Emulating the South Asian Atmospheric Variations: Framework and Inter-Comparison of Deep Learning Models
This study presents a deep learning framework that successfully emulates high-resolution South Asian atmospheric variations, including meteorological fields and ozone, by training four different architectures on WRF-Chem data, with the UNet-3blk model achieving optimal performance despite challenges in reproducing PM2.5 variability.