Mesoscale Numerical Weather Prediction With the WRF Model Ying-Hwa Kuo, Joseph Klemp, and John Michalakes Mesoscale and Microscale Meteorology Division.

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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.

Evolution of Numerical Models NCEP Operational Regional ModelPenn State/NCAR Mesoscale Model YearModelResolutionYearModel 1955Princeton QG381 km /3 levels19693-D Hurricane / 30 km 1966Primitive Equation381 km /6 levels1971Began MM0 – MM3 devel 1971 Limited Area Fine Mesh (LFM) km / 7 levels1981Began MM4 development 1985 Triply Nested Grid (NGM) 80 km / 16 levels1987MM4 released to community 1993ETA80 km / 38 levels1990First R-T MM4 fcst (30 km) 1995Meso-Eta29 km / 50 levels1994MM5 (non-hydro) released 1996 Nested Eta (experimental) 10 km / 60 levels1997MM5 adjoint system 1998ETA32 km / 45 levels1998ATEC 1.1 km real-time 2000ETA22 km / 50 levels 2001ETA12 km / 60 levels2001Danny simulation – 1 km 2002Non-hydrostatic (experimental) 8 km / 60 levels2002Columbia Gorge simulation at 440 m (U. of Washington)

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

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

36h WRF Precip Forecast Analyzed Precip 27 Sept Goals: Develop an advanced mesoscale forecast and assimilation system, and accelerate research advances into operations Collaborative partnership, principally among NCAR, 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 Weather Research and Forecasting Model

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. WRF Model Characteristics

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 WRF Software Design Mediation Layer Driver Layer Model Layer 27km WRF Model Ocean SST Wave Height Mobile Bay

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

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?

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?

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 10 km WRF forecast domain 4 km WRF forecast domain Field program conducted 20 May – 6 July 2003

Real-time WRF 4 km BAMEX Forecast Composite NEXRAD RadarReflectivity forecast Initialized 00 UTC 9 June 03

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

Real-time WRF 4 km BAMEX Forecast Initialized 00 UTC 10 June 03 Reflectivity forecastComposite NEXRAD Radar

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

Realtime WRF 4 km BAMEX Forecast Composite NEXRAD Radar30 h Reflectivity Forecast Squall line 7” hail 00Z Valid 6/23/03 06Z

Real-time WRF 4 km BAMEX Forecast Initialized 00 UTC 12 June 03 Reflectivity forecastComposite NEXRAD Radar

Realtime WRF 4 km BAMEX Forecast Composite NEXRAD Radar30 h Reflectivity Forecast Missed Valid 6/12/03 06Z

Criteria: Within 400 km and 3 h Probability of Detection False Alarm Corresponding mesoscale convective systems 58%29% For squall line or quasi-linear convection 79%29% Most organized mode for each forecast period 80%7% Skill of Storm-scale prediction From Done, Davis and Weisman (2003)

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

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

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

Preliminary BAMEX Forecast Verification Equitable Threat Scores

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

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 Challenge:

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

Real-data Nested-Grid Simulation

Auto-Generated On-line Documentation 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

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

For details please refer to Upcoming events –WRF workshop: June 2004 –WRF Tutorial: 28 June – 2 July 2004

Thank you!