Transcript NCAR Mesoscale and Microscale Meteorology Division

Weather Research and Forecast (WRF) Model
 Develop an advanced mesoscale forecast and assimilation system
 Promote closer ties between research and operations
Research:
Design for 1-10 km horizontal grids
Advanced data assimilation and model physics
Accurate and efficient across a broad range of scales
Well-suited for both research and operations
Community model support
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WRF Project Collaborators
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Original Partners:
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Additional Collaborators:
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NCAR Mesoscale and Microscale Meteorology Division
NOAA National Centers for Environmental Prediction
NOAA Forecast Systems Laboratory
OU Center for the Analysis and Prediction of Storms
Air Force Weather Agency
NOAA Geophysical Fluid Dynamics Laboratory
NASA GSFC Atmospheric Sciences Division
NOAA National Severe Storms Laboratory
NRL Marine Meteorology Division
EPA Atmospheric Modeling Division
University Community
WRF Project Management
Steve Lord, Chair NOAA/NCEP
Sandy MacDonald FSL &GFDL
Bob Gall
NCAR/MMM
Steve Nelson
NSF/ATM
Col. Charles French USAF/AFWA
WRF Oversight
Board
Joe Klemp NCAR/MMM
WRF
Coordinator
WRF Science
Board
WRF Development
Teams (5)
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WRF Development Teams
Working Groups
Numerics and
Software
(J. Klemp)
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Dynamic Model
Numerics
(W. Skamarock)
Data
Assimilation
(T. Schlatter)
Standard
Initialization
(J. McGinley)
Analysis and
Validation
(K. Droegemeier)
Analysis and
Visualization
(L. Wicker)
3-D Var
(J. Purser)
Software
Architecture,
Standards, and
Implementation
(J. Michalakes)
4-D Var,
Ensemble
Techniques
(D. Barker)
Model Testing
and Verification
(C. Davis)
Community
Involvement
(W. Kuo)
Operational
Implementation
(G. DiMego)
Model Physics
(J. Brown)
Data Handling
and Archive
(G. DiMego)
Atmospheric
Chemistry
(P. Hess)
NCEP
Requirements
(G. DiMego)
Workshops,
Distribution,
and Support
(J. Dudhia)
AFWA
Requirements
(M. Farrar)
WRF Software Objectives
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Performance-Portable
– Performance: scaling and time to solution
– Architecture independence
– No specification of external packages
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Run-Time Configurable
– Scenarios, domain sizes, nest configurations
– Dynamical-core and physics
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Maintainability & Extensibility
– Single source code
– Modular, hierarchical design, coding standards
– Plug compatible physics, dynamical cores
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WRF Multi-Layer Domain Decomposition
Logical
domain
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1 Patch, divided
into multiple tiles
Single version of code enabled for
efficient execution on:
– Distributed-memory multiprocessors
– Shared-memory multiprocessors
– Distributed memory clusters of
SMPs
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Model domains are decomposed for parallelism on two-levels
– Patch: section of model domain allocated to a distributed
memory node
Inter-processor
communication
– Tile: section of a patch allocated to a shared-memory processor within a node
– Distributed memory parallelism is over patches; shared memory parallelism is
over tiles within patches
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WRF Hierarchical Software Architecture
Top-level “Driver” layer
– Isolates computer architecture concerns
– Manages execution over multiple nested domains
– Provides top level control over parallelism
» patch-decomposition
Driver Layer
» inter-processor communication
» shared-memory parallelism
– Controls Input/Output
initial_config
Mediation Layer
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Model Layer
filter
physics
decouple
Performs actual model computations
Tile-callable
Scientists insulated from parallelism
General, fully reusable
advance uv
solve
Low-Level “Model” layer
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integrate
solve_interface
– Specific calls to parallel mechanisms
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init_domain
scalars
“Mediation” Layer
alloc_and_configure
recouple
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wrf
advance w
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Parallel Scaling on Compaq Computer
Compaq ES40, 41x81x81
35
30
25
1 (2d)
2 (2d)
4 (2d)
1 (1d)
2 (1d)
4 (1d)
ideal
speedup
20
15
10
5
0
0
5
10
15
20
processors
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25
30
35
Penalty for IJK Loop Order
Alpha workstation (EV56)
VPP 5000
100
30
80
25
60
40
20
20
15
0
10
-20
-40
5
81
81
-60
41
0
21
21
41
X tile dimension
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81
Y tile
dimension
41
-80
21
21
41
X tile dimension
81
IJK versus KIJ for all patch dimensions X,Y=(21,41,81); 41 levels throughout
Penalty for IJK decreases with increased length of minor dimension, X
Penalty is most severe for sizes typical of a DM patch
IJK is strongly favored by vector for adequate length of X
Surprise: vector prefers KIJ for short X; but an unlikely result once full physics
Y tile
dimension
Numerics for Dynamical Solver
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Numerical Modeling Issues:
– Equations / variables
– Vertical coordinate
– Terrain representation
– Grid staggering
– Time Integration scheme
– Advection scheme
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Strategy
– Identify and analyze alternative procedures
– Evaluate alternates in idealized simulations
– Evaluate in NWP applications as model complexity increases
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Treatment of Terrain by Vertical Coordinate
Terrain Following
 Smooth topography well represented
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Selective resolution enhancement near ground
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Potential for spurious circulations above steep terrain
Step Mountain
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Can represent blocking due to step terrain
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Reduced errors in computing horizontal gradients
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Degraded representation of sloped topography
Shaved Cell
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Maintains horizontal coordinate surfaces
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Represents terrain slope accurately
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Potential complications in numerics for shaved cells
Mountain Wave with Step Terrain Coordinate
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Mountain Wave with Step Terrain Coordinate
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Prototype Nonhydrostatic Model Solvers
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Split-Explicit Eulerian Model:
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Pressure and temperature diagnosed from thermodynamics
Two time level split-explicit time integration
Flux-form prognostic equations in terms of conserved variables
Accurate shape preserving advection
Both terrain-following height and mass coordinates being tested
Semi-Implicit Semi-Lagrangian Model:
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Unstaggered (A) grid
Forward trajectories with cascade interpolation back to grid
High order compact differencing
Terrain following hybrid coordinate
Flux-Form Equations in Height Coordinates
Conservative variables:
Inviscid, 2-D
equations in
Cartesian
coordinates
U   u, V   v, W   w,   
U

Uu
Wu
  R
 fV  

t
x
x
z
W

Uw
Ww
  R
 g  

t
z
x
z

U
W


Q
t
x
z

U
W


 0
t
x
z
Pressure terms
directly related to  :
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 R   c p   p
Flux-Form Equations in Mass Coordinates
Hydrostatic pressure coordinate:
Conservative variables:
Inviscid, 2-D
equations
without rotation:
   s t
U   u, W   w,    ,   
U
 p p 
Uu
u
 

 

t
 x  x
x


W
p 
Uw
w
  
 g   

t
 
x



U
 


 Q
t
x


U

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 0
t
x

d
 gw,
dt
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     t  / ,

   ,

 R 

p  
 p0 

2-D Mountain Wave Simulation
a = 1 km, dx = 200 m
a = 100 km, dx = 20 km
Height Coordinate
Mass Coordinate
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Comparison of Gravity Current Simulations
Height
Coordinate
5 min
Mass
Coordinate
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10 min
15 min
Comparison of Height and Mass Coordinates
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Time-Split Leapfrog and Runge-Kutta Integration Schemes
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Strategy for WRF Model Physics
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Define “plug-compatible” interface for physics modules
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Implement and test basic physics in WRF:
– Kessler-type (no-ice) microphysics
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Lin et al. (graupel included) microphysics
Kain-Fritsch cumulus parameterization
Shortwave radiation (cloud-interactive) from MM5
Longwave radiation (RRTM)
– MRF (Hong and Pan) PBL
– Blackadar surface slab ground temperature prediction
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Implement a complete suite of research physics packages
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Encourage and facilitate community involvement in
advanced model physics development and evaluation
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WRF 3D-Var Data-Assimilation System
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Essential features of initial 3D-Var system:
– Basic quality control
– Assimilation of conventional observations (surface, radiosonde, aircraft)
– Multivariate analysis
– Adherence to WRF coding standards
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Additional features to be added:
– 3-D anisotropic background errors using recursive filters
– Additional observation operators (radar, satellite, wind profiler, etc.)
– Flexible choice of first guess
– Further enhancements
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WRF Model Testing and Verification Strategy
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Analytic and converged numerical solutions
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Inviscid dynamics (baroclinic instability, frontogenesis)
Buoyancy driven flow (gravity currents, warm thermals)
Topographic flow (nonhydrostatic, hydrostatic, inertial-gravity mountain waves)
Moist convection (idealized convection with constant eddy mixing)
Regime dependence of nonlinear flows
– Topographic flow (finite amplitude waves, wave overturning, lee vortices)
– Moist convection (convective behavior as a function of CAPE and shear)
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Observational case studies
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Extratropical cyclones (STORM-FEST case)
Topographic flow (downslope windstorm, orographic precip., cold-air damming)
Moist convection (supercell case, squall-line case, multi-parameter radar case)
PBL-surface physics (1-D diurnal cycle, sea-breeze case, marine inversion and CTD)
Tropical cyclone (COMPARE case)
Projected Timeline for WRF Project
Development Task
2000
2001
2002
2003
2004
Basic WRF model (limited
physics, standard initialization)
Research quality NWP version
of WRF
Model physics
3D-Var assimilation system
Simple
Research suite
Basic
4D-Var assimilation system,
ensemble techniques
Research
Advanced
Advanced
Basic
Testing for operational use at
NCEP, FSL, & AFWA
Diagnosis of operational
performance, refinements
Release and support to community
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Operational deployment
Advanced
2005-08
WRF Calendar for 2000
12 January
First WRF Oversight Board Meeting
14 February
WRF Planning Meeting
29-30 March
WRF Planning Workshop
23 June
30 September
First Annual WRF Users Workshop
Release of “bare-bones” WRF Model
WRF Status & Updates: wrf-model.org
7/17/2015