Revista Brasileira de Meteorologia · 2016 · 16 citations · 21 references
Natural SciencesEarth SciencesGeographyClimatologySpatial Data AnalysisTime Series AnalysisGeostatistical ModelingPrecipitationPrecipitation EstimationSpatial Time SeriesCokrigingData ImputationKrigingOrdinary KrigingRainfall Time Series AnalysisSpatio-temporal Data ModelSpatio-temporal KrigingSpatio-temporal Missing Data Imputation
Abstract Spatio-temporal modelling is an area of increasing importance in which models and methods have often been developed to deal with specific applications. In this study, a spatio-temporal model was used to estimate daily rainfall data. Rainfall records from several weather stations, obtained from the Agritempo system for two climatic homogeneous zones, were used. Rainfall values obtained for two fixed dates (January 1 and May 1, 2012) using the spatio-temporal model were compared with the geostatisticals techniques of ordinary kriging and ordinary cokriging with altitude as auxiliary variable. The spatio-temporal model was more than 17% better at producing estimates of daily precipitation compared to kriging and cokriging in the first zone and more than 18% in the second zone. The spatio-temporal model proved to be a versatile technique, adapting to different seasons and dates.
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