Aiding the Earth System Models with Super Resolution Deep Learning

Abstract

From the food we eat, the air we breathe, and the water we drink, climate change affects everything around us. Continual research on this topic has produced sophisticated climate simulation models that run in high- and ultra-high resolution and provide unprecedented details at the local level. However, an enormous computational cost is associated with running such models, limiting parameter calibration, and extensive experimentation. We employ two state-of-the-art deep learning approaches to upscale computationally cheaper low-resolution simulation data into high resolution. Our initial results suggest that deep learning models are a viable approach that outperforms existing baselines.