Mesoscale Numerical Weather Prediction With the WRF Model

1. Mesoscale Numerical Weather Prediction With the WRF Model Ying-Hwa Kuo, Joseph Klemp, and John Michalakes Mesoscale and Microscale Meteorology Division National Center for Atmospheric Research Boulder, Colorado, U.S.A.

2. Evolution of Numerical Models

3. 3-D Trajectories Anthes’ hurricane simulation 30 x 30 x 3 mesh at 30 km. First 3-D simulation with asymmetric hurricane structure. Slide from Anthes

4. Modeling Winds in the Columbia Gorge Portland Cascade Locks Troutdale • Strongest winds are at the exit

5. Weather Research and Forecasting Model Goals: Develop an advanced mesoscale forecast and assimilation system, and accelerate research advances into operations 36h WRF Precip Forecast • Collaborative partnership, principally amongNCAR, NOAA, • DoD, OU/CAPS, FAA, and university community • Governance through multi-agency oversight and • advisory boards • Development conducted by 15 WRF Working Groups • Ongoing active testing and rapidly growing community use • Over 1,600 registered community users, annual • workshops and tutorials for research community • Daily experimental real-time forecasting at NCAR , • NCEP, NSSL, FSL, AFWA, U. of Illinois • Operational implementation at NCEP and AFWA in 2004 Analyzed Precip 27 Sept. 2002

6. WRF Model Characteristics • Highly modular, single source code with plug-compatible modules • State-of-the-art, transportable, and efficient in a massively parallel • computing environment. • Design priority for high-resolution (nonhydrostatic) applications • Advanced data assimilation systems developed in tandem with the • model itself. • Numerous physics options, tapping into the experience of the full • modeling community. • Maintained and supported as a community mesoscale model to facilitate • broad use in the research community. • Research advances will have a direct path to operations. • With these hallmarks, the WRF model is unique in the • history of numerical weather prediction in the U.S.

7. Driver Layer Mediation Layer Model Layer 27km WRF Model WRF Parallel Scaling Mobile Bay 150 COMPAC 100 Gflop/s IBM Regatta 50 Intel IBM Winterhawk II 0 0 500 1000 Ocean SST Wave Height processors WRF Software Design • Modular, hierarchical design • Plug compatible physics, dynamical cores • Parallelism on distributed- and shared memory processors • Efficient scaling on foreseeable parallel platforms • Model coupling infrastructure • Integration into new Earth System Model Framework

8. WRF Version 1.3 12-km CONUS 500 times real time equivalent to 48 h forecast in 6 mins. No I/O or initialization WRF Performance Benchmarks

9. Key Scientific Questions for Storm-Scale NWP • What is the predictability of storm-scale events, and will resolution of fine-scale details enhance or reduce their prediction? • What observations are most critical, and can high-resolution data (e.g. WSR-88D) from national networks be used to initialize NWP models in real time? • What physics are required, and do we understand it well enough for practical application? • How can ensembles be utilized for storm-scale prediction? • What are the most useful verification techniques for storm and mesoscale forecasts? • What networking and computational infrastructures are needed to support high-resolution NWP? • How can useful decision making information be generated from forecast model output?

10. Convection-Resolving NWP using WRF Motivating Questions • Is there any increased skill in convection-resolving forecasts, measured objectively or subjectively? • Is there increased value in these forecasts? • If the forecasts are more valuable, are they worth the cost?

11. 10 km WRF forecast domain 4 km WRF forecast domain Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) Goal: Study the lifecycles of mesoscale convective vortices and bow echoes in and around the St. Louis MO area Field program conducted 20 May – 6 July 2003

12. Real-time WRF 4 km BAMEX Forecast Initialized 00 UTC 9 June 03 Reflectivity forecast Composite NEXRAD Radar

13. Real-time WRF 4 km BAMEX Forecast Valid 6/10/03 12Z 4 km BAMEX forecast 36 h Reflectivity 4 km BAMEX forecast 12 h Reflectivity Composite NEXRAD Radar

14. Real-time WRF 4 km BAMEX Forecast Initialized 00 UTC 10 June 03 Reflectivity forecast Composite NEXRAD Radar

15. Real-time 12 h WRF Reflectivity Forecast Valid 6/10/03 12Z 4 km BAMEX forecast 10 km BAMEX forecast 22 km CONUS forecast Composite NEXRAD Radar

16. Realtime WRF 4 km BAMEX Forecast Valid 6/23/03 06Z 30 h Reflectivity Forecast Composite NEXRAD Radar 7” hail 00Z Squall line

17. Real-time WRF 4 km BAMEX Forecast Initialized 00 UTC 12 June 03 Reflectivity forecast Composite NEXRAD Radar

18. Realtime WRF 4 km BAMEX Forecast Valid 6/12/03 06Z 30 h Reflectivity Forecast Composite NEXRAD Radar Missed

19. Skill of Storm-scale prediction From Done, Davis and Weisman (2003)

20. 10-km WRF 4-km WRF Parameterized convection (on the 10 km grid) cannot differentiate different mode of convection Dashed magenta indicates approximate area of rainfall Produced by convective parameterization

21. 30h WRF BAMEX Forecast Valid 6/10/03 06Z 4 km Surface Theta-E 10 km Surface Theta-E

22. 30h WRF BAMEX Forecast Valid 6/10/03 06Z 4 km 850 RH 10 km 850 RH

23. Preliminary BAMEX Forecast Verification Equitable Threat Scores

24. Preliminary Findings for BAMEX Forecasts • Rapid spinup of storm-scale structure from large-scale IC • Forecasts were helpful to field operations planning, particularly • on the number of systems, their mode and location • 4 km WRF replicates overall MCS structure and character better than 10 km WRF with cumulus parameterization • More detailed representation of convective mode • No improvement in precipitation threat scores • Skill in forecasting systems as high after 21 h as during the • first 6-12 h, suggesting mesoscale control of initiation • Convective trigger function wasn’t needed Convection resolving forecasts should be a useful tool for predicting significant convective outbreaks and severe weather

25. Challenge: • QPF problematic (too much convective precip) • Stratiform regions appear too small (microphysics?) • Convective systems often fail to decay (BL evolution?) • Lack of convection on high terrain (domain boundary issue?) • Initialization (data assimilation) • Verification methods

26. WRF Version 2.0 Features • 1-way and 2-way nesting (Multiple domains, flexible ratio) • New physics • Land-surface models (Unified Noah LSM, RUC LSM) • PBL physics (Yonsei Univ PBL) • Microphysics (Hong et al., 3 and 5 classes schemes) • Cumulus (Grell-Devenyi ensemble) • Updated NCEP physics (inc. Betts-Miller-Janjic CPS, • Mellor-Yamada-Janjic PBL, Ferrier microphysics, and • GFDL radiation) • ESMF time-keeping, PHDF5 I/O, and more I/O options • Capability to run WRF initialization program for large domains • Updated Standard Initialization program (nest capability) • Coordinated with WRF 3DVAR release • Optional WRF initialization from MM5 preprocessor (by July) • More complete documentation (users guide & tech note) • V 2.0 release scheduled for June 2004

27. Auto-Generated On-line Documentation http://www.mmm.ucar.edu/wrf/WG2/software_2.0 • Generated directly from WRF source code • Collapsible/expandable call tree browser • Man-page-style hypertext documentation from in-line code commentary • Clicking a subroutine argument displays trace of variable up call tree to point of definition

28. WRF and ESMF • WRF is a participating application in ESMF • WRF 2.0 includes ESMF Time Manager • Exact, drift-free time arithmetic, even for fractions of seconds • Time objects in WRF are now compatible with representation in other ESMF-compatible components • Merging of WRF and ESMF I/O specifications in progress • Top level of WRF easily conforms to ESMF component interface for model coupling

29. For details please refer to http://www.wrf-model.org/ • Upcoming events • WRF workshop: 22-25 June 2004 • WRF Tutorial: 28 June – 2 July 2004

30. Thank you!