1. Model Resolution Prof. David Schultz University of Helsinki, Finnish Meteorological Institute, and University of Manchester

2. What Resolution Means to You n n Will affect the types of weather phenomena you can forecast using model guidance n n Will affect the conclusions you can draw from your research n n Will affect your choice of parameterizations or how you set up the model n n Will affect your computer resources and how fast the model runs

3. Goals for this Lecture n n Distinguish between resolution and grid spacing. n n What does resolution mean? n n Why you should care n n Why higher resolution is not necessarily better

4. Resolution is the ability of a NWP model to represent a feature adequately. Grid spacing is the distance between grid points (usually referring to the horizontal).

5. Resolution is the ability of a NWP model to represent a feature adequately. Grid spacing is the distance between grid points (usually referring to the horizontal). Resolution ≠ grid spacing!

6. Resolution does not equal grid spacing! Five grid points are needed to “resolve” the wave. How many points are needed to resolve a feature will depend upon the requirements of the user and the type of feature.

10. Mass et al. (2002)

11. (Baldwin and Wandishin 2002) Just because a model advertises a certain grid spacing does not mean that the model is actually “resolving” features of that scale. schematic

12. (Baldwin and Wandishin 2002) Just because a model advertises a certain grid spacing does not mean that the model is actually “resolving” features of that scale. Effective resolution 10 km Effective resolution 25 km schematic

13. (Skamarock 2004) real models

14. (Skamarock 2004) Effective resolution 22-km WRF Effective resolution 4-km WRF real models 20 km 110 km

15. Because the resolution of a model is ambiguous, use the term grid spacing instead. How do you select the grid spacing of a model?

16. No Man’s Land (Joe Klemp)

17. No Man’s Land (Joe Klemp)

18. What is meant by “resolved convection”? People now refer to “convection-permitting” or “convection-allowing” models, indicating that organized mesoscale convective storms can be simulated and resolved, but the individual convective cells are not fully resolved.

19. Although grid spacings of 1–4 km may produce realistic-looking mesoscale convective systems, the turbulent eddies of the convection are not resolved. (Axel Seifert)

20. (Bryan et al. 2003) across-line along-line equivalent potential temperature 3-D idealized squall line simulations 1 km 125 m

21. Richard Rotunno and Yongsheng Chen Hurricane Eyewall Simulations 10-m wind speed

22. Physical processes may not be adequately represented in the model because of large grid spacing. Example 1: Spurious convection ahead of squall lines

23. Spurious Convection Near Squall Lines 2-km WRF

24. George Bryan (2005, Monthly Weather Review) Spurious Convection Near Squall Lines A result of moist absolutely unstable layers (MAULs)

25. Physical processes that were unimportant at large grid spacing become important at small grid spacing. Example 2: Bias in location of orographic precipitation

26. Mass et al. (2002) Two years of model runs Over-prediction downwind of mountains: Improved riming parameterization (Colle, in preparation)

27. Verification of high-resolution output is problematic.

28. High-resolution models may produce wonderfully detailed, but inaccurate, forecasts.

29. Increasing resolution requires a new forecasting approach. (Sami Niemelä) 7.5-km HIRLAM2.5-km AROMEradar precipitation

30. Increasing resolution requires a new forecasting approach. (Sami Niemelä) 7.5-km HIRLAM2.5-km AROMEradar precipitation

31. Increasing resolution requires a new forecasting approach. (Sami Niemelä) 7.5-km HIRLAM2.5-km AROMEradar precipitation ?

32. 3 May 1999 Oklahoma Outbreak (Jarboe) n n 66 tornadoes, produced by 10 long-lived and violent supercell thunderstorms n n 45 fatalities, 645 injuries in Oklahoma n n ~2300 homes destroyed; 7400 damaged n n Over $1 billion in damage, the U.S.’s most expensive tornado outbreak (Daily Oklahoman) (Schultz)

33. 0131 UTC 0221 UTC 0200 UTC 0100 UTC Observed radar imagery (courtesy of Travis Smith, NSSL) 2-km MM5 simulation initialized 25 hours earlier (no data assimilation) pink: 1.5-km w (> 0.5 m/s) blue: 9-km cloud-ice mixing ratio (>0.1 g/kg) Moore Moore

34. Stage IV Radar/Gauge Precip. Analysis (Baldwin and Mitchell 1997) Moore Moore

35. Modeled Storms as Supercells n n Identify updrafts(> 5 m/s) correlated with vertically coherent relative vorticity for at least 60 minutes n n 22 supercells, 11 of which are on OK–TX border

36. Observed vs Modeled Supercells

37. Summary of Oklahoma Outbreak n n The high-resolution forecast did not put the precipitation in the right place in central Oklahoma. n n The model indicated the potential for supercell thunderstorms with tornadoes in the Oklahoma–Texas region.

38. Some Remaining Issues n n When should forecasters believe the model forecast as a literal forecast? n n What is the role of model formulation in predictability? n n What is the value of mesoscale data assimilation in the initial conditions? n n What constitutes an appropriate measure of mesoscale predictability? n n What is the appropriate role of postprocessing model data (e.g., neural networks, bias-correction techniques)? n n What tools can be developed to help forecasters view, use, and diagnose high-resolution model output?

39. For Further Reading n n Some practical considerations regarding horizontal resolution in the first generation of operational convection-allowing NWP – Kain et al. (2008) n n Toward improved prediction: High-resolution and ensemble modeling systems in operations – Roebber et al. (2004) n n Does increasing horizontal resolution produce more skillful forecasts? – Mass et al. (2002)