2. Revolutions in Remote Sensing Greatly Enhanced Weather Prediction from the 1950s Through Today

3. Satellite and Weather Radars Give Us a More Comprehensive View of the Atmosphere

4. Before Satellites We Had a VERY Poor Knowledge of What Was Happening Over the Oceans! As a result, forecasts were often very poor, particularly in coastal locations. The 1938 Hurricane was basically unforecast

5. Weather Satellites Give Us Much More than Pretty Pictures We start with imagery in several wavelengths: – Visible – Infrared – Water vapor (wavelengths where we see the water vapor distribution) Plus many new capabilities

6. Better than Star Trek!

7. Water Vapor Imagery Looks at wavelengths where water vapor absorbs and emits infrared radiation

8. Each wavelength gives us information

9. Cloud and Water Vapor Track Winds Based on Geostationary Weather Satellites

11. GOES sounder unit

12. Satellite Temperature and Humidity Soundings

13. QuickScat Satellite Bounces microwaves off the ocean surface Capillary waves dependent on wind speed and directon

15. Weather Radar Has Revolutionized Local Forecasting

16. Weather Radar

17. Camano Island Weather Radar

18. Radar was first used operationally in WWII by the British to track German planes But they found some interference by heavy precipitation!

19. After WWII Meteorologists Experimented with Military Radars

20. Hurricane Radar Image

21. In the late 1950’s a meteorological radar network was established.

22. In the late 1980s, the NWS put in a network of Doppler Weather Radars NEXRAD WSR88D

23. Sound of train passing: http://www.fourmilab.ch/cship/sounds/doppler.au

25. NowWith Two New Radars

26. But even with all this improving technology, some forecasts fail. Why?

27. Weather Radars Lets us track thunderstorms and hurricanes Can see where it is precipitating and where it is moving. Many other uses.

28. Problems with the Models Some forecasts fail due to inadequacies in model physics…. How the model handles precipitation, friction, and other processes. Example: too much precipitation on mountain slopes

29. Some forecasts fail due to poor initialization, i.e., a poor starting description of the atmosphere. This is particularly a problem for the Pacific Northwest, because we are downstream of a relatively data poor region…the Pacific Ocean.

30. Pacific Analysis At 4 PM 18 November 2003 Bad Observation

31. Eta 48 hr SLP Forecast valid 00 UTC 3 March 1999 3 March 1999: Forecast a snowstorm … got a windstorm instead

32. The problem of initialization should lessen as new observation technologies come on line and mature. New ways of using or assimilating weather data are also being developed.

33. A More Fundamental Problem In a real sense, the way we have been forecasting has been essentially flawed. The atmosphere is a chaotic system, in which small differences in the initialization…well within observational error… can have large impacts on the forecasts, particularly for longer forecasts. Not unlike a pinball game….

34. A More Fundamental Problem Similarly, uncertainty in our model physics also produces uncertainty in the forecasts. Thus, all forecasts have some uncertainty.

35. This is Ridiculous!

36. Or this…

37. Forecast Probabilistically We should be using probabilities for all our forecasts or at least providing the range of possibilities. There is an approach to handling this issue that is being explored by the forecasting community…ensemble forecasts

38. Ensemble Prediction Instead of making one forecast…make many…each with a slightly different initialization Possible to do now with the vastly greater computation resources that are available.

39. The Thanksgiving Forecast 2001 42h forecast (valid Thu 10AM) 13: avn* 11: ngps* 12: cmcg* 10: tcwb* 9: ukmo* 8: eta* Verification 1: cent 7: avn 5: ngps 6: cmcg 4: tcwb 3: ukmo 2: eta - Reveals high uncertainty in storm track and intensity - Indicates low probability of Puget Sound wind event SLP and winds

40. Ensemble Prediction Can use ensembles to give the probabilities that some weather feature will occur. Can also predict forecast skill! It appears that when forecasts are similar, forecast skill is higher. When forecasts differ greatly, forecast skill is less.

41. Probabilistic Prediction So instead of saying the temperature in two days will be 67F. We might tell you: 50% probability it will be between 64 and 69F 90% probability it will be between 62 and 72F.

43. ENSEMBLE SYSTEMS http://www.atmos.washington.edu/~ens/uwme.cgi http://www.esrl.noaa.gov/psd/map/images/ens/ens.html#us

44. The Future As computer get faster and faster and our understanding of atmospheric processes improve, there will be a transition to higher resolution, more specific, forecasts and more probabilistic information. Too much information for TV…so the web and other online media will dominate.

45. The Limit Forecast skill will be pushed out in time— more skill at longer projections. But there are theoretical limits and we will probably never be able to forecast specific weather features out past about 2 weeks. But we do have some skill out months for average conditions.