# Presentation: 278842

## 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 Model |  |  | Penn State/NCAR Mesoscale Model |  |
| --- | --- | --- | --- | --- |
| Year | Model | Resolution | Year | Model |
| 1955 | Princeton QG | 381 km /3 levels | 1969 | 3-D Hurricane / 30 km |
| 1966 | Primitive Equation | 381 km /6 levels | 1971 | Began MM0 – MM3 devel |
| 1971 | Limited Area Fine Mesh (LFM) | 190.5 km / 7 levels | 1981 | Began MM4 development |
| 1985 | Triply Nested Grid (NGM) | 80 km / 16 levels | 1987 | MM4 released to community |
| 1993 | ETA | 80 km / 38 levels | 1990 | First R-T MM4 fcst (30 km) |
| 1995 | Meso-Eta | 29 km / 50 levels | 1994 | MM5 (non-hydro) released |
| 1996 | Nested Eta (experimental) | 10 km / 60 levels | 1997 | MM5 adjoint system |
| 1998 | ETA | 32 km / 45 levels | 1998 | ATEC 1.1 km real-time |
| 2000 | ETA | 22 km / 50 levels |  |  |
| 2001 | ETA | 12 km / 60 levels | 2001 | Danny simulation – 1 km  |
| 2002 | Non-hydrostatic (experimental) | 8 km / 60 levels | 2002
 | Columbia 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

**Modeling Winds in the Columbia Gorge**

- Strongest winds are at the _**exit**_

**Portland**

**Troutdale**

- Cascade Locks

## Weather Research and Forecasting Model

**36h WRF Precip Forecast**

**Analyzed Precip**

**27 Sept. 2002**

***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

## 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.

## 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 

**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

## WRF Performance Benchmarks

**WRF Performance Benchmarks**

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

**Notes:**
Additional information:

Platforms listed: 
	Cray X1
		Vector MPP system (each processor is about 3 Gf/s peak)
		Results provided by vendor
		Peculiar bump at 300 processors corresponds to the number of processors exactly dividing the number of latitudes
	SGI Altix
		This is a Linux/Intel IA64 platform, using SGI’s proprietary interconnection network
		Intel compilers
		Results provided by vendor
	HP system at PNNL
		This is also a Linux/Intel IA64 platform, Quadrics interconnection network
		Intel compilers
		Results obtained by Michalakes
	HP (Compaq) system at Pittsburgh
		Tru64/Alpha EV68, Quadrics interconnection network
		HP/Compaq compilers
		Results obtained by Michalakes
	IBM p690 (bluesky.ucar.edu)
		AIX/Power4, IBM Colony interconnection network
		IBM XLF compilers
		Results obtained by Michalakes
	iJet  (ijet.fsl.noaa.gov)
		Linux/Pentium 4, Myrinet interconnect network
		Portland Group compiler
		Results provided by Craig Tierney at FSL
	IBM Winterhawk II (old NCAR system, blackforest.ucar.edu)
		AIX/Power3
		IBM XLF compilers
		Results obtained by Michalakes

## 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*

- Field program conducted 20 May – 6 July 2003

## Real-time WRF 4 km BAMEX Forecast

**Composite NEXRAD Radar**

**Reflectivity 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

**Notes:**
It appears that for this case, the shorter range (12h) forecast produced a system that moves at a slower speed than observation (and the earlier forecast).

If I understand it right, all the BAMEX forecast was made at 000 UTC (1800 LST)? The forecast is available for weather briefing (and decision making) the next morning.

Is there any other points worth making?

## Real-time WRF 4 km BAMEX Forecast

- Initialized 00 UTC 10 June 03

**Reflectivity forecast **

**Composite NEXRAD Radar**

**Notes:**
The point for this case is that WRF not only predict the evolution of the first system, but also captured quite well the evolution of the second system. Any other points?

## 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 Radar**

**30 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 forecast **

**Composite NEXRAD Radar**

## Realtime WRF 4 km BAMEX Forecast

**Composite NEXRAD Radar**

**30 h Reflectivity Forecast**

**Missed**

- Valid 6/12/03 06Z

## Skill of Storm-scale prediction

| 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% |

- 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

**Notes:**
What is the purpose of this slide?

- 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

- 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

**Notes:**
ESMF time keeping is a standard time tracking based on Earth System Modeling Framework (www.esmf.ucar.edu)

## 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

- http://www.mmm.ucar.edu/wrf/WG2/software_2.0

## 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
	http://www.wrf-model.org/

Upcoming events
WRF workshop: 22-25 June 2004
WRF Tutorial: 28 June – 2 July 2004

- 	_[http://www.wrf-model.org/](http://www.wrf-model.org/)_
- Upcoming events
- WRF workshop: 22-25 June 2004
- WRF Tutorial: 28 June – 2 July 2004

## Thank you!