| ABSTRACT | Abstract
Cloudiness is considered as the the major atmospheric parameter that affects the transfer of solar irradiance through the atmosphere. Depending on type, coverage of the sky, height, position relative to the Sun and velocity, clouds could diminish solar irradiance reaching the ground or cause enhancements well above the solar constant. This complex effect of clouds on the direct and diffuse components of solar irradiance cannot usually be simulated by satellite-derived or model-calculated irradiances.
In this study, we use 1-minute averaged values of global horizontal, direct normal and diffuse horizontal irradiances (GHI, DNI and DHI respectively) for a 2-years period at Patras, South Greece (38.3oN, 21.8oE, 50m a.s.l.), to analyze the variability of solar irradiance due to cloudiness. For this reason, irradiance measurements are accompanied by a collocated digital imaging system to provide the cloud coverage, type and visible percentage of the Sun disk. Solar irradiance measurements are taken by a Rotating Shadowband Radiometer, programmed to measure GHI at 1Hz, that has a shadow cast on the sensor allow the determination of DHI and subsequently the calculation of DNI from GHI and DHI. A VIS-J1006 camera system (equipped with a fish-eye lens) is used for taking sky images that are processed by software to derive the cloud properties. Model-calculated irradiances under clear skies are used to define the extent of decrease or enhancement caused by cloudiness. For this reason, the LibRadtran radiative transfer model is used, by taking into account climatic vertical profiles for the basic atmospheric gases for a midlatitude site like Patras, Greece.
According to results, the cloud type and the relative position to the Sun have the most significant effect on solar irradiance variability by causing changes between -900 to +300 W/m2 relative to the clear sky values. A detailed analysis is provided about the statistical importance of the enhancement events. Specific examples are provided as well as cases are classified according to the cloud conditions aiming to contribute on the reduction of uncertainties on modeled radiative fluxes, satellite-derived estimates of DNI and GHI and solar irradiance variability to the local scale.
Acknowledgments: The authors are indebted to CMS-Ing. Dr Josef Schreder for providing the VIS-J1006 camera. The libradtran team is acknowledged for providing the model algorithm. The study was partly funded by FP7-ENERGy project DNICast (dnicast-project.net), Grant Agreement 608623. |