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ESMF and the Weather Research and Forecast Model

ESMF and the Weather Research and Forecast Model . John Michalakes, Thomas Henderson Mesoscale and Microscale Meteorology Division National Center for Atmospheric Research michalak@ucar.edu Thomas Black Environmental Modeling Center NOAA / National Centers for Environmental Prediction.

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ESMF and the Weather Research and Forecast Model

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  1. ESMF and the Weather Research and Forecast Model John Michalakes, Thomas Henderson Mesoscale and Microscale Meteorology Division National Center for Atmospheric Research michalak@ucar.edu Thomas Black Environmental Modeling Center NOAA / National Centers for Environmental Prediction

  2. Weather Research and Forecast Model Goals: Develop an advanced mesoscale forecast and assimilation system, and accelerate research advances into operations • Large collaborative effort to develop next-generation community model with direct path to operations • Advanced Software Architecture • Modular, flexible, extensible • Portable and efficient • Designed for HPC • Applications • Atmospheric Research • Numerical Weather Prediction • Coupled modeling systems • Air quality research/prediction • High resolution regional climate • prediction • Air quality research and prediction • Regional climate + DTC

  3. Top-level Control, Memory Management, Nesting, Parallelism, External APIs driver ARW solver NMM solver Physics Interfaces mediation Plug-compatible physics Plug-compatible physics Plug-compatible physics Plug-compatible physics model Plug-compatible physics Weather Research and Forecast Model Goals: Develop an advanced mesoscale forecast and assimilation system, and accelerate research advances into operations • Large collaborative effort to develop next-generation community model with direct path to operations • Advanced Software Architecture • Modular, flexible, extensible • Portable and efficient • Designed for HPC • Applications • Atmospheric Research • Numerical Weather Prediction • Coupled modeling systems • Air quality research/prediction • High resolution regional climate • prediction • Air quality research and prediction • Regional climate

  4. ESMF Support • WRFV2.2 fully interoperable as ESMF component • Runs stand-alone without ESMF, or • Fully integrated component in ESMF • Distributed with ESMF unit test coupled “data” ocean • Infrastructure: • ESMF Time Manager using reference implementation or shared implementation with CCSM • Superstructure: “Wrapperized” • Top level init-run-finalize convention • ESMF conforms to “coupling as I/O” and is integrated with WRF Registry

  5. Extension of WRF I/O API MCEL (U. Southern Miss.) MCT (Argonne NL) ESMF Projects WRF/ROMS, WRF/ADCIRC/SWAN/LSOM Very high resolution urban airflow modeling (Fei Chen, NCAR; CFD Corp.) Coupled WRF/HYCOM Katrina simulation MCEL MCT ESMF WRF Model Coupling ESMF Superstructure

  6. WRF and HYCOM two-way coupled through ESMF to improve modeling of hurricane intensification Synchronization is through successive calls to components by ESMF top-level driver Status: WRF an ESMF component (NCAR), Init-run-finalize at top level Import/export through WRF I/O API ESMF Time Manager WRF I/O in ESMF HYCOM-ESMF (NRL) HYCOM component ESMF WRF Component Interface WRF/HYCOM Coupling (ESMF) ESMF Superstructure WRF export state: Surface winds & air temps Precipitation Radiation fluxes WRF import state: SST, Roughness length HYCOM export state: SSTs HYCOM import state: Winds Precipitation Radiation fluxes execution control regridding … WRF component ESMF WRF Component Interface WRF I/O API ESMF Infrastructure

  7. WRF/LIS Coupling through ESMF • LIS = Land Information System • NASA GSFC (lis.gsfc.nasa.gov) • Incorporates CLM, Noah, and VIC land surface models • Initial WRF-LIS prototype by Sujay Kumar (GSFC) • Coupled via WRF surface driver using ESMF • All ESMF objects manufactured by LIS • Planned • WRF provides ESMF_State objects to LIS • Extend to allow different grids

  8. Interoperability • Supported metadata formats: NetCDF+parallel, HDF+parallel, GRIB[1&2] • Participating in continuing refinement of Climate and Forecast metadata convention • Participate in GOESSP meetings to discuss conventions (go-essp.gfdl.noaa.gov) • Provide feedback for Balaji’s “Gridspec” proposal (www.gfdl.noaa.gov/~vb/gridstd/gridstd.html)

  9. Interoperability • Share goals with Earth System Curator • Similar approaches may apply to forecast V&V, managing ensembles, etc. • Earth System Curator-Numerical Model Metadata (NMM) standard • http://ncas-cms.nerc.ac.uk/NMM/index.php • Full specification of an “experiment” • Automatic testing of component compatibility

  10. Key obstacle for Petascale; opportunity for new approaches, e.g. PGAS languages Instrument WRF using PAPI Generated high-resolution traces over 8 day period in July ’05 Characterize dynamic load from microphysics as functions of Decomposition Sizes, trajectories, other characteristics of load features Dynamic Load Balancing Workload Characterization of Physics-Induced Load Imbalance in WRF (draft NCAR TM, 2007)

  11. Key obstacle for Petascale; opportunity for new approaches, e.g. PGAS languages Instrument WRF using PAPI Generated high-resolution traces over 8 day period in July ’05 Characterize dynamic load from microphysics as functions of Decomposition Sizes, trajectories, other characteristics of load features Dynamic Load Balancing Workload Characterization of Physics-Induced Load Imbalance in WRF (draft NCAR TM, 2007) Figure 6: Maximum, average, minimum, and standard-deviation of load imbalance over eight-day measurement period as function of subdomain size.

  12. Plans • Convergence of ESMF and WRF software • WRF as ESMF component (current) • Support for additional infrastructure elements • Support for ESMF components coupled in WRF call tree • Continue to follow, participate in data-interoperability standardization (C.F., Curator)

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