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

Though one of the most significant driving forces behind ecological processes such as biogeochemical cycles and energy flows, solar radiation data are limited or non-existent by conventional ground-based measurements, and thus, often estimated from other meteorological data through (geo)statistical models. In this study, spatial and temporal patterns of monthly average daily solar radiation on a horizontal surface at the ground level were quantified using 130 climate stations for the entire Turkey and its conventionally-accepted seven geographical regions through multiple linear regression (MLR) models as a function of latitude, longitude, altitude, aspect, distance to sea; minimum, maximum and mean air temperature and relative humidity, soil temperature, cloudiness, precipitation, pan evapotranspiration, day length, maximum possible sunshine duration, monthly average daily extraterrestrial solar radiation, and time (month), and universal kriging method. The resulting 20 regional best-fit MLR models (three MLR models for each region) based on parameterization datasets had R(2)(adj) 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 R(2) values of 87.7% for the Mediterranean region to 98.5% for the Southeast Anatolia region. The best-fit anisotropic semi-variogram models for universal kriging as a result of one-leave-out cross-validation gave rise to R(2) values of 10.9% in July to 52.4% in November. Surface maps of monthly average daily solar radiation were generated over Turkey, with a grid resolution of 500 m × 500 m.