Prediction of Daily Ambient Temperature and Its Hourly Estimation Using Artificial Neural Networks in an Agrometeorological Station in Castile and León, Spain.

This study evaluates the predictive modeling of the daily ambient temperature (maximum, T; average, T; and minimum, T) and its hourly estimation (T, …, T) using artificial neural networks (ANNs) for agricultural applications. The data, 2004-2010, were used for training and 2011 for validation, recorded at the SIAR agrometeorological station of Mansilla Mayor (León). ANN models for daily prediction have three neurons in the output layer (T(t + 1), T(t + 1), T(t + 1)).