Sensitivities of a Squall Line over Central Europe in a Convective-Scale Ensemble

作者
Kirsty E. Hanley,Daniel J. Kirshbaum,Nigel M. Roberts,Giovanni Leoncini
出处
期刊:Monthly Weather Review [American Meteorological Society]
卷期号:141 (1): 112-133 被引量:49
标识
DOI:10.1175/mwr-d-12-00013.1
摘要

Abstract Convective-scale ensemble simulations with perturbed initial and lateral boundary conditions are performed to investigate the mechanisms and sensitivities of a central European convection event from the Convective and Orographically Induced Precipitation Study (COPS). In this event, a “primary” squall line developed ahead of a decaying mesoscale convective system (MCS) upstream of the Vosges Mountains (France), weakened over the Rhine valley, then regenerated as a “secondary” squall line over the Black Forest Mountains (Germany). All ensemble members captured the squall-line evolution, but most suffered from a delay in the onset of convection and positional errors of 50–150 km over the COPS region. These errors in the secondary initiation were linked to errors in the primary initiation. Detailed analysis revealed a similar primary initiation mechanism in all members: in the ascending branch of a midlevel frontal circulation ahead of the MCS, convection initiated within a mesoscale moisture anomaly embedded within the prefrontal flow. The differences in the skill of the ensemble members were related to subtle differences in their initial upper-level representation of potential vorticity (PV). Members that verified well possessed a stronger PV gradient at the leading edge of an upper-level trough. This led to more rapid cyclogenesis over northern France and the United Kingdom and faster development and propagation of the midlevel front and the prefrontal moisture anomaly. As a consequence, the squall lines in these members developed earlier and closer to the COPS region. This case study provides an example of the subtle mechanisms by which errors on the larger scales may transfer to the convective scale and lead to errors in quantitative precipitation forecasts.

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