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Fly - Fight - Win 2 d Weather Group Mr. Evan Kuchera HQ AFWA 2 WXG/WEA Template: 28 Feb 06 Approved for Public Release - Distribution Unlimited AFWA Ensemble Prediction System
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Fly - Fight - Win 2 Overview Purpose: To discuss progress towards an AFWA ensemble prediction system AFWA is exploring how ensembles can best be exploited to improve DoD forecast processes and warfighter decision making Diverse global and mesoscale models Probabilistic algorithms for “high impact” variables Concise, warfighter-focused products Emphasis on training and outreach
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Fly - Fight - Win 3 Webpage https://weather.afwa.af.mil/host_home/DNXM/JEFS/jefs.html Available products for global (JGE) and mesoscale (JME): Precipitation Amount Precipitation Type Snow Amount Cloud Cover Lightning Dust Lofting Severe Weather Blizzard Surface Wind Gust Visibility Wind Chill Heat Index Realtime verification also available on webpage
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Fly - Fight - Win 4 Mesoscale Ensemble Pre-processing GFS ensemble from six hours earlier is used for initial/lateral boundary conditions Model configuration 10 independent model configurations with varying physics and lower boundary conditions (land surface, SSTs) run twice a day Also producing 31-member merged JME-SREF over CONUS The table lists different physics packages used by each member
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Fly - Fight - Win 5 Current Mesoscale Domains 30 km 10 km 30 km 10 km 3 km SWA East Asia CONUS 3 km resolution reserved for complex terrain areas 30/10 resolutions best for available resources Hourly output on the 10 km domains to 48 hours
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Fly - Fight - Win 6 8-day storm forecast
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Fly - Fight - Win 7 Calibration Algorithms As opposed to “traditional” calibration… Observations/gridded analysis for real-time calibration are not always available Real-time calibration can reduce skill in forecasting rare events and pattern changes Use regression with past model-obs data sets and physics-based algorithms to produce a climatologically calibrated forecast Accounts for diagnosis uncertainty for unresolved variables Does not necessarily account for model biases Lightning, visibility, and precipitation type created so far
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Fly - Fight - Win 8 30 hour ice storm forecast “MIX” PROBABILITY FRZR PROBABILITY SNOW PROBABILITY
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Fly - Fight - Win 9 21 hr lightning forecast
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Fly - Fight - Win 10 Dust Lofting—30 hr fcst
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Fly - Fight - Win 11 Precipitation Meteogram Observations in circles
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Fly - Fight - Win 12 Surface Wind Meteogram
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Fly - Fight - Win 13 Objective Verification
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Fly - Fight - Win 14 Way Ahead Global (2009) Begin work to operationalize products that are ready Mesoscale (2009-2011) Further work needed to generate more representative mesoscale initial condition/model perturbations—crucial to success Continue making products in development environment Statistical post-processing work also important Forecast variables of interest with algorithms; mitigate biases Large effort required—reserved for highest impact variables Training and outreach Outreach to decision makers; work hand-in-hand with forecasters for maximum exploitation capability Formalize training on certainty forecasting principles
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