Estimation of diurnal total radiation based on meteorological variables in the period of plant vegetation in Poland

Abstract

The paper presents selected models for the estimation of diurnal total radiation on the basis of other meteorological variables (using simple data as temperature and rainfall) in the vegetation months in the territory of Poland. For that purpose 6 meteorological stations were selected, having standard meteorological data as well as total radiation data for the period of 2001 – 2010. The stations were chosen so that two of them were situated on the coast, two in the lowland part of the country, and two in the mountains. The models were evaluated with the use of the coefficient of determination R² and the relative error of estimation RMSE with division into 6 months and 6 meteorological stations. In each of the regions the best results were obtained for models 6 and 7 which are combinations of the remaining models and additionally the constructed variable ΔT, used in other non-linear models analysed in the other studies. The best fit for those models was obtained for the mountain stations (R² from 0.67 to 0.75, RMSE from 2.7 to 4.4). The poorest estimation was obtained for the coastal stations (R² from 0.41 to 0.67, RMSE from 2.6 to 5.1). The paper does not indicate the best month in terms of the fitting, due to the high variation of results for the stations and the models.

Estimating Daily Global Solar Radiation with No Meteorological Data in Poland

“…The best source of information on global solar radiation is its measurement results; however, due to the lack of sufficiently dense actinometric network, a modeling approach is a common practice. There are different types of models based on meteorological elements, including those which use sunshine duration as an input variable, i.e., the classic Angström formula [10,11] and its modified versions [12][13][14]; those based on the relationship between solar radiation and air temperature [15][16][17]; and models utilizing cloudiness [18,19], relative air humidity [20], or precipitation [21].…”