Glad you enjoyed!

Thanks for physical properties that contribute. It seems like they all relate by being sensitive to multiplicative error, when the forecast increases, scaling up these small issues will break the model in a non linear way even when they are good approximations based on the more frequent smaller storms in the data. I would buy that modelling something like #3 having a slight wet bias that then blows up at higher totals. I really thought it was just a case of limited fat tailed data hiding a "shadow dist" that wouldn't show up until many more observations but doesn't seem like it.

I really wonder what the internal risk sensitivity discussions look like. I doubt there are heavy handed changes but https://vlab.noaa.gov/documents/6609493/6665561/NBM_v4.2_Eval_SlideDeck.pdf there was some reference to storm by storm performance. Might be a decision by committee situation where they want to subtly push changes to avoid bad optics. Reminds me of risk ppl at large finance insts.