A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts

Understand

Despite continuous improvements, precipitation forecasts are still not as accurate and reliable as those of other meteorological variables.

• A major contributing factor to this is that several key processes affecting precipitation distribution and intensity occur below the resolved scale of global weather models.
• Generative adversarial networks (GANs) have been demonstrated by the computer vision community to be successful at super-resolution problems, i.e., learning to add fine-scale structure to coarse images.
• Leinonen et al.