1.1. General specifications

Spatially-distributed (map) solar radiation databases are classified according to several factors:

• Input data from which they have been created: (a) observations from the meteorological stations (global, diffuse and direct irradiances, and other relevant climate data), (b) digital satellite images or (c) combination of both; here also ancillary atmospheric data used in the models are considered, such as water vapour, ozone and aerosols;

• Period of time (typically a number of years) which is represented by the input data;

• Spatial resolution, i. e geographical distribution of the meteorological sites, grid resolution of the satellite data and resulting outputs;

• Time resolution, which characterises periodicity of the measurement of the input data and of the resulting parameters. Thus a primary database may include time series with periodicity of a few minutes up to hourly and daily averages (sums), or it may contain only monthly and long-term averages.

• Methodical approach used for computation of the primary database: typically solar radiation models combined with interpolation methods (e. g. geostatistical methods or splines, in case that ground observations are used) or algorithms for satellite data processing (e. g. Heliosat). Primary database typically consists of global, direct normal or diffuse irradiances (irradiation in case of time-integrated products) and also some auxiliary parameters such as clear-sky index.

• Simulation models used for calculation of derived parameters, such as global irradiance for inclined and sun-tracking surface, spectral products (e. g., illuminances, UV and PV-related irradiances), estimation of terrain effects, derived statistical products (e. g. synthetic time series).

Quality of an individual data set is assessed for a set of locations by comparing them to ground measurements, where the first order statistics is calculated (bias, root mean square deviation, standard deviation, the correlation coefficient) and the frequency distribution is analysed. In this work we focus on the relative map-based cross comparison of several solar radiation products.

Such comparison provides means for improved understanding of regional distribution of the uncertainty by combining all existing resources (calculating the average of all) and quantifying their mutual agreement by the means of standard deviation.