Resumen

AGUADO-RODRIGUEZ, G. Javier et al. Meteorological variables prediction through ARIMA models. Agrociencia [online]. 2016, vol.50, n.1, pp.1-13. ISSN 2521-9766.

Meteorological variables prediction is applied in agriculture to predict water uptake of plants for planning irrigation depths. In the present study a program was made for the prediction of temperature, solar radiation, reference evapotranspiration and relative humidity by means of autoregressive integrated mobile media models. The effectiveness of the program was tested for prediction under high and low rainfall conditions. The prediction periods evaluated were in March and in June, 2013, in three automatic meteorological stations (EMAS) of the National Meteorological Service (SMN). The analysis of results indicated that the prediction of meteorological variables with ARIMA models was better than with persistent prediction in the period with low rainfall conditions (March).

Palabras llave : Prediction; R Statistics; real time.

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