Sistema híbrido basado en redes neuronales artificiales y descomposición modal empírica para la evaluación de la interrelación entre la irradiancia solar total y el calentamiento global

Abstract

Resumen. El calentamiento global o cambio climático es probablemente el mayor reto científico actual de la humanidad. De todos los factores tanto naturales como antropogénicos involucrados en el calentamiento global, así como sus complejas interrelaciones, poca atención se ha centrado en los factores externos al sistema Tierra, como lo es la variabilidad solar. En este trabajo se presenta un sistema híbrido de inteligencia artificial basado en redes neuronales artificiales y descomposición modal empírica para determinar la interrelación entre la irradiancia solar total recibida en la Tierra en lasúltimas cuatro décadas con uníndice clave en el cambio climático: la temperatura superficial del mar. Los resultados hasta el momento muestran una evidente interrelación entre ambosíndices, sugiriendo que el principal motor de la variabilidad en la temperatura superficial del mar son las variaciones en la entrada de energía solar al sistema Tierra.Palabras clave: Redes neuronales artificiales, descomposición modal empírica, cambio climático, calentamiento global, irradiancia solar, inteligencia artificial, reconocimiento de patrones, temperatura superficial del mar, IA, RNA, DME.

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