Monday, 1 August 2005
Regency Ballroom (Omni Shoreham Hotel Washington D.C.)
Matthew D. Greenstein, University at Albany/SUNY, Albany, NY; and L. F. Bosart, D. Keyser, and D. J. Nicosia
Cold-season precipitation in the northeastern United States not only falls in different frozen forms, but also is manifested in a variety of spatial patterns easily seen on radar imagery. Although forecasters can predict likely areas of precipitation, considerable difficulty remains in properly identifying mesoscale precipitation areas within the main precipitation shield. As viewed on a radar image, precipitation can appear splotchy, relatively uniform, banded, or a combination of all three. Being able to forecast such characteristics of the precipitation is vital in adding value to a forecast through enhanced mesoscale prediction of snowfall totals and variability within a domain. Therefore, the purpose of this research is to examine the role of mesoscale features in the structure and evolution of precipitation regions in Northeast winter storms.
Warm air advection-driven, or overrunning, precipitation often contains important mesoscale features, as does differential cyclonic vorticity advection-driven wrap-around precipitation. This presentation focuses on just warm advection events. Northeast winter storms exhibiting such mesoscale precipitation areas are used to create storm-relative flow composites from which quasi-geostrophic and mesoscale forcing signatures are derived. Appropriate horizontal maps and cross sections are created to ascertain relationships between these forcings and the modes of precipitation. Specifically, this presentation will exhibit composites of 10 recent warm advection precipitation events, along with radar and satellite imagery, to demonstrate connections between, for example, moist symmetric instability and mesoscale bands oriented along the thermal wind. A representative case study from the 20042005 winter is included to document the connections between synoptic and mesoscale features and precipitation mode.
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