Evaluación de la capacidad de pronóstico de sequías mediante análisis de índices climáticos de gran escala

Abstract

Abstract: There are various tools and techniques for predicting or forecasting the occurrence of droughts in each region where certain phenomena are involved. These tools include analyzing historical data from climate index, assessing extreme events, and using climate prediction models. Based on this, useful information can be provided to those responsible for the management of water and other natural resources to take preventive measures and to mitigate the negative effects of drought in the affected areas. This study performs a statistical analysis of the available climate data such as the indices: ENSO, AMO and PDO using correlation and regression techniques, as well as artificial intelligence to evaluate the occurrence of droughts. In addition, the ability of different climate prognosis models such as ENSO, AMO and PDO to predict the occurrence of droughts is evaluated. The results show that some of these climate prediction models have a greater ability to predict the occurrence of droughts than others.