Wednesday, 27 June 2007
Summit C (The Yarrow Resort Hotel and Conference Center)
The translational speeds at which mesoscale convective systems (MCSs) move span a considerable range there exist observations of systems that are nearly stationary to those that move in excess of 25 m s-1
. System speed is an important forecasting parameter, both for the immediate high-impact effects associated with the convection itself, as well as for downstream and/or upscale feedbacks. It has been noted in past studies that forecasting MCS translational speed is a complex problem. Indeed, while many factors exist to determine the MCS speed, one physical process that appears to be underemphasized is that of the downward transport of horizontal momentum. It is hypothesized here that in some fast-moving MCS cases, the downward flux of westerly momentum from upper levels may contribute to faster MCS motion near the surface. To test this hypothesis, two cases are examined one fast MCS case and one slow MCS case. Each is analyzed to assess the degree to which momentum from upper levels appears to have an effect on surface translational speed of the MCS.
An additional implication of this study of potential significance to the operational community in particular is that numerical model forecasts that employ convective parameterization (CP) schemes often neglect this effect. Most operational forecast models continue to use CP schemes to represent convective precipitation, and many operational CP schemes only adjust temperature and moisture fields, neglecting the adjustment of momentum. Thus, for systems in which these processes are important, we hypothesize that the operational NWP forecast of MCS translation speed would be underestimated.
The relative importance of vertical momentum transport in two recent squall line cases is compared by performing a momentum budget for each case using output from two high-resolution WRF simulations. The implications that momentum transport may have on MCS translational speed, as well as the significance that this process bears for forecasting and NWP model configuration for these types of events are also discussed.
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