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Higher Resolution Operational Models
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Higher Resolution Operational Models

Feb 24, 2016

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Higher Resolution Operational Models. Operational Mesoscale Model History. Early: LFM, NGM (history) Eta (mainly history) MM5: Still used by some, but phasing out NMM- Main NWS mesoscale model. Sometimes called WRF-NMM WRF-ARW: Heavily used by research and some operational communities. - PowerPoint PPT Presentation
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Page 1: Higher Resolution Operational Models

Higher Resolution Operational Models

Page 2: Higher Resolution Operational Models

Operational Mesoscale Model History

• Early: LFM, NGM (history)• Eta (mainly history)• MM5: Still used by some, but phasing out• NMM- Main NWS mesoscale model. Sometimes

called WRF-NMM• WRF-ARW: Heavily used by research and some

operational communities.• The NWS calls their mesoscale run NAM: North

American Mesoscale . Now NMM

Page 3: Higher Resolution Operational Models

Eta Model

Page 4: Higher Resolution Operational Models

Eta CoordinateAnd Step Mountains

MSL

ground

= 1

Ptop = 0

Page 5: Higher Resolution Operational Models
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Horizontal resolution of 12 km

12-km terrain

Page 7: Higher Resolution Operational Models

Drawbacks of the Eta Coordinate

• The failure to generate downslope wind storms in regions of complex terrain

• Weak boundary layer winds over elevated terrain when compared to observations

• The displacement of precipitation maxima too far toward the bottom of steeply sloping terrain as opposed to the observed location near the top half of the terrain slope

• The reduction in the number of vertical layers used to define the model atmosphere above elevated topography particularly within the boundary layer

Page 8: Higher Resolution Operational Models
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WRF and NMM

Page 10: Higher Resolution Operational Models

Why WRF?• An attempt to create a national mesoscale prediction system

to be used by both operational and research communities.• A new, state-of-the-art model that has good conservation

characteristics (e.g., conservation of mass) and good numerics (so not too much numerical diffusion)

• A model that could parallelize well on many processors and easy to modify.

• Plug-compatible physics to foster improvements in model physics.

• Designed for grid spacings of 1-10 km

Page 11: Higher Resolution Operational Models

WRF Modeling System

Obs Data,Analyses

Post Processors,Verification

WRF Software Infrastructure

Dynamic Cores

Mass Core

NMM Core…

Standard Physics Interface

Physics Packages

StaticInitialization

3DVAR DataAssimilation

Page 12: Higher Resolution Operational Models

Two WRF Cores• ARW (Advanced Research WRF) • developed at NCAR• Non-hydrostatic Numerical Model (NMM) Core developed at NCEP• Both work under the WRF IO Infrastructure

NMM ARW

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The NCAR ARW Core Model:(See: www.wrf-model.org)

Terrain following vertical coordinate two-way nesting, any ratio Conserves mass, entropy and scalars using up to

6th order spatial differencing equ for fluxes. Very good numerics, less implicit smoothing in numerics.

NCAR physics package (converted from MM5 and Eta), NOAH unified land-surface model, NCEP physics adapted too

Page 14: Higher Resolution Operational Models

The NCEP Nonhydrostatic Mesoscale Model: NMM (Janjic et al. 2001), NWS

WRF

Hybrid sigmapressure vertical coord. 3:1 nesting ratio Conserves kinetic energy, enstrophy and

momentum using 2nd order differencing equation Modified Eta physics, Noah unified land-surface

model, NCAR physics adapted too

Page 15: Higher Resolution Operational Models

•The National Weather Service dropped Eta in 2006 as the NAM (North American Mesoscale) run and replaced it with WRF NMM.

•The Air Force uses WRF ARW.

•Most universities use WRF ARW

Page 16: Higher Resolution Operational Models

NWS NMM—The NAM RUN• Run every six hours over N. American and adjacent

ocean• Run to 84 hours at 12-km grid spacing.• Uses the Grid-Point Statistical Interpolation (GSI) data

assimilation system (3DVAR)• Start with GDAS (GFS analysis) as initial first guess at t-

12 hour (the start of the analysis cycle)• Runs an intermittent data assimilation cycle every three

hours until the initialization time.

Page 17: Higher Resolution Operational Models

October 2011 Update: NMMB

• One-way nested forecasts computed concurrently with the 12-km NMM-B parent run for

– CONUS (4 km to 60 hours)– Alaska (6 km to 60 hours)– Hawaii (3 km to 60 hours)– Puerto Rico (3 km to 60 hours)– For fire weather, moveable 1.33-km CONUS and 1.5-km Alaska nests are also run

concurrently (to 36 hours).

• A change in horizontal grid from Arakawa-E to Arakawa-B grid, which speeds up computations without degrading the forecast

Page 18: Higher Resolution Operational Models

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September 2011 NAM Upgrade

Current NAM• WRF-NMM (E-grid)• 4/Day = 6 hr update• Forecasts to 84 hours• 12 km horizontal grid

spacing

New NAM• NEMS based NMMB• B-grid replaces E-grid• Parent remains 12 km to 84 hr• Four Fixed Nests Run to 60 hr

– 4 km CONUS nest– 6 km Alaska nest– 3 km HI & PR nests

• Single placeable 1.33km or 1.5 km Single placeable 1.33km or 1.5 km FireWeather/IMET/DHS run to 36hrFireWeather/IMET/DHS run to 36hr

Page 19: Higher Resolution Operational Models

NMMB 4-km Conus

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NMM• Was generally inferior to GFS

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Page 22: Higher Resolution Operational Models

Looks like it has improved…

Page 23: Higher Resolution Operational Models