1. Update on the Regional Modeling System Cliff Mass, David Ovens, Richard Steed, Mark Albright, Phil Regulski, Jeff Baars, Eric Grimit

2. Supported by the Northwest Modeling Consortium…the regional modeling effort centered at the UW is Running the MM5 at 36, 12, and 4 km resolution Running the new WRF model at 36, 12 km resolution Running a high resolution regional ensemble system to provide probabilistic forecasts Gathering all local weather observations from dozens of networks. Plus quality control. Running a wide range of weather applications dealing with air quality, hydrology, transportation weather and fire weather.

4. 36 km

5. 12 km

6. 4 km

7. A Few of the Major Additions and Changes this Year

8. Addition of WRF WRF: the Weather Research and Forecasting Model, is the replacement for the MM5 and should be the national mesoscale model used by both the operational and research community. We are now running it at 36 and 12 km grid spacing, and will be replacing our current system with an updated one in late March.

9. Evaluation We will evaluate WRF this year and may switch all regional modeling to WRF at the end of the year.

12. Extended MM5 to 7.5 days at 36 and 12 km grid spacing

13. Explanations of Model Graphics

16. Substantial Graphics Additions New color scheme for surface to better delineate freezing temps. More and better snow graphics Local wind speed graphics New options…dmodel and dprog/dt Many more

20. Map Selection Interface We have a new map interface for getting soundings at ANY location. Will put online in about a week. Will be adding surface meteograms and time-height cross sections soon.

23. Map Selection Check it out at: http://www.atmos.washington.edu/~regulski/sound_gen2/sounding_mai n.cgi

24. The Northwest Ensemble System

25. The Northwest Mesoscale Ensemble System 17 members using both initialization and physics uncertainty Extended to 72 h (from 48 h) Grid acquisition is much more robust Web page improved and new products

27. The Next Step in Probabilistic Forecasts We are now post-processing the ensemble forecasts to use them in a more optimal way. Using Bayesian Model Averaging we weight each of the ensemble members by their quality. Produces far better probabilistic forecasts Two main web pages to view it.

30. PROBCAST Check it out at www.probcast.comwww.probcast.com

31. 46 networks! 4100 observing sites! 250,000 observations a day! Addition of More Observations to the Northwest Real-time Database

32. Many more things I could have mentioned Improved computer infrastructure, making our systems and web pages more reliable Improved road weather applications and web pages Grid-based bias removal …

33. The END