Extended Abstract (456K)P3.4
The distribution of precipitation over the Northeast accompanying landfalling and transitioning tropical cyclones
David P. DeLuca, University at Albany/SUNY, Albany, NY; and L. F. Bosart, D. Keyser, and D. R. Vallee
Landfalling and transitioning tropical cyclones pose a significant challenge in forecasting distributions of heavy precipitation in the northeastern United States. The forecast challenge is heightened because the heavy rainfall distribution associated with these tropical cyclones can be modulated significantly when the poleward-moving storms interact with mobile midlatitude upper-level troughs and coastal fronts over regions of complex terrain. The purpose of this presentation is to document the large spatial and temporal variability of heavy precipitation that accompanies landfalling and transitioning tropical cyclones and to determine the physical basis for the observed rainfall distribution.
A 38-storm dataset of landfalling and transitioning tropical cyclones that produced at least 10 cm (4 ") of precipitation during 1950-1998 has been constructed. The NCEP 24 h daily (1200-1200 UTC) Unified Precipitation Dataset (UPD) and the twice-daily (0000 and 1200 UTC) NCEP/NCAR reanalysis dataset were used to produce maps of storm rainfall and synoptic-scale circulation features for each of the 38 storms. The 38-storm dataset also served as the basis for the preparation of maps showing the rainfall distribution relative to the track of each tropical cyclone. The National Hurricane Center (NHC) best track dataset at 6 h intervals (0000, 0600, 1200 and 1800 UTC) was used to define the 38 individual storm tracks.
This presentation will focus on the analysis of storm-total precipitation relative to storm track in an effort to identify the impact of complex terrain and coastal fronts on the observed precipitation distribution. It will also examine how storm-trough interactions and diabatically induced outflow in the downstream ridge/jet feed back on and impact the observed precipitation distribution. Model forecast biases associated with this diabatically induced outflow will be identified from archived model gridded forecast datasets for landfalling and transitioning tropical cyclone events.
Poster Session 3, Wednesday Posters
Wednesday, 14 January 2004, 2:30 PM-4:00 PM, Room 4AB
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