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Monthly Average Temperature Modeling in an Intertropical Region

Mercedes Andrade-BejaranoSchool of Statistics, Universidad del Valle, Santiago de Cali, Colombia

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Abstract

Data for this research come from time series of monthly average temperatures from 28 sites over the Valle del Cauca of Colombia in South America, collected over the period 1971–2002. Because of the geographical location of the study area, monthly average temperature is affected by altitude and El Niño–La Niña (El Niño–Southern Oscillation, or ENSO phenomenon). Time series for some of the sites show a tendency to increase. Also, because of the two dry and wet periods in the study area, a seasonal pattern of behavior in monthly average temperature is seen. Linear mixed models are formulated and fitted to account for within- and between-site variations. The ENSO phenomenon is modeled by the Southern Oscillation index (SOI) and dummy variables. Spatial and temporal covariance structures in the errors are modeled individually using isotropic variogram models. The fitted models demonstrate the influence of the ENSO phenomenon on monthly average temperatures; this is seen in the maps produced from the models for ENSO and normal conditions. These maps show the predicted spatial patterns for differences in temperature throughout the study area.

Corresponding author address: Mercedes Andrade-Bejarano, School of Statistics, Universidad del Valle, Apartado Aéreo 25360, Cali, Colombia. E-mail: mercedes.andrade@correounivalle.edu.co

Abstract

Data for this research come from time series of monthly average temperatures from 28 sites over the Valle del Cauca of Colombia in South America, collected over the period 1971–2002. Because of the geographical location of the study area, monthly average temperature is affected by altitude and El Niño–La Niña (El Niño–Southern Oscillation, or ENSO phenomenon). Time series for some of the sites show a tendency to increase. Also, because of the two dry and wet periods in the study area, a seasonal pattern of behavior in monthly average temperature is seen. Linear mixed models are formulated and fitted to account for within- and between-site variations. The ENSO phenomenon is modeled by the Southern Oscillation index (SOI) and dummy variables. Spatial and temporal covariance structures in the errors are modeled individually using isotropic variogram models. The fitted models demonstrate the influence of the ENSO phenomenon on monthly average temperatures; this is seen in the maps produced from the models for ENSO and normal conditions. These maps show the predicted spatial patterns for differences in temperature throughout the study area.

Corresponding author address: Mercedes Andrade-Bejarano, School of Statistics, Universidad del Valle, Apartado Aéreo 25360, Cali, Colombia. E-mail: mercedes.andrade@correounivalle.edu.co
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