1. Grid Point Models
Surface Data

2. Models: Types Spectral Models (AVN) Data is not represented on grid
Data represented by wave functions
Resolution is a function of # waves used in model
Computational errors generally less
Not well-suited for mesoscale modeling

3. Models: Types Hydrostatic Models (ETA, AVN, NGM)
Cannot produce vertical accelerations
Vertical motions determined by the continuity equation
Non-Hydrostatic Models (Some MM5)
Can produce vertical accelerations
Calculate Vertical Motions explicitly
Used in mesoscale applications (conv)

4. Models: The Basics Domain: Area covered by the model
IDD grids
Regional vs. Global
Nested models

5. Models: The Basics Resolution: Distance between grid points
High and low resolution models

6. Models: Resolution

7. Model Resolution
Should have 5 to 7 grid points to resolve feature

8. Model Resolution
Should have 5 to 7 grid points to resolve feature

9. Models: The Basics What can’t models simulate? How’s a model to cope?
Processes neglected in simplified equations
Processes unknown
Processes that are sub-grid scale
How’s a model to cope?

10. Models: The Basics Parameterizations
Model’s attempt to ““simulate”” (incorporate) important sub-grid scale processes
Examples:
Convection
Microphysical processes of precipitation
Surface/Boundary layer fluxes

11. Model Parameterizations: CONVECTION

12. Model Parameterizations: CONVECTION

13. Model Parameterizations: CONVECTION

14. Model Parameterizations: CONVECTION

15. Why are model forecasts imperfect?
Imperfect Initial Conditions
Too few observations
“Continuous atmosphere = Non-continuous sampling”
some areas worse than others
Bad observations
instrument error
Errors in the initialization procedure
First guess & objective analysis
“GI = GO”

16. Imperfect Models: Accurate Ob = Good ob?
Good Observation
Or Bad Observation?

17. Why are model forecasts imperfect?
Imperfect Models
Simplified equations
many “unimportant” terms = 0
Neglected Processes
that’s why we still have field projects!
Resolution
can’t simulate small scale stuff
‘good’ ob can be a bad ob

18. Trend of Numerical Models
Resolution increasing!
Run more frequently!
More models!
Computer power increasing
Cost decreasing

19. Trend of Numerical Models
Implications: Higher Resolution
Improved initialization
More small-scale effects will be predicted!
Will these small-scale phenomena be correct?
If terrain-forced weather phenomena = YES!
Density obs VS. density grid points
Heightened sensitivity to initial conditions

20. Higher Resolution: Improves Initialization
Good Observation
Or Bad Observation?
Higher Resolution
will help but not solve
the problem!

21. Model Resolution
Should have 5 to 7 grid points to resolve feature

22. Higher Resolution: Improves Terrain-forced weather!
Model Terrain vs. Actual Terrain

23. Model Terrain ETA 80km ETA 32km ETA 10km Actual terrain
ETA 32km
ETA 10km
Actual terrain

24. Orographic: Differential Heating

25. Orographic: Differential Heating

26. Density of OBS vs. Grid points
What if grid density (aka. model resolution) exceeds observation density?

27. Sensitivity to Initial Conditions