The increase of greenhouse gases concentration in the atmosphere causes the climate change and global warming. The excessive use of fossil fuels is the most relevant cause of this phenomenom. The emissions related to the burning of these fuels are concentrating in the atmosphere and leading to the warming of the Earth. Apart from the hazardous effects of the utilization of fossil fuels, it is important to note that their reserves are finite, and the enormous consumption of oil, gas and coal in the last 200 years has led to their depletion.
Renewable energy sources, also known as alternative or green energy sources, are naturally replenished, clean and environmental friendly with zero or almost zero emissions of greenhouse gases and pollutants. They have the potential to meet the worldwide current and future energy demand. The solar energy is the most promising green energy source.
For a proper design of solar energy application systems, it is essential to have solar radiation data. The starting point for the radiation data is almost always global and diffuse horizontal radiation in the form of hourly or sub-hourly data. It is not always possible to obtain a long-term series of hourly or sub-hourly data for the above-mentioned parameters.
Global radiation at an hourly, daily or monthly frequency is the most commonly measured solar data and this is available for a limited number of stations. The measurement of the diffuse radiation is even scarcer due to higher operational costs associated to the measurements and meteorological offices tend to record the latter variable at much fewer locations.
On the contrary, through the work of NASA (http://eosweb.larc.nasa.gov/cgibin/ sse/retscreen.cgi?email=rets@nrcan.gc.ca) it is now possible to obtain daily-averaged irradiation data for virtually any location in the world. These data include long-term estimates of meteorological quantities and surface solar energy fluxes obtained from satellite systems.
NASA data that now is available in public domain can be used to construct a computational chain to get all manner of solar energy calculations that require hourly horizontal and slope, global and diffuse radiation data.
Using established models, it is then possible to decompose the daily to averaged-hourly global irradiation. The missing link so far has been hourly averaged diffuse irradiation. In this study data was pooled from 19 world-wide locations to obtain a regression model to complete the above missing link. It was presently shown that the averaged–data regressions are distinctly different from previously available hour-by-hour regressions.
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