I think this blog article did not frame the novelty of this study very well. It is not the nowcast that is the problem, it is getting nowcast at a spatial resol

I think this blog article did not frame the novelty of this study very well. It is not the nowcast that is the problem, it is getting nowcast at a spatial resolution higher than weather forecast models. But in that case, the limitation is more about computation rather than physics. What their U-Net does seems to be a fancy way of doing statistical downscaling. Needless to say, this should not be interpreted as machine learning can replace physics in weather forecast or operational meteorology (see Lorenz 1963 paper). It shines as a great data assimilation technique though.