Development and Tropical Transition of an Alpine Lee Cyclone. Part I: Case Analysis and Evaluation of Numerical Guidance

Abstract

Abstract The development and tropical transition (TT) of a subsynoptic-scale cyclone in the Gulf of Genoa during the Mesoscale Alpine Project (MAP) demonstration of probabilistic hydrological and atmospheric simulation of flood events in the alpine region (D-PHASE) project is investigated using analyses and model simulations. Cyclogenesis occurs in association with the passage of a synoptic-scale trough and attendant surface cold front across the Alps on 15 November 2007. An embedded coherent tropopause disturbance (CTD) plays an important role in promoting the initial development of the lower-level vortex by simultaneously providing quasigeostrophic forcing for ascent and reducing the bulk column stability over warm Mediterranean waters. Persistent convection thereafter erodes the CTD as the storm transitions into a hurricane-like vortex. In addition to this upper-level forcing, a pair of diabatically generated lower-level cyclonic potential vorticity (PV) features associated with distinct flow regimes is potentially important to the cyclogenetic process in this case. The first, a warm surface potential temperature anomaly, is generated during cross-barrier flow by prefrontal upslope precipitation on the Alpine northside, followed by parcel descent in the lee. The second PV feature is a mountain-scale PV banner that extends southward from the southwestern tip of the Alps as the flow is deflected around the mountain chain. Numerical guidance for this case is evaluated on its ability to accurately depict the development and evolution of the cyclone. Comparison of a triply nested integration (grid spacings of 33, 10, and 2.5 km) with observations and analyses demonstrates that the model is capable of simulating the salient features of the event. Combining reliable guidance from high-resolution modeling systems with the paradigms of lee cyclone development and the emerging concepts of TT promotes an improved understanding of these potentially high-impact events.