The Cloud Radiation Forcing Prediction Based on Textural Feature Extraction from Cloud Image

Abstract

The intermittency and instability of the solar energy resource brings great challenge to the accurate forecasting of the surface solar irradiation. In this work, based on texture characteristics analysis of sky image collected by TSI combined with SVM model, a new methods for the forecasting of cloud radiative forcing was presented. First, the texture characteristics related to solar irradiation were extracted from sky images through image processing technologies, including contrast, entropy, grayscale and energy; Then regression model was built between image characteristics and irradiation reduction coefficient; Finally, the SVM model was used to forecasting cloud radiation forcing. The experiment results indicated that: the forecasting accuracy of the method based on texture characteristics tends to provide better a performance than traditional forecasting method and forecasting method based on cloud block movement prediction. It can provide important reference for the accurate forecasting of surface solar irradiation on complex climate conditions.