the irradiance at the ground. The model also estimates the cloud cover in advance. Comparisons with the Global Atmosphere Watch station ground-based measurements of incoming solar radiation agree with the values retrieved with the AMESIS model.
There are several areas where Amesis could contribute: 1) The development of databases and maps of solar radiation for each Italian municipality, identification of sites with greater solar potential, thus optimizing the 'consumption' of territory, 2) the foreknowledge of cloud cover to assess the power fed into the grid, which is crucial when planning the sources of supply and negotiating feed, 3) the development of technical tools to support operational planning and actions on energy retrofit existing buildings and 4) the characterization of the suitability of agricultural land.
Given the main limitations to the use of solar energy, namely its low temporal and spatial resolution data and the lack of estimates of spectral irradiance, it is Amesis primary objective to produce very accurate radiation data with a temporal resolution of 15 minutes and space of 1 square kilometer, continuous and homogeneous across the European and North African region.
The development of technical tools to support operational planning and actions on energy retrofit existing buildings; the characterization of the suitability of agricultural land and the foreknowledge of cloud cover to assess the power fed into the grid, which is crucial when planning the sources of supply and negotiating feed.
Emissions reduction; Consumption optimization through the identification of sites with greater solar potential with the help of the developed databases and maps of solar radiation.
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