Abstract
This paper presents a technique to map monthly average hourly global illuminance from satellite data. A semi-empirical model relating monthly average global illuminance to cloud index, precipitable water, total ozone column (TOC), aerosol optical depth (AOD) and air mass was developed. Data for the cloud index, AOD and TOC were obtained from the visible imagery data of MTSAT-1R, MODIS/Terra and OMI/Aura satellites respectively, while precipitable water was extracted from NCEP/NCAR reanalysis database. The model was formulated using global illuminance measured at four stations in Thailand for a four-year period and validated with an independent one-year data set. Values of monthly average hourly global illuminance calculated from the model and those obtained from the measurements were in good agreement, with a root mean square difference (RMSD) and mean bias difference (MBD) of 8.1% and −0.8%, respectively. The model was used to calculate monthly average hourly global illuminance over Thailand and the results were displayed as illuminance maps. The maps reveal diurnal and seasonal effects mainly in response to solar zenith angle changes and cloud cover related to the southwest and northeast monsoons.
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