1 / 25

Higher Resolution Operational Models

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 WRF-ARW: Heavily used by research and some operational communities.

whitley
Download Presentation

Higher Resolution Operational Models

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Higher Resolution Operational Models

  2. Operational Mesoscale Model History • Early: LFM, NGM (history) • Eta (mainly history) • MM5: Still used by some, but phasing out • NMM- Main NWS mesoscale model • WRF-ARW: Heavily used by research and some operational communities. • The NWS calls their mesoscale run NAM: North American Mesoscale . Now NMM

  3. Vertical Coordinate Systems • Originally p and z • Then eta, sigma p and sigma z, theta • Increasingly use of hybrids– e.g., sigma-theta

  4. Sigma

  5. Sigma-Theta

  6. ground ground Hybrid and Eta Coordinates Ptop Ptop  = 0 Pressure domain  = 0 Sigma domain  = 1 MSL  = 1

  7. Horizontal resolution of 12 km 12-km terrain

  8. Nesting

  9. Why Nesting? • Could run a model over the whole globe, but that would require large amounts of computational resource, particularly if done at high resolution. • Alternative is to only use high resolution where you need it…nesting is one approach. • In nesting, a small higher resolution domain is embedded with a larger, lower-resolution domain.

  10. WRF Model Family A Tale of Two Dynamical Cores

  11. 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

  12. WRF Software Infrastructure Dynamic Cores Mass Core NMM Core … Static Initialization Post Processors, Verification Obs Data, Analyses 3DVAR Data Assimilation Standard Physics Interface Physics Packages WRF Modeling System

  13. 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

  14. 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

  15. The NCEP Nonhydrostatic Mesoscale Model: NMM (Janjic et al. 2001), NWS WRF • Hybrid sigmapressure 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

  16. 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

  17. 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.

  18. NAM 12-km Domain (dashed)

  19. In March Added 4-km Domains

  20. March 2011 Upgrade of HiResWindow 4.0 km WRF-NMM 5.15 km WRF-ARW 48 hr fcsts from both Unless there are hurricanes 18Z Expanded PR/Hispaniola domain 00Z 12Z 00Z 12Z 00Z 12Z Guam 06Z 06Z 18Z

  21. Details of NCEP HiResWindow Runs No Changes with This Upgrade

  22. NMM • Was generally inferior to GFS

More Related