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An Intercomparison of Surface Observations and High-Resolution Forecasting Model Output for the Lake Okeechobee Region By Kathryn Shontz July 19, 2006.

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Presentation on theme: "An Intercomparison of Surface Observations and High-Resolution Forecasting Model Output for the Lake Okeechobee Region By Kathryn Shontz July 19, 2006."— Presentation transcript:

1 An Intercomparison of Surface Observations and High-Resolution Forecasting Model Output for the Lake Okeechobee Region By Kathryn Shontz July 19, 2006 Department of Marine and Environmental Systems Florida Institute of Technology 150 W. University Blvd. Melbourne, Florida 32901

2 Introduction Purpose Idealized model of a Lake Breeze Observational and Analytical Methods Lake Breeze on June 8, 2006: Graphical and Satellite Data What is the Weather Research and Forecasting Model? Model Output: Image and Graphical Data Comparison between Observed and Model Data Conclusions Future Considerations

3 Purpose Gauge Weather Research and Forecasting (WRF) model representation of the lake breeze phenomenon with respect to Lake Okeechobee Evaluate the model performance in terms of forecasting capabilities

4 Idealized Lake Breeze Meso-gamma scale turbulent vertical flow (2-20 km) Occurs in afternoon due to solar heating and flows inland less than characteristic width of lake (Segal, 1997) Known to extend vertically for several hundred meters (Segal, 1997) Most events occur in the month of lowest average wind speed and maximum solar heating (Laird, 2001)

5 + easterly large scale (synoptic flow) Synoptic scale influence on the lake breeze evolution ~150

6 Methods and Observations Weather Station Data: K4JHI Only Okeechobee Station Sensible Weather Elements WRF Model Output Data Processing Grads Output and Images K4JHI Lake Okeechobee Mesowest Achieve, 2006 Palmdale

7 Results Sunrise Lake Breeze

8 Results Continued

9 Satellite Imagery Lake Okeechobee Sea Breeze Front Lake Breeze Front

10 What is the Weather Research and Forecasting (WRF) Model? Most current regional forecast model Numerical weather prediction in 4-dimensional space Spatial resolution from meters to tens of kilometers Prognostic dynamical model that incorporates actual data with physical parameterizations (e.g., radiation, boundary layer, cloud physics). T, p, u, v, w,q WRF Configuation Domain size Hz Resolution (4 km), Vertical Resolution? Initial/Boundary Conditions (NAM)

11 950 Model Winds at 5:00 PM WRF Model Run of June 8, 2006: 5 am - 8 pm 5:00 AM8:00 AM11:00 AM2:00 PM5:00 PM8:00 PM

12 Time Series Data from WRF Output N E S W

13 Comparison of Observations and Model Data sunrise/mixing

14 Conclusions Possible lake breeze boundary observed in temperature, winds, and dew point at station K4JHI Temperature, dew point and relative humidity are not handled well by the WRF model (especially the diurnal temperature cycle) 4-km resolution model is too inaccurate to use instead of weather observations Possible problems/issues Sparse observations Rounding of data Observed lake temperature ~ 29 C, model ? Temporal model output insufficient Timing/distribution of convection model parameterizations (land surface, radiation, skin temperature, soil moisture) Synoptic scale flow appears to be different than observed

15 Future Considerations Repeated trials especially during other pressure regimes 1-km resolution or smaller output Enhanced monitoring equipment on all lake shores

16 References Laird, N.F. et al. “Lake Michigan Lake Breezes: Climatology, Local Forcing, and Synoptic Environment.” Journal of Applied Meteorology: Vol. 40, no. 3, pp Segal, M. et al. “Small Lake Daytime Breezes: Some Observational and Conceptual Evaluations.” Bulletin of the American Meteorological Society: Vol. 78, no. 6, pp June Weather Station History: K4JHI in Okeechobee City, FL. Taken from Mesowest database. Questions? Christopher Flanary, Natalie Lamberton, Kelli Zargiel

17 Vertical Wind Profile: Surface to 1.5 km at 5:00 PM 1000 mb950 mb900 mb850 mb


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