89th American Meteorological Society Annual Meeting

Wednesday, 14 January 2009
GOES winter precipitation efficiency algorithm
Hall 5 (Phoenix Convention Center)
Robert Rabin, NOAA / NSSL & Univ of Wisconsin / CIMSS, Madison, WI; and D. A. Sheffler and J. W. Hanna
Recent studies have shown the importance of snow microphysics for heavy snowfall. Specifically, snow production and accumulation appears to be highly efficient when a maximum in saturated vertical ascent (level of non-divergence) is collocated within a narrow temperature range (centered at -15ºC). This temperature range is favorable for efficient snow production as a result of the preferential growth of ice crystals by deposition. In addition, the dominant crystal type formed in this temperature range is dendrites, which have been shown to be conducive for high snow to liquid ratios.

To highlight areas conducive for this highly efficient snowfall a GOES Winter Precipitation Efficiency Algorithm was developed by the lead author. The GOES Winter Precipitation Efficiency Algorithm uses cloud products derived from Geostationary Operational Environmental Satellite (GOES) Imager radiances to create an analysis of the height of the pressure level at -15ºC. Further refinement of the analysis is conducted by including vertical velocity output from the Rapid Update Cycle (RUC) to highlight areas where the -15ºC pressure level is collocated with moderate lift (defined in the algorithm as -10µb/sec).

During the 2006-2007 and 2007-2008 winter seasons, NESDIS meteorologists performed objective and subjective validations on the algorithm to determine its value as an operational satellite product. The objective validation compares the derived height of the pressure level at -15ºC from the GOES Winter Precipitation Efficiency Algorithm against the actual height of this level as measured by radiosondes at each respective upper-air site. Based on results from the 2006-2007 validation, a bias correction was added to the algorithm, which resulted in a noticeable improvement during the 2007-2008 validation. Continuing validation of this product will help determine its scientific usefulness as a satellite product compared to solely using Numerical Weather Prediction (NWP) guidance.

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