Variability and forecasting of air temperature in Elqui Valley (Chile)

method to forecast air temperature T A in Elqui Valley (south of Chile’s Atacama Desert) using an artificial neural network (ANN) and meteorological time series data relevant to this zone, is proposed. This zone has one of the most sensitive climates in South America due to the influence of phenomena such as El Niño/La Niña , the Southeast Pacific Subtropical Anticyclone, Humboldt Current, and Madden–Julian Oscillation, in addition to the complex topography of Chilean east-west transverse valleys, and the Andes. We used a method that combines ANN and genetic algorithm (GA) for forecasting T A 1, 3, and 6 hours ahead. GA is introduced to optimize the weights update process in the proposed method. Our database contains 457,969 data, from 2004–2017, taken from eight stations throughout the valley and divided into three datasets: training set with 50