1. Discussion 4/17 Small-scale winds Forecasting & Models

2. Small scale winds Land & sea breezes – Lake breeze Mountain & valley breezes – Katabatic wind / Boulder windstorm Downdraft/Heatburst Chinook (“snow eater”) The Santa Ana Winds Derecho – Bow echo

8. Fig. 12-9, p. 360 Number of derecho storms occurring from 1994 to 2003

9. WEATHER FORECASTING FOLKLORE PERSISTENCE – The weather tomorrow will be the same as the weather today (two times out of three) CLIMATOLOGY – This takes persistence one step further – The average weather say for a particular month is the same each year MODELING

10. TREND AND ANALOG We know that persistence forecasts will eventually be wrong because weather does change. A trend forecast assumes that the weather-causing patterns are themselves unchanging in speed, size, intensity, and direction of movement (this is called steady-state). – For instance: we know that an approaching cyclone will bring rain (weather does change) but assume that the amount of rain or its speed will not change along the path the cyclone will travel. The analog forecast also acknowledges that weather changes, but unlike the trend method, it assumes that weather patterns can evolve with time. – The main assumption is that weather repeats itself. – Therefore, this method “searches” for past weather patterns that are similar (analog) to the current situation. – In this sense, the future weather patterns “should” be similar to those that happened in the past.

11. NUMERICAL WEATHER PREDICTION Step One: Weather Observations Step Two: Data Assimilation Step Three: Forecast Model Integration Step Four: Tweaking and Broadcasting

12. Data Assimilation

13. Fig. 13.9

14. Numerical Weather Prediction Models North America Model (NAM) Global Forecast System (GFS) Computational power / nested grids Errors Ensemble forecasts