Statistical Modeling of Spatio-Temporal Variability in Monthly Average Daily Solar Radiation over Turkey

• Main Authors: Can Ertekin, Fatih Evrendilek
• Format: Article
• Language: English
• Published: MDPI AG 2007-11-01
• Series: Sensors
• Subjects: Solar radiation; Spatio-temporal modeling; Universal kriging; Multiple linear regression; Turkey.
• Online Access: http://www.mdpi.com/1424-8220/7/11/2763/

Though one of the most significant driving forces behind ecological processessuch as biogeochemical cycles and energy flows, solar radiation data are limited or non-existent by conventional ground-based measurements, and thus, often estimated from othermeteorological data through (geo)statistical models. In this study, spatial and temporalpatterns of monthly average daily solar radiation on a horizontal surface at the ground levelwere quantified using 130 climate stations for the entire Turkey and its conventionally-accepted seven geographical regions through multiple linear regression (MLR) models as afunction of latitude, longitude, altitude, aspect, distance to sea; minimum, maximum andmean air temperature and relative humidity, soil temperature, cloudiness, precipitation, panevapotranspiration, day length, maximum possible sunshine duration, monthly average dailyextraterrestrial solar radiation, and time (month), and universal kriging method. Theresulting 20 regional best-fit MLR models (three MLR models for each region) based onparameterization datasets had R2adj values of 91.5% for the Central Anatolia region to 98.0%for the Southeast Anatolia region. Validation of the best-fit MLR models for each region led to R2 values of 87.7% for the Mediterranean region to 98.5% for the Southeast Anatoliaregion. The best-fit anisotropic semi-variogram models for universal kriging as a result ofone-leave-out cross-validation gave rise to R2 values of 10.9% in July to 52.4% inNovember. Surface maps of monthly average daily solar radiation were generated overTurkey, with a grid resolution of 500 m x 500 m.