کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
299965 512465 2015 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A technique to map monthly average global illuminance from satellite data in the tropics using a simple semi-empirical model
ترجمه فارسی عنوان
یک تکنیک برای نشان دادن ماهیت میانگین ماهیت جهانی از داده های ماهواره ای در مناطق گرمسیری با استفاده از یک مدل نیمه تجربی ساده
کلمات کلیدی
روشنایی جهانی، داده های ماهواره ای، مدل، گرمسیری
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی


• A technique to map monthly average global illuminance from satellite data in the tropics was proposed.
• The illuminance was estimated using a simple semi-empirical model.
• Values of measured and estimated illuminance are in good agreement.
• Monthly average illuminance maps over Thailand were produced.

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable Energy - Volume 74, February 2015, Pages 170–175
نویسندگان
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