Abstract
The network of weather stations in Brazil is very recent, with few stations in the country possessing data over more than 100 years. In addition, many of the series from these stations present missing data, either due to lack of measurement (in the case of conventional stations) or due to equipment failures (in the case of automatic stations). There are different methods in the literature for filling these gaps. In this work, six methods are compared and applied to series of known monthly data for mean compensated temperature and precipitation for weather stations located in the State of Rio Grande do Sul, in Southern Brazil. The results for mean compensated temperature suggest that multiple linear regression methods and regional weighing are best suited for estimating missing data, while for precipitation there was no superior method.
Keywords:
meteorological stations; missing data; gap filling methodologies; compensated mean temperature; precipitation
