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Bulk Statistics on Ensemble Model Forecasts for MDSS Demo 2003

Bulk Statistics on Ensemble Model Forecasts for MDSS Demo 2003. Paul Schultz NOAA Forecast Systems Laboratory June 17, 2003. 2. The MDSS ensemble modeling component. What is it? Several computer model forecasts to supplement the NWS model forecast services Why are we doing this?

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Bulk Statistics on Ensemble Model Forecasts for MDSS Demo 2003

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  1. Bulk Statistics on Ensemble Model Forecasts for MDSS Demo 2003 Paul Schultz NOAA Forecast Systems Laboratory June 17, 2003

  2. 2 The MDSS ensemble modeling component • What is it? • Several computer model forecasts to supplement the NWS model forecast services • Why are we doing this? • Better forecasts. Just seeing if you’re paying attention. • How does it work? • By combining multiple (imperfect) forecasts of the (imperfectly observed) atmosphere, we can make a single ensemble forecast that is better than any of the forecasts that went into it.

  3. 3 Ensemble modeling • Did it work during the 2003 Demo? • Not as well as it can. It shows promise. It can be improved.

  4. 5 The ensemble for Demo 2003 • Three models, two LBC source models, total of six ensemble members • models: MM5, RAMS, WRF • LBC sources (from NCEP): AVN, Eta • 6-hour cycle • 27-hour forecasts • 12-km grid

  5. 6 Bulk statisticsState variables, 12-hr forecastsFeb 1 – Apr 8, 2003

  6. 7 Precipitation verification

  7. A closer look 9 pm model runs, verifying only Iowa stations, entire expt

  8. 8 Improving the ensemble • Remove unhelpful members • If we can’t fix RAMS problems, it’s gone • Different LBC models don’t seem to help (?????)

  9. Unhelpful members The LBC models don’t add enough diversity MM5+Avn MM5+Eta WRF+Avn WRF+Eta

  10. Improving the ensemble • Add good models • FSL/RUC a very good candidate for Demo 2004 • Change model configurations • WRF cloud/precip physics • Model cycle frequency, lead times, etc. • Optimize use of available computing resources • Take advantage of what regional models do best • Improve post-processing • Better PoP (probability of precip) estimates -- FSL • Better tuning procedures -- NCAR • Hope for “better” weather during tuning period

  11. Reliability 9 Planned power outage at FSL NCEP data problems Giant snowstorm in Boulder

  12. 10 Reliability • MM5 shows good reliability • Others will improve with better scripting

  13. Photos from MDSS field trip Downward-pointed radiometer mounted on rear-view mirror of Jim Van Sickle’s truck RWIS tower, I-35 south of Ames Bob Stradley and Ron Simmons

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