Extreme precipitation events represent a significant economic and societal threat to the well being of Canadians. Specific examples include the 1998 freezing-rain storm in the St. Lawrence River Valley (SLRV) that imposed more than $3 billion in economic losses. Warm-season extreme rainfalls, particularly those associated with the transition of hurricanes to extratropical cyclones, can also inflict large impacts on the citizens of eastern Canada. For example, the extratropical transitions of Hurricanes Katrina (2005), Rita (2005), and Ike (2008), each contributed more than half of the monthly rainfall climatology in the SLRV.
Given that such episodic events of extreme precipitation are so crucial to a region’s climate, we propose to attack the problem of understanding and predicting extreme precipitation events in the SLRV of eastern Canada. Our approach will involve a ‘funnelling’ of scale-dependent processes, which includes documentation of 1) planetary- and synoptic-scale atmospheric structures necessary for the production of extreme precipitation, and 2) given the necessary background atmospheric environments, determining mesoscale environments that are sufficient for the extreme precipitation processes to occur. The mesoscale environments to be studied include several contributing processes. The SLRV constitutes a significant weather-producing topographic feature documented to be crucial to the regional wind climatologies, influencing the phase of precipitation during the cold seasons, and significantly amplifying the amount of precipitation in association with ageostrophic frontogenesis.
Global (NCEP/NCAR) and regional (NARR) reanalyses will be combined with high-resolution model simulations to study crucial processes sensitive to the atmospheric vertical structure in terms of temperature, moisture and winds. Previous studies (Gyakum, 2008) have established that the precipitation intensity is related to the Extreme Precipitation Index (EPI) defined as the area-averaged column precipitable water (moisture content) times the quasi-geostrophic forcing for ascent (layer-mean Q vector convergence), divided by the static stability. The expression itself is deceptively simple, yet comprises crucial information about the nature of extreme precipitation events.