Developing and Validating Satellite-based Models for Solar Irradiance Retrieval over Desert Environments: UAE Case Study

Abstract

Remote estimation of the direct normal irradiance (DNI) and global horizontal irradiance (GHI) by means of satellite images has been benchmarked against ground measurements in several locations worldwide. Few studies have been previously carried out over the Arabian Peninsula, where the unique climatic conditions, characterized by high concentrations of airborne dust particles and high humidity, make this region an interesting case. The objective of this research is to develop and validate models to estimate the DNI, diffuse horizontal irradiance (DHI) and GHI at the surface of the UAE at 15min temporal and 3km spatial resolutions through the employment of SEVIRI images (onboard Meteosat Second Generation satellite). Heliosat-2 method, for GHI estimation, is recalibrated and obtained results over four stations combined show a relative root mean square error (rRMSE) of 10.1% and a relative mean bias error (rMBE) of -0.5%. A model to estimate the DNI, DHI and GHI utilizing thermal channels of SEVIRI as inputs to an artificial neural network ensemble is developed. Results of this approach for an independent dataset over two stations in the UAE obtained rRMSE values of 15.7, 23.6 and 7.2% for the DNI, DHI and GHI, respectively, and rMBE values of +0.8, +8.3 and +1.9%, respectively.

Date of Award	2012
Original language	American English
Supervisor	Mohamed Hosni Ghedira (Supervisor)