Diagnosing Synoptic Progressiveness Forecast Errors in Cut-Off Low Events

Cutoff low systems are often associated with high-impact weather events, such as heavy rainfall, severe convection and winter hazards. Forecast model errors associated with cutoff low events were recently documented in a study by Lupo et al. (2023) for the Global Forecasting System (GFS), where a systematic progressiveness error was identified in medium-range forecasts of cutoff low systems. Here, we investigate potential sources of these progressiveness forecast errors using the Unified Forecast System Medium-Range Weather Application (UFS-MRW App). Simulations of 24 cutoff low events that exhibited large eastward zonal position errors in the GFS forecasts over the conterminous United States have been conducted. The same physics suite as that was in operational use is used in these simulations. Cutoff-low progressiveness errors in the UFS-MRW simulations are found to be similar to those identified in the GFS forecasts, supporting the use of the MRW App as a tool to investigate sources of model errors. Forecast evolution of the cut-off lows at early lead times compares well with those diagnosed from GFS analyses. Diabatic processes due to convection and radiation can have a strong impact on cutoff lows. Our analysis will focus on the composite model tendencies from the UFS-MRW simulations related to these processes, and demonstrate their use in the identification of potential sources of model errors that may have contributed to the systematic progressiveness error.