Missing data assessment in a solarimetric network

Abstract

AbstractPrincipal components analysis was applied to solar irradiation (energy per unit area integrated over a daily period) in Paraiba State, north‐east Brazil, in order to find homogeneous subregions. The network data set included measurements of 19 solarimetric stations, generated by bimetallic Robitzsch‐type actinographs with associated daily errors not greater than 5 per cent. Two months were considered (February and August 1976).A simple procedure is developed for assessing missing data in time series of any station in the network, based on the remaining known data and on a small number of network eigenvectors. If applied over a homogeneous subregion, a specific new principal components analysis leads to a lower dimensioned system with even fewer eigenvectors used for proper assessment of missing data. Standard deviation of errors is lower than half the data standard deviation (the same order of expected instrumental errors). The method may be adapted easily in order to simulate (synthetize) time series of a site with no station, provided that time correlation fields vary smoothly within the region.