2B.2 Storms on the rock: Synoptic-scale characteristics and typing of cool-season precipitation events at St. John's, Newfoundland (1979-2005)

Monday, 1 June 2009: 10:45 AM
Grand Ballroom West (DoubleTree Hotel & EMC - Downtown, Omaha)
Shawn M. Milrad, McGill University, Montreal, QC, Canada; and E. Atallah and J. R. Gyakum

The issue of Quantitative Precipitation Forecasting (QPF) continues to be a significant challenge in operational forecasting, particularly in regions susceptible to extreme precipitation events. St. John's, Newfoundland (CYYT) is one location affected frequently by such events, particularly in the cool season (October-April). These events can include flooding rains, paralyzing snow, and damaging winds.

First, a precipitation climatology is developed at St. John's for 1979-2005, based on discrete precipitation events occurring over a time period of 48 hours or fewer. Second, threshold amounts for categories of precipitation events (extreme, moderate, light) are statistically derived and utilized to categorize such events.

Subsequently, two separate methodologies are used to partition events within a precipitation category into various synoptic types. The first method uses a backward air parcel trajectory analysis and the second is based on several dynamically relevant variables, such as warm air advection (WAA), frontogenesis, and vorticity advection (VA).

Composite and anomaly plots of sea-level pressure, 500 hPa height and precipitable water are presented to depict synoptic-scale similarities and differences among the three threshold precipitation amounts as well as within each precipitation intensity category, with a focus on extreme events. In addition, composite thermodynamic (sounding) analyses will be presented to illustrate differences in thermodynamic structure among synoptic types. Finally, there is an examination of the predictability of a recent case (December 2008) using NCEP ensemble forecast models.

It is our hope that the unique methodology and results of the synoptic typing in this project will aid forecasters in identifying certain characteristics of future precipitation events at St. John's and similar stations.

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