Facilitating Research into Operation: NCAR perspective

1. Facilitating Research into Operation: NCAR perspective Roger Wakimoto NCAR

2. Integrated Science Program (ISP) Peter Backlund Advanced Study Program (ASP) Chris Davis NCAR Library Mary Marlino Research Relations Peter Backlund Member Institutions Board of Trustees UCAR Richard Anthes, President Finance & Administration Katy Schmoll, VP Corporate Affairs Jack Fellows, VP Budget & Planning(B&P) Rena Brasher-Alleva NCAR Roger Wakimoto, Director Maura Hagan, Deputy Director UCAR Community Programs (UCP) Jack Fellows, Director Hanne Mauriello, B&A Cooperative Program for Operational Meteorology Education & Training (COMET) Tim Spangler Global Learning & Observations to Benefit the Environment (GLOBE) Ed Geary Constellation Observing System for Meteorology Ionosphere Climate (COSMIC) Bill Kuo Digital LearningSciences (DLS) Karon Kelly Computational & Information Systems Laboratory (CISL) Al Kellie, Associate Director Earth Observing Laboratory (EOL) Sue Schauffler, Acting Associate Director Unidata Mohan Ramamurthy Visiting Scientists Program (VSP) Meg Austin NCAR Earth System Laboratory (NESL) Greg Holland, Interim Associate Director Research Applications Laboratory (RAL) Brant Foote, Associate Director Joint Office for Science Support (JOSS) Gene Martin National Science Digital Library (NSDL) Kaye Howe High Altitude Observatory (HAO) Michael Thompson, Associate Director

3. Governing Entities UCAR (University Corporation for Atmospheric Research) NCAR (National Center for Atmospheric Research) and Labs Institute Facility & Service Providers Scientific Research Divisions Education & Application Programs UOP (UCAR Office of Programs) Earth Observing Laboratory (EOL) Roger Wakimoto, Associate Director Computational & Information Systems Laboratory (CISL) Al Kellie, Associate Director Research Applications Laboratory (RAL) Brant Foote, Associate Director Institute for Mathematics Applied to Geosciences (IMAGe) Doug Nychka Aviation Applications Program (AAP) Bruce Carmichael Cyberinfrastructure & Data Services (CDS) Michael Daniels Climate Science and Applications Program (CSAP) Lawrence Buja Operations & Services Division Anke Kamrath Design & Fabrication Services (DFS) Jim Moore, Interim Hydrometeorological Applications Program (HAP) Roy Rasmussen Technology Development Division Rich Loft Field Project Services (FPS) Brigitte Baeuerle Joint Numerical Testbed (JNT) Barb Brown NCAR Earth System Laboratory (NESL) Greg Holland, Interim Associate Director In-Situ Sensing Facility (ISF) Stephen Cohn National Security Applications Program (NSAP) Scott Swerdlin Atmospheric Chemistry Division (ACD) Bill Randel Weather Systems & Assessment Program (WSAP) Bill Mahoney Research Aviation Facility (RAF) Jeff Stith Climate & Global Dynamics Division (CGD) Bill Large Mesoscale & Microscale Meteorology Division (MMM) Rich Rotunno (Interim) Remote Sensing Facility (RSF) Wen-Chau Lee (Acting) Technology Development Facility (TDF) Alan Fried High Altitude Observatory (HAO) Michael Thompson, Associate Director

4. NCAR involvement with DTC • Approximately 2/3 of DTC staff reside in RAL’s Joint Numerical Testbed • NCAR hosts the DTC Director’s Office • NCAR/NESL/MMM provides support for the WRF modeling community • Modeling research & development conducted at NCAR have significant potentials for operational applications

5. Worldwide WRF User Participation 130 Foreign Countries WRF Registered Users Registered Users 8/08/10 U.S. Universities, govt. labs, and private sector 4759 Foreign users 9272 -------- 14031 5070 active subscribers to wrf-news@ucar.edu 425 email inquiries per month

6. WRF User Community • WRF is a modeling systemjointly developed by the research and operational community over the past decade • The number of registered user exceeds 14,000, and it keeps growing. • This is a big community of which operational centers can leverage its research results. • NCAR/MMM, NCEP/EMC, and DTC provide community user support for WRF modeling system • NCEP is transitioning to the NEMS framework for its modeling systems. • We need to ensure there is a path for research-to-operation transition. Model software framework should not become an obstacle for collaboration.

7. NCAR’s Modeling R&D: Some examples • NESL: • Development of Model for Prediction Across Scales (MPAS) • WRF 4D-Var system • WRF EnKF data assimilation • Radar data assimilation • Cloud-scale ensemble prediction • CISL: • DART (Data Assimilation Research Testbed) • RAL: • Model verification tools development • Aviation weather forecasting

8. MPAS: Model for Prediction Across Scales Based on Voronoi Tesselations (hexagons) Jointly developed, primarily by NCAR and LANL, for weather, regional climate and climate applications. MPAS infrastructure - NCAR, LANL, others. MPAS - Atmosphere (NCAR) MPAS - Ocean (LANL) MPAS - Ice, etc. Bill Skamarock, Joe Klemp, Michael Duda, Sang-Hun Park, Laura Fowler NCAR/NSF Todd Ringler LANL/DOE John Thuburn Exeter University Max Gunzburger Florida State University Lili Ju University of South Carolina

9. MPAS formulation is demonstrably accurate and efficient at both large and small scales, and should scale well on next-generation supercomputers. MPAS-Atmosphere, global configuration MPAS-Atmosphere, cloud-model configuration Prediction Across Scales 500 m cell spacing Supercell at 2 hours Vertical velocity contours at 1, 5, and 10 km (c.i. = 3 m/s) 30 m/s vertical velocity surface shaded in red Rainwater surfaces shaded as transparent shells Perturbation surface temperature shaded on baseplane Jablonowski and Williamson baroclinic wave test case. Relative vorticity (s-1), day 16 (jet level)

10. MPAS: Variable Resolution Capability Local refinement capabilities are critical for NWP and regional climate applications. • Initial test results using variable resolution grids are encouraging • (baroclinic waves and squall lines). • Atmospheric (hydrostatic and nonhydrostatic) and ocean solvers are robust on these grids.

11. MPAS - Current Status - August 2010 3D Solvers Hydrostatic 3D SVCT solver (pressure coordinate). Nonhydrostatic 3D SVCT solver (height coordinate). Both solvers work on the sphere and on 2D and 3D Cartesian domains. Tests results confirm viability of Voronoi C-grid discretization at large scales (global) and cloud-permitting scales for both solvers. Variable-resolution grid results are encouraging. Present and Future Development Weather, regional climate and climate physics suites. Further testing of variable resolution meshes, physics development. Further development and testing of higher-order transport schemes. Expectations NWP testing by early next year. Friendly-user release summer/fall 2011.

12. MPAS - Current Status - August 2010 Software Engineering MPAS software: Developed based on MPAS applications requirements. Lightweight (for rapid prototyping, ease of maintenance). We have developed and use a Registry similar to that used in the WRF infrastructure. We are exploring using other model physics (e.g. from CCSM, WRF, GFS) directly from the other models’ repositories (in the spirit of Kalnay et al’sInterchange of Physical Parameterizations proposal in BAMS 1989 620-622). We are considering possible model couplers (e.g. CPL7). We have not adopted any formal software framework. We are considering lightweight, industry-standard approaches for the MPAS software infrastructure (e.g. OOPS - Object-Oriented Prediction System being developed at ECMWF).

13. The Ensemble Kalman Filter (EnKF) • EnKF combines data assimilation and ensemble forecasting • Analysis step produces ensemble of analyses, given new observations • Analysis step employs covariance, estimated from short-range ensemble • In forecast step, make ensemble of short-range forecasts from ensemble of analyses • Attractions for mesoscale applications • Few assumptions about covariances, so applicable to range of scales/phenomena • Flexible to details of model, such as complex microphysical schemes • Ease of implementation and parallelization; no adjoints • For applications here, use 50-100 members

14. Data Assimilation Research Testbed (DART) • Provides general, model-independent algorithms for ensemble filtering • Numerous DART-compliant models • ARW, CAM, NOGAPS, … • Applications to atmospheric, ocean, and space weather data assimilation • Parallel analysis scheme that scales well to 100’s of processors • See http://www.image.ucar.edu/DAReS/DART/

15. Real-Time Analyses for Tropical Cyclones • Analyses from WRF/DART provided ICs for NCAR’s high-res TC forecasts during 2009 season • Produced 36-km analyses every 6 h • Assimilate conventional obs + satellite winds + vortex position, intensity • NObogussing of any kind; no satellite radiances • WRF configuration • “hurricane” physics + KF convection • 36 km, with stationary 12-km nest centered on each TC/TS/TD • System cycled continuously for ~ 4 months

16. Real-Time Analyses for Tropical Cyclones (cont.)

17. Real-Time Analyses for Tropical Cyclones (cont.) • Analyses captured all 2009 storms, from depressions to hurricanes. • No need to bogus • No spurious storms, despite not assimilating radiances RMS fits of analysis and 6-h forecast to best-track estimates Courtesy R. Torn

18. Real-Time Analyses for Tropical Cyclones (cont.) • Analysis increment from position observation • Reflects covariance (wind speed, vortex position), which in turn reflects vortex structure • Shifts vortex coherently and consistently in all model fields Hurricane Bill, 00Z 19 Aug 2009 Wind speed @ 1st level contours: ens.-mean, 6-h forecast colors: increment given obs of vortex position (analysis - forecast) Courtesy S. Cavallo

19. Radar data assimilation slides WRF-VAR radar data assimilation testing in central U.S. • Radar data assimilation • systems are being tested and • improved over selected U.S. • regions and foreign countries • These systems include GSI, • WRF-VAR, and WRF/DART. • 3DVAR, 4DVAR, and EnKF • are all involved in the • testing/development. • These systems are tested with • WRF as the forecast model and • with a goal to support • operational applications. b) WRF 1h FCST 25 radars assimilated Beijing operational pre-testing Radar Mosiac WRF 3h FCST

20. Different requirements in Operation and Research NWP • Operation: • Robustness • Efficiency • Easy maintenance • Prefers incremental changes • Thorough testing • Research: • Flexibility • Multiple-choices • User friendliness • Community support • Innovation

21. Effective Research to Operation Transition • Need to challenge (attract) research community to work on problems of interest to operation • Need a clear path for R2O • Need to minimize obstacles preventing R2O (e.g., model software framework) • Need to provide sufficient support for O2R and R2O activities

22. Concluding Remarks • NCAR is committed to: • Support the WRF community for many more years to come. • Support the development of next generation modeling and data assimilation systems (e.g., MPAS, DART/EnKF) • Support the research to operation transition through the DTC