This phenomenon disrupts the order of predicted values in weather forecasts. This phenomenon arises from the numerical weather prediction (NWP) process involving observations and atmospheric evolution laws. Past attempts explored nonparametric methods like quantile regression neural networks (QRNN) and their variants, designed to output quantiles reflecting value ranks in the forecast distribution.