Mean preserving algorithm for smoothly interpolating averaged data

Hourly mean or monthly mean values of measured solar radiation are typical vehicles for summarized solar radiation and meteorological data. Often, solar-based renewable energy system designers, researchers, and engineers prefer to work with more highly time resolved data, such as detailed diurnal profiles, or mean daily values. The object of this paper is to present a simple method for smoothly interpolating averaged (coarsely resolved) data into data with a finer resolution, while preserving the deterministic mean of the data. The technique preserves the proper component relationship between direct, diffuse, and global solar radiation (when values for at least two of the components are available), as well as the deterministic mean of the coarsely resolved data. Examples based on measured data from several sources and examples of the applicability of this mean preserving smooth interpolator to other averaged data, such as weather data, are presented.