88th Annual Meeting (20-24 January 2008)

Tuesday, 22 January 2008: 2:30 PM
LEAD: Automatic triggering of high resolution forecasts in response to severe weather indications from the NOAA Storm Prediction Center
207 (Ernest N. Morial Convention Center)
R. B. Wilhelmson, University of Illinois at Urbana-Champaign, Urbana, IL; and B. F. Jewett, J. Alameda, A. Rossi, S. Hampton, D. Weber, K. Thomas, Y. Wang, and K. Droegemeier
Poster PDF (94.8 kB)

In Spring, 2007, LEAD, using a trigger developed by NCSA/CORE, launched WRF forecasts in support of NOAA's Hazardous Weather Testbed (hwt.nssl.noaa.gov/Spring_2007/) (HWT); this was one of three aspects of LEAD's collaborations with the HWT which are described elsewhere in this session.  The trigger  determined when and where forecasts would take place by continuously monitoring and parsing Mesoscale Discussion and Severe Weather Watch products from the NOAA Storm Prediction Center via an RSS feed. 6-hour WRF forecast workflows were then launched, monitored, post-processed and archived by the ensemble broker (http://broker.ncsa.uiuc.edu) .  Typically, 18-km, singly-nested and 2-km triply nested forecasts were triggered automatically for each SPC bulletin, using NAM data and the WPS package for initialization.  20km ARPS Data Analysis System (ADAS) initialized WRF forecasts were also triggered.  The domain centers of all WRF forecasts triggered automatically in this manner are shown in the figure below.  Overall, more than 1000 forecasts were initiated in this manner.

This work, besides providing an opportunity to have ready access to high resolution forecasts over regions of interest based on SPC observations, provided an excellent opportunity to stress-test all aspects of the workflow and computational systems involved.  This support of the SPC Spring Experiment also served as an important mechanism for further integration of the ensemble broker into LEAD, where it soon will be added as a service.  The triggered runs, carried out on production rather than dedicated resources, also pointed out the critical need for sophisticated quality of service improvements needed so that all of the important runs on a busy severe weather day complete within the needed window of time; static mechanisms to provide reserved portions of a machine are inadequate in this sense to deliver forecasts in a timely fashion on a busy day, while not waste resources on a calm weather day.

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