Joe Klemp National Center for Atmospheric Research Boulder, Colorado, USA

1. WRF-CAM Collaborations for Future Weather and Climate Applications 3 km WRF/ARW 25 h reflectivity forecast CCSM2 20 year annually averaged precipitable water Joe Klemp National Center for Atmospheric Research Boulder, Colorado, USA

2. WRF/ARW Registered Users | | | | | | | | 2001 2002 2003 2004 2005 2006 2007 2008 WRF User Participation 4/4/08 Registered Users WRF Principal Partners 250 U.S. Universities (135) 1257 U.S. Government Labs 388 Private Sector 629 Foreign 3915 ------- Total 6439 New V3.0 registrations 1158 ------- 7597 Foreign countries represented 103 V3.0 release 3200 active subscribers to wrf-news@ucar.edu Currently averaging 400 email inquiries per month to wrfhelp

3. Characteristics, Features, & Capabilities Nonhydrostatic dynamical solver using higher order numerics and conservative prognostic equations Data-assimilation options through WRF-Var Flexible, extensible to range of WRF applications Parallel, efficient on range of computers in WRF community Movable, feature following nested grids Coupling to other models Petascale precursor systems ESMF Superstructure WRF component HYCOM component ESMF WRF Component Interface ESMF WRF Component Interface WRF I/O API ESMF Infrastructure Courtesy: Peter Johnsen and John Levesque, Cray WRF/ARW Model Overview WRF/HYCOM Coupling through ESMF

4. WRF-ARW Nonhydrostatic Dynamic Core • Terrain-following hydrostatic pressure vertical coordinate • Arakawa C-grid • 3rd order Runge-Kutta split-explicit time differencing, 5th or 6th order differencing for advection • Conserves mass, momentum, dry entropy, and scalars using flux form prognostic equations • Minimal additional computational damping Observed Kinetic Energy Spectra WRF-ARW Kinetic Energy Spectra

5. Physics Options Implemented in WRF • Microphysics: Kessler-type (no-ice), Lin et.al., Goddard, • WSM3/5/6, Ferrier, Thompson, Morrison • Cumulus Convection: New/Old Kain-Fritsch, Grell Ensemble, • Betts-Miller-Janjic, Grell-3 • Shortwave Radiation: Dudhia (MM5), Goddard, GFDL, CAM • Longwave Radiation: RRTM, GFDL, CAM • Turbulence: Prognostic TKE, • Smagorinsky, constant diffusion • PBL: MRF, MYJ, YSU • Surface Layer: Similarity theory, MYJ • Land-Surface: 5-layer soil model, RUC LSM • Noah unified LSM, CLM* * In progress

6. 1 10 100 km Model Physics in High Resolution NWP Physics “No Man’s Land” Resolved Convection Cumulus Parameterization 3-D Radiation Two Stream Radiation LES PBL Parameterization

7. WRF-ARW Real-Time Convective Forecasts

8. 3 km WRF-ARW Forecast 2007 NOAA HWT Spring Experiment Forecast and composite radar reflectivity for tornadic squall line at 01 UTC 4/14/07 25 h WRF/ARW 3 km forecast 2 km NOWRAD Mosaic

9. Number of cases Wind Speed (m/s) Cat 1: 33-42 Cat 2: 42-50 Cat 3: 50-59 Cat 4: 60-69 Cat 5: >69 2005 Real-time 4 km ARW Moving-Grid Hurricane Forecasts Katrina Wind Forecast, Initialized 00Z 27 Aug 2005 Number of cases

10. The Nested Regional Climate Model Phase 1: 1996-2000 & 2000-2005 Tropical Simulations Tropical Channel, 36 km, N/S boundaries 1-way nested into NCEP Reanalysis with specified SST, Kain-Fristch Cu Parameterization, CAM radiation and YSU boundary layer. 45o N 30o S 4 km nested domain inside 12 km and 36 km domains, fully 2-way interactive, Dudhia cloud physics, no cumulus parameterization. Wind Speed (m/s)

11. Monsoon Activity Monsoon intraseasonal activity is evident even in the unfiltered OLR data (Compare the outlined regions) Northward propagation of the convective anomalies Low-Pressure system moves from the Bay of Bengal into the Continent

12. NRCM Hurricane Simulations North Atlantic 12 and 4 km 2-way nested domains. Run may-October 2005 35N EQ 100W 20W 4 km res. domain 12 km res. domain No cumulus parameterization in 4 km domain

13. North Atlantic and North American Regional Climate Changes The goal is to simulate the effects of climate change on precipitation across the intermountain West States and tropical cyclones, with a focus on the Gulf of Mexico. • Outer domain nested into CCSM, which also provides surface conditions. • 1996-2000, then three 5-y time slices out to 2050 • 5 ensemble members for each period • Allocated half of NCAR IBM Blue Fire for 2 months

14. CAM physics - WRF status CAM 3 radiation - In WRF Version 3.0 release CLM 3 land-surface - Mostly added to WRF non-repository code - requires linking to WRF initial state and land properties - implemented directly into WRF executable code rather than by coupling PBL - potentially Holtslag Boville or Bretherton scheme could be added to WRF with little effort Convection - several CAM options, but considering Neale-Richter, probably little effort Cloud microphysics - 2-moment Morrison scheme in CAM is being considered (complications include whether to also add sub-column or cloud fraction parameterizations to WRF) Subgrid-scale dynamics - potentially gravity wave drag, but currently porting Hong orographic drag scheme instead. This is already in progress. Porting CAM physics to WRF is a high priority !

15. Simulation speed Mars at northern summer solstice (temperature and zonal wind) 80% efficiency GFDL MARS GCM Oxford Mars GCM Global WRF WRF Global Model Global WRF on a lat-long grid • Adapted from community development at Cal Tech for planetary atmospheres • Functional system for nested nonhydrostatic global simulations • Baseline for future nonhydrostatic global model development 10 day precipitable water forecast, initialized 7-11-2007 12Z 810 x 405 x 41 (x,y,z), ~50 km grid at the equator, 200 second timestep 512x256 810x405

16. The Atmospheric Component Towards a Next Generation Climate-Weather-Earth System Model (Courtesy of Morris Weisman)

17. Existing and future applications require meso-scale and cloud-scale resolution in a global model. • Current climate models are poor weather models, and current weather models are poor climate models. • Opportunity to leverage the diverse interests and experience of the climate and weather communities to create and share a next-generation atmospheric simulation system. Motivation

18. What is Wrong With Our Existing Global Models? Why use higher resolution? • Explicitly simulate convective systems: • Capture system evolution (growth, decay, propagation). • Resolve moisture redistribution, cloud systems. • Remove need for deep cumulus parameterization (with sufficient resolution - x < a few km). • Explicitly simulate gravity waves, wave breaking: • Remove the need for gravity-wave drag parameterization. • Better resolution of external forcing: • topography, land-use, etc. They do not scale to 104 - 105 processors. (e.g. lat-long grid models) They were not constructed for mesoscale/cloudscale applications (e.g. physics, numerics, tuning).

19. Towards a Next Generation Climate-Weather-Earth System Model The Atmospheric Component • Objectives • For weather, climate, and ESM requirements: • Construct an atmospheric dynamical core that runs efficiently on existing and future MPP computers, and has sufficient flexibility for diverse applications. • Unify and share physics, and leverage development efforts, where possible.

20. ESM Atmospheric Component WG • Atmospheric Dynamical Core • Subgroup • Bill Skamarock (facilitator) • 25 members (14 outside NCAR) • Fall workshop being planned • Atmospheric model physics • Subgroup • Phil Rasch and Dan Marsh (facilitators) • Still being formed • CCSM and WRF scientists Phil Rasch, Dan Marsh, Bill Skamarock (co-chairs) The working (sub)groups serve as forums for discussions and information dissemination, and provide recommendations, critiques, and reviews.

21. NCAR External Joern Behrens (Alfred Wegener Institute) Jean-Michel Campin (MIT) Phil Colella (Lawrence Berkeley Labs (LBL)) Bill Collins (LBL) John Drake (ORNL) Dale Durran (Univ. Washington) Christiane Jablonowski (Univ. Michigan) Jin Lee (NOAA/GSD) Bill Putnam (NASA) Todd Ringler (LANL) Richard Rood (U. Mich.) Mark Taylor (Sandia) John Thuburn (Exeter Univ.) Robert Walko (Duke Univ.) ESM Atmospheric Core WG Members George Bryan Joe Klemp Peter Lauritzen Ram Nair Phil Rasch Amik St-Cyr Bill Skamarock Piotr Smolarkiewicz Joe Tribbia Henry Tufo Dave Williamson

22. Features of a Weather and Climate ESM Dynamical Core Strong Consensus Fully compressible nonhydrostatic equations Mass conserving Scalar mass conserving, consistent. Positive-definite (PD) transport for PD scalars Local refinement capability Regional modeling capability

23. Features of a Weather and Climate ESM Dynamical Core Desirable Features Monotonic transport options Horizontal grid uniformity (little variation in cell area) Horizontal grid isotropy (dx ~ dy) Energy conservation?

24. Features of a Weather and Climate ESM Dynamical Core Evaluation Metrics and Issues Good energetics KE spectra (resolving both synoptic- and meso-scales) Dissipational and frictional heating Efficient (cost for a given accuracy level) On MPP architectures Global to cloud scales, weather and climate Low-order schemes or higher-order schemes? Implicit or explicit formulations? The grid should be invisible

25. Some Possible Discretizations for the Sphere lat-long grid triangular grid hexagonal grid cubed sphere yin-yang grid • High-order solvers • Grid-cell isotropy • Uniformity of grid-cell sizes • Grid continuity, handling of special points • Local refinement Issues:

26. Nonhydrostatic Modeling on Hexagonal C-Grid • New ESM core must function effectively at both global and cloud-resolving scales • Icosahedral hexagonal grid has good potential to satisfy these requirements. • Hexagonal grids have not been evaluated for cloud-scale applications. • C-grid staggering on hexagonal grids not widely accepted 12 pentagons Global Hexagonal Grid Limited Area Hexagonal C-Grid

27. 3-D Cloud Model on Hexagonal Grid Splitting Supercell at 2 hours • Research Progress: • Constructed a 3-D limited-area hexagonal-grid cloud model (based on WRF/ARW numerics) to evaluate performance. • Documented that hexagonal-grid cloud simulations are at least as accurate and computationally more efficient than those on a conventional rectangular grid. 1 km Hexagonal Grid Simulation

28. Atmospheric Component: The Path Forward 3 years from now Capable of global cloud-resolving simulations - days to months. This implies Developing and testing of promising dynamical core prototypes, and a decision on a first ESM dynamical core within 2 years. Developing and porting of select physics. Developing a computational framework suitable for the dynamical solver, the physics, and model-coupling needs. Developing archival capabilities, and analysis and post-processing tools. Resources for development, testing, and near-term applications.