Statistical cloud coverage as determined from sunshine duration: a model applicable in daylighting and solar energy forecasting

Abstract A radiative/luminous energy budget is difficult to predict on a daily or hourly base if cloud coverage is obtained by subjective methods in discrete time points. A simple theoretical model that overcomes this shortcoming through interrelation of absolute cloud fraction and sunshine duration is presented. The latter is measured routinely at the meteorological stations worldwide. The model is based on statistical probability of clear line of sight, where Poisson spatial cloud distribution is analyzed for three different cloud shapes. A validation of the model using long-term measurements show a good correlation between experimentally determined and theoretically predicted data. The absolute cloud fraction obtained this way are a base for daylighting and solar energy applications including simulations of luminance/radiance sky distributions under different meteorological conditions. A simple calculation tool is developed and demonstrated on global horizontal illuminance (GHI).

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