Monday, 12 January 2004
Cold season 500 hPa cutoff cyclone precipitation distribution and a case study
Room 4AB
Anthony R. Fracasso, University at Albany/SUNY, Albany, NY; and L. F. Bosart, D. Keyser, and M. Evans
Poster PDF
(1.1 MB)
Cutoff cyclones pose a challenge to forecasters, especially in the northeastern United States. A climatology of cold season (October - May) cutoff cyclones has been produced for the period 1948-1998 using the gridded reanalysis datasets available from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR). Similarly, the NCEP Unified Precipitation Dataset (UPD), a once-daily (1200-1200 UTC) gridded precipitation dataset available on a 0.25 deg grid, has been used to construct precipitation maps for all cases where a cutoff cyclone was present in the northeast US and vicinity. The purpose of this presentation is to use these datasets to diagnose and understand the distribution of precipitation associated with the passage of cutoff cyclones in the Northeast by means of composite and case studies, and to identify whether there are characteristic precipitation signals associated with particular cutoff cyclone tracks.
Ongoing research is focused on stratifying precipitation as a function of cutoff cyclone track and intensity in an effort to determine whether a track-dependent precipitation signal exists for cutoff cyclones as they cross a region of complex terrain. Individual case studies representative of specific cutoff cyclone tracks will also be examined as part of this research effort. As an example, a recent cutoff cyclone that posed a significant forecast challenge occurred in late May 2003. The cutoff cyclone tracked across the Great Lakes and over New York State. Although heavy rains were forecast for most of the area, some locations received well under 25 mm, while other areas received closer to 100 mm over a period of a few days. The structure and evolution of this cutoff cyclone and its associated precipitation shield will be examined.
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