Through the classical approaches, it is difficult to find atmospheric effect to extraterrestrial solar irradiation and length of day. As seen in Fig. 6.8 global irra – diance mostly reaches the surface depending on sun position’s, sunrise and sunset times. In a partially cloudy day, there would be some discontinuities for measurements during the day, these detailed reduction and variation appear as randomness
in Fig. 6.8 which is a good example for atmospheric conditions and variability in order to receive solar irradiation. According to the suggestion in this equation, extraterrestrial variable ratio S0 /H0 is assumed to have a reduction amount, Re, due to cloud cover, dust, humidity, etc.
Such reductions in sunshine duration and solar irradiation are measured on the horizontal surface. There is a relation between extraterrestrial and terrestrial ratios due to atmospheric effects. This reduction effect can be expressed as
S0 (1 _Re) = S
where Re represents extraterrestrial ratio reduction amount. The reduction factor results fromEq. (6.33) as,
Given the astronomical calculations of H0 and S0 together with measurements of the H and S, Re can be calculated easily from Eq. (6.34). If Re is known then terrestrial sunshine duration S and solar irradiation H can be estimated as
This formulation has the following advantages,
1. Atmospheric effect to extraterrestrial solar components can be explained easily. In other words, reduction amount in solar irradiation or length of day can be evaluated by proposed method,
2. Angstrom equation parameters (a and b) need for each period (month, day or hour) a long time measurements for each station. This method provides reduction in the parameter evaluations for each month, day or hour. In other words, atmospheric effects to extraterrestrial solar variables are monitored for each period, and
3. In the proposed method, there is no need for least square technique parameter estimation procedure and no restrictive assumption. As mentioned earlier, there are six assumptions in the least square methodology like Angstrom linear equation applications. However, in the proposed approach there is no assumption.