The formation and impact of an incipient cold-air precipitation feature on the 24--25 January 2000 East Coast cyclone

The 24--25 January 2000 East Coast cyclone was characterized by a major operational forecast failure. In an effort to understand why short-range operational numerical weather prediction (NWP) model forecasts were so poor, the impact of a cold-air incipient precipitation (IP) feature that developed prior to the rapid cyclogenesis on 24 January is investigated using potential vorticity (PV) analysis. The IP was poorly forecasted by the operational NWP models, which subsequently failed to produce precipitation far enough inland over the Carolinas and Virginia. The formation of the IP is examined from an observational perspective, its impact is quantified using PV methodology, and the ability of an NWP model to simulate its formation is tested by varying model physics, initial conditions and grid spacing.; Calculations from a PV budget and piecewise PV inversion show that the IP was associated with the genesis of a lower-tropospheric PV maximum. The balanced flow associated with the PV maximum contributed to moisture transport into the region of heavy snowfall. The IP formed in a region of elevated conditional instability and conditional symmetric instability (CSI) and forcing for ascent was provided by an approaching upper-level trough/jet streak. An 18-member mesoscale model ensemble varying initial condition analyses and model physics was unable to generate the IP. A high-resolution model simulation with 4-km grid spacing showed that the initial IP formation occurred within a layer of elevated CSI, consistent with analyses. Simulations with larger grid spacing degraded the representation of these features. The current configuration of operational models with grid spacing insufficient to fully resolve slantwise convection suggests that cases may occur where NWP models fail to capture the impact of a cold-air precipitation feature, resulting in poor forecasts of downstream moisture transport and cyclone evolution. Operational forecasters should be aware of this possibility and anticipate the potential feedbacks from precipitation onto atmospheric dynamics using PV thinking to adjust model guidance and hopefully improve forecasts in high-impact situations.