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Mike Evans

Use of a historical analog-based winter storm guidance package for forecasting a central New York snow event. Mike Evans. Motivation. Models are often better at forecasting large scale patterns than quantitative precipitation.

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Mike Evans

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  1. Use of a historical analog-based winter storm guidance package for forecasting a central New York snow event Mike Evans

  2. Motivation • Models are often better at forecasting large scale patterns than quantitative precipitation. • Forecasters often make forecasts by examining model forecasts of large-scale patterns, then evaluating qpf based on experience. • “Based on my experience, what type of precipitation pattern does this type of storm produce?”. • “Does the model QPF look reasonable?”. • This type of methodology should best be employed by forecasters with the most experience.

  3. Motivation • …Forecast skill is largely determined by experience. The relative advantage of highly experienced forecasters is secured by virtue of the larger set of cases from which they many draw upon…. - Roebber and Bosart, 1996

  4. Motivation continued… • ….There were major variations in the experience and perceived abilities of the Phoenix teams, generally producing the expected variations in performance. Teams composed of more senior and capable forecasters produced the greatest improvements (over guidance)… - McCarthy, Purcell and Ball, 2007

  5. The problem…. • “I can’t remember what happened yesterday, let alone what happened with some storm from 5 years ago” - An unidentified lead forecaster with many years of experience

  6. The Saint Louis University Historical Analog-Based Winter Weather Guidance System • Aids forecasters by providing easy access to a data set of winter storm events that are similar to upcoming, forecast events. • “Instant Experience”

  7. The Saint Louis University Historical Analog-Based Winter Weather Guidance System • Ingests current GFS forecasts of large-scale forecast patterns • Searches the NARR data base to find the best historical analogs to the current forecast • Returns information on the analogs • Mean fields, and probabilistic information is included • Detailed information on the top 15 analogs is included

  8. Parameters that determination the top 15 analogs • Parameters are determined within a user-selectable domain (2 east-coast domains, 2 mid-west domains). • 300 and 500 and 850 hPa heights. • 850 hPa temperature and theta-e advection. • 850 and 700 hPafrontogenesis. • Surface temperature and sea-level pressure. • Precipitable water. • Storm track is included in the calculation. • For details, see: http://intra.crh.noaa.gov/metdat/ssd/2008-12-16 13.01_SLU_Analog_Seminar.wmv.

  9. http://www.eas.slu.edu/CIPS/ANALOG/analog.php

  10. Select a model run for comparison

  11. 15 analogs are returned – with information on the analogs available

  12. Example – December 31, 2008

  13. Sea-level pressure and 1000-500 mb thickness – December 31, 2008

  14. 700 hPa heights and frontogenesis

  15. Vertical motion, temperature and NAM QPF – December 31, 2008

  16. How much snow have similar systems historically produced for our area?

  17. Mean 500 hPa heights and sea-level pressure from the 15 analogs

  18. Probabilistic snowfall information from the 15 analogs

  19. Best analog – February 26, 1994

  20. Best analog – observed snowfall

  21. 2nd best analog – January 13, 2000

  22. 2nd best analog – observed snowfall

  23. Observed snowfall – December 31, 2008

  24. Conclusion • Probabilistic information from the analogs indicated a high probability for greater than 2 inches of snow across central NY, with lower probabilities of 4 and 6 inches. • The best analogs indicated that a west-east band of 6 to 10 inches would be possible across central New York.

  25. In this case, the guidance system… • Provided “instant experience” to the forecaster for these types of systems. • Allowed forecasters to assess the “reasonability” of the model QPF, and corresponding snowfall amounts. • Other cases showed similar results. • Still waiting to assess the system for a major nor’easter.

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