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ICON The new global nonhydrostatic model of DWD and MPI-M

Daniel Reinert 1 , Günther Zängl 1 , and the ICON-team 1,2 1 Deutscher Wetterdienst / 2 Max-Planck-Institute for Meteorology 13 th EMS Annual Meeting 09 – 13 September 2013, Reading, United Kingdom. ICON The new global nonhydrostatic model of DWD and MPI-M.

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ICON The new global nonhydrostatic model of DWD and MPI-M

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  1. Daniel Reinert1, Günther Zängl1, andthe ICON-team1,2 1Deutscher Wetterdienst / 2Max-Planck-Institute forMeteorology 13th EMS Annual Meeting 09 – 13 September 2013, Reading, United Kingdom ICON The new global nonhydrostatic model of DWD and MPI-M

  2. ICON – ICOsahedralNonhydrostaticModel • Joint developmentprojectofDWDandMax-Planck-Institute forMeteorologyforbuilding a next-generation global NWP andclimatemodellingsystem • Atmosphereandocean model DWD MPI Outline Project goals Horizontal grid structure and accompanying problems ICON NWP physics suite Selected results Roadmap and Summary Daniel Reinert – 12.09.2013

  3. Primary developmentgoals • Improvedconservationproperties (at least mass) andconsistenttracertransport (tracerair-massconsistency) • Applicability on a widerangeofscalesfrom100 km to 1 km • Scalabilityandefficiency on massively parallel computerarchitectureswith O(104 +) cores • Localrefinement/nestingcapability • At DWD: • Replace current global model GME • Replace regional model COSMO-EU by a high-resolution window over Europe. • At MPI-M: • Use ICON as dynamical core of an Earth System Model (MPI-ESM2) Horizontal grid with nest over Europe Daniel Reinert – 12.09.2013

  4. ICON’s unstructured grid Primal cells: triangles • uses icosahedron for macro triangulation • C-type staggering: • local subdomains (“nests”) • velocity at edge midpoints • mass at cell circumcenter Triangular C-Grid local domain(s) global domain Daniel Reinert – 12.09.2013

  5. Equations (dry adiabatic) and solver • Fully compressible nonhydrostatic vector invariant form, shallow atm. • Solver: • Finite volume/finite difference discretization(mostly 2nd order) • Two-time level predictor-corrector time integration • Vertically implicit (vertical sound-wave propagation) • Fully explicit time integration in the horizontal (at sound wave time step; not split explicit!) • Mass conserving Daniel Reinert – 12.09.2013

  6. Checkerboard noise on triangular C-Grid • Main problem with triangular C-grid: suffers from spurious computational mode (e.g. Danilov (2010)), triggered by the discretized divergence operator (Wan (2013)) • Divergence operator: applies the Gauss theorem • Truncation error (Wan (2013)): • Only 1st order accurate on triangular C-grid • Error changes sign from upward- to downward pointing triangle  checkerboard Example for synthetic velocity field (Wan, 2013) Daniel Reinert – 12.09.2013

  7. Controlling the checkerboard noise • Goal: Eliminate 1st order error • Basic idea: Divergence averaging II: Compute divergence estimate based on immediate neighbors (2nd order bilinear interpolation) I: Compute standard 1st order div III Averaging: 2nd order accurate for isosceles triangles Daniel Reinert – 12.09.2013

  8. Example: Baroclinic wave Jablonowski-Williamson (2006) baroclinic wave test case T PS Daniel Reinert – 12.09.2013

  9. Example: Baroclinic wave Jablonowski-Williamson (2006) baroclinic wave test case T PS Standard divergence operator Divergence averaging div div “checkerboard” noise Daniel Reinert – 12.09.2013

  10. ICON NWP-physics Daniel Reinert – 12.09.2013

  11. Reduced grid for radiation • Hierarchical structure of the triangular mesh is very attractive for calculating physical processes (e.g. radiative transfer) with different spatial resolution compared to dynamics. upscaling Radiation step Radiative transfer computations Empirical corrections every 30min downscaling Daniel Reinert – 12.09.2013

  12. Proof of concept • net surface shortwave flux (reduced – full grid) • average over 30 x 48h forecast runs in June 2012 Avg: 1.57 Reduced radiation grid currently generates positive bias in Daniel Reinert – 12.09.2013

  13. Flat-MPI performance Recall goal: scalability up to O(104+) cores time (s) 4096 1024 4096 1024 MPI tasks Test setup: ICON RAPS 2.0, IBM Power 7 20/10/5 km, 8h forecast, reduced radiation grid (S. Körner, DWD, 03/2013) Daniel Reinert – 12.09.2013

  14. Selected results of NWP test suite • Real-case 7-day forecasts with interpolated IFS analysis data • WMO standard verification against IFS analysis on 1.5° lat/lon grid. • Comparison against GME reference experiment with interpolated IFS analysis data. • Basic requirement for operational use of ICON • ICON must outperform GME in terms of forecast quality/scores Daniel Reinert – 12.09.2013

  15. Verification: Surface Pressure, January 2012 Region:Northern hemisphere (NH) ICON GME against IFS SH: 21% Verification: G. Zängl, U. Damrath, 08/2013 (DWD) Daniel Reinert – 12.09.2013

  16. Verification: Geopot 500 hPa, January 2012 Region:Northern hemisphere (NH) ICON GME against IFS SH: 9.4% Verification: G. Zängl, U. Damrath, 08/2013 (DWD) Daniel Reinert – 12.09.2013

  17. Verification: Rh 700 hPa, January 2012 Region:Tropics (Tr) ICON GME against IFS ICON shows strong positive moisture bias in the tropics Verification: G. Zängl, U. Damrath, 08/2013 (DWD) Daniel Reinert – 12.09.2013

  18. Roadmap towards operational application Daniel Reinert – 12.09.2013

  19. Summary ICON is entering the home stretch for becoming operational • Verification results are mostly exceeding those of GME, but there are still some weaknesses/biases e.g. moisture field • Technical parts scale on massively parallel systems (I/O still needs performance improvements) • Optimization of forecast quality still ongoing • Tests with own 3D-Var data assimilation have started recently. Daniel Reinert – 12.09.2013

  20. Thankyouforyourattention !!

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