1. 10/22/2015 Zängl ICON The next-generation global model for numerical weather prediction and climate modeling of DWD and MPI-M Current development status and the way towards preoperational testing Günther Zängl and the ICON development team

2. 22.10.2015 Zängl  General overview of ICON and its current development status  Selected results of idealized mountain tests and of (a very first) real-data forecast  Further planning towards preoperational testing  Summary Outline

3. 22.10.2015 Zängl ICON = ICOsahedral Nonhydrostatic model  Joint development project of DWD and Max-Planck-Institute for Meteorology for the next-generation global NWP and climate modeling system  Nonhydrostatic dynamical core for triangles and hexagons as primal grid; C-grid discretization; coupling with physics parameterizations in principle completed  Two-way nesting for triangles as primal grid, capability for multiple nests per nesting level; vertical nesting, one-way nesting mode and limited-area mode are also available  Work in progress: Thorough testing (and debugging) of physics parameterizations and physics-dynamics coupling, GRIB2 I/O, further optimization of MPI parallelization, data assimilation, ocean model on triangular grid ICON

4. 22.10.2015 Zängl Primary development goals  Better conservation properties (air mass, mass of trace gases and moisture, consistent transport of tracers; hexagonal core also conserves energy)  Grid nesting in order to replace both GME (global forecast model, mesh size 30 km) and COSMO-EU (regional model, mesh size 7 km) in the operational suite of DWD  Applicability on a wide range of scales in space and time ("seamless prediction"); therefore, the dynamical core was requested to be nonhydrostatic  Scalability and efficiency on massively parallel computer architectures with O(10 4 +) cores ICON

5. 22.10.2015 Zängl G. Zängl Project leader DWD two-way nesting, parallelization, optimization, numerics H. Asensioexternal parameters M. Baldauf NH-equation set K. Fröhlich physics parameterizations M. Köhlerphysics parameterizations D. Liermann post processing, preprocessing IFS2ICON F. Prillnumerics, optimization, parallelization D. Reinert advection schemes P. Ripodas test cases,power spectra B. Ritter physics parameterizations A. Seifertcloud microphysics U. Schättler software design MetBw T. Reinhardt physics parameterizations M. Giorgetta Project leader MPI-M physics parameterizations M. Esch software maintenance A. Gaßmann NH-equations, numerics P. Korn ocean model L. Kornblueh software design, hpc L. Linardakis parallelization, grid generators S. Lorenzocean model C. Mosleyregionalization R. Müllerpre- and postprocessing T. Raddatzexternal parameters F. Rauser adjoint version of the SWM W. SaufAutomated testing (Buildbot) U. Schulzweida external post processing (CDO) H. Wan 3D hydrostatic model version, physics parameterizations External: R. Johanni: MPI-Parallelization Project teams at DWD and MPI-M

6. 22.10.2015 Zängl The horizontal grid

7. 22.10.2015 Zängl Primary (Delaunay, triangles) and dual grid (Voronoi, hexagons/pentagons) The horizontal grid

8. 22.10.2015 Zängl latitude-longitude windows circular windows Grid structure with nested domains

9. 22.10.2015 Zängl v n,w: normal/vertical velocity component  : density  v : Virtual potential temperature K: horizontal kinetic energy  : vertical vorticity component  : Exner function blue: independent prognostic variables Nonhydrostatic equation system

10. 22.10.2015 Zängl Two-time-level predictor-corrector time stepping scheme 2D Lamb transformation for nonlinear momentum advection Flux form for continuity equation and thermodynamic equation; Miura 2 nd -order upwind scheme (centered differences) for horizontal (vertical) flux reconstruction implicit treatment of vertically propagating sound waves, but explicit time-integration in the horizontal (at sound wave time step; not split-explicit); larger time step (default 4x) for tracer advection / fast physics Mass conservation and tracer mass consistency Numerical implementation

11. 22.10.2015 Zängl Finite-volume tracer advection scheme (Miura) with 2 nd -order and 3 rd -order accuracy for horizontal advection; 2 nd -order MUSCL and 3 rd -order PPM for vertical advection with extension to CFL values larger than 1; monotonous and positive-definite flux limiters Special measures to improve the numerical stability over steep terrain: Option for truly horizontal temperature diffusion over steep slopes Option for truly horizontal discretization of the horizontal pressure gradient over steep slopes Numerical implementation

12. Precompute for each edge (velocity) point at level the grid layers into which the edge point would fall in the two adjacent cells Discretization of horizontal pressure gradient (apart from conventional method) dashed lines: main levels pink: edge (velocity) points blue: cell (mass) points A S

13. Reconstruct the Exner function at the mass points using a quadratic Taylor expansion, starting from the point lying in the model layer closest to the edge point Discretization of horizontal pressure gradient Note: the quadratic term has been approximated using the hydrostatic equation to avoid computing a second derivative Treatment at slope points where the surface is intersected:

14. 22.10.2015 Zängl Cloud microphysics from COSMO-EU (hydci_pp) New mass-conserving saturation adjustment scheme (U. Blahak/ A. Seifert) Turbulence schemes from COSMO-model (M. Raschendorfer) and ECHAM Tiedtke-Bechtold convection scheme (from ECMWF) COSMO cloud cover scheme; new scheme under development by M. Köhler Ritter-Geleyn and RRTM radiation schemes TERRA surface scheme Physics parameterizations

15. Isolated circular Gaussian mountain, e-folding width 2000 m, various mountain heights (see subsequent slides) Isothermal atmosphere at rest or with u 0 = 20 m/s Horizontal mesh size  300 m 50 vertical levels, top at 40 km, gravity-wave damping layer starts at 27.5 km dry dynamical core with turbulence scheme for vertical mixing Results are shown after 6 h of integration time Idealized steep-mountain test

16. 22.10.2015 Zängl vertical wind speed (m/s)potential temp. (c.i. 4 K), hor. wind speed (m/s) mountain height: 2.25 km, isothermal atmosphere at rest maximum slope 0.95 (43.5°) conventional pressure gradient discretization, no z-diffusion of temperature

17. 22.10.2015 Zängl conventional pressure gradient discretization, with z-diffusion of temperature vertical wind speed (m/s)potential temp. (c.i. 4 K), hor. wind speed (m/s) mountain height: 2.25 km, isothermal atmosphere at rest maximum slope 0.95 (43.5°)

18. 22.10.2015 Zängl conventional pressure gradient discretization, with z-diffusion of temperature vertical wind speed (m/s)potential temp. (c.i. 4 K), hor. wind speed (m/s) mountain height: 3.0 km, isothermal atmosphere at rest maximum slope 1.27 (52°)

19. 22.10.2015 Zängl z-based pressure gradient discretization, and z-diffusion of temperature vertical wind speed (m/s)potential temp. (c.i. 4 K), hor. wind speed (m/s) mountain height: 3.0 km, isothermal atmosphere at rest maximum slope 1.27 (52°)

20. 22.10.2015 Zängl vertical wind speed (m/s)potential temp. (c.i. 4 K), hor. wind speed (m/s) mountain height: 3.75 km, isothermal atmosphere at rest maximum slope 1.59 (58°) z-based pressure gradient discretization, and z-diffusion of temperature

21. 22.10.2015 Zängl vertical wind speed (m/s)potential temp. (c.i. 4 K), hor. wind speed (m/s) mountain height: 4.5 km, isothermal atmosphere at rest maximum slope 1.90 (62°) z-based pressure gradient discretization, and z-diffusion of temperature

22. 22.10.2015 Zängl vertical wind speed (m/s)potential temp. (c.i. 4 K), hor. wind speed (m/s) mountain height: 3.5 km, isothermal atmosphere with u 0 = 20 m/s maximum slope 1.49 (56°) z-based pressure gradient discretization, and z-diffusion of temperature

23. 22.10.2015 Zängl vertical wind speed (m/s)potential temp. (c.i. 4 K), hor. wind speed (m/s) mountain height: 4.5 km, isothermal atmosphere with u 0 = 20 m/s maximum slope 1.90 (62°) z-based pressure gradient discretization, and z-diffusion of temperature

24. Global mesh size 40 km, refinement to 20 km over Europe Model top at 45 km, 60 levels (another expt.: 67.5 km / 90 levs) Time step in global domain: 60s / 240s Initialization with interpolated IFS analysis data for 01.01.2011 Total integration time: 20 days Results shown on subsequent slides: 3-day forecast in comparison with corresponding analysis data Real-data test

25. Temperature at 3 km AGL 22.10.2015 Zängl

26. Specific humidity at 3 km AGL 22.10.2015 Zängl

27. Pressure at 3 km AGL 22.10.2015 Zängl

28. Further steps towards preoperational testing Thorough investigation of still exisiting numerical instabilities; bug fixes or improvement of algorithms Test suites for ICON and GME with interpolated IFS analysis data; systematic tuning of physics parameterizations and their mutual interaction (maybe also physics-dynamics coupling) Work on GRIB2 I/O, interpolation to lat-lon grid and pressure/ height levels, meteogram output, … Data assimilation

29. 22.10.2015 Zängl Conclusions and further remarks We are on a good way, but there is still a lot to do… Efficiency and scalability: significantly better than for GME; roughly comparable to the COSMO model Time planning: start with preoperational testing late 2011 / early 2012; operational use (hopefully) by mid-2013