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

2. ICON – ICOsahedral Nonhydrostatic Model
DWD
MPI
Joint development project of DWD and Max-Planck-Institute for Meteorology for building a next-generation global NWP and climate modelling system
Atmosphere and ocean model
Outline
Project goals
Horizontal grid structure and accompanying problems
ICON NWP physics suite
Selected results
Roadmap and Summary
Daniel Reinert –

3. Primary development goals
Improved conservation properties (at least mass) and consistent tracer transport (tracer air-mass consistency)
Applicability on a wide range of scales from 100 km to  1 km
Scalability and efficiency on massively parallel computer architectures with O(104 +) cores
Local refinement/nesting capability
Horizontal grid with nest over Europe
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)
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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
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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
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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)
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7. Controlling the checkerboard noise
Goal: Eliminate 1st order error
Basic idea: Divergence averaging
I: Compute standard 1st order div
II: Compute divergence estimate based on immediate neighbors (2nd order bilinear interpolation)
III Averaging:
2nd order accurate for isosceles triangles
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8. Example: Baroclinic wave
Jablonowski-Williamson (2006) baroclinic wave test case PS T
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9. Example: Baroclinic wave
Jablonowski-Williamson (2006) baroclinic wave test case PS T
Standard divergence operator
Divergence averaging
div
div
“checkerboard” noise
Daniel Reinert –

10. ICON NWP-physics Process Author Scheme Origin Radiation
Mlawer et al. (1997)
Barker et al. (2002)
RRTM
ECHAM6
Non-orographic gravity wave drag
Scinocca (2003)
Orr, Bechthold et al. (2010)
wave dissipation at critical level
IFS
Cloud cover
Köhler et al. (new development)
diagnostic (later prognostic) PDF
ICON
Microphysics
Doms and Schättler (2004)
Seifert (2010)
prognostic: water vapour, cloud water, cloud ice, rain, snow
COSMO
Saturation adjustment
Blahak (2010)
isochoric adjustment
Convection
Tiedtke (1989)
Bechthold et al. (2008)
mass-flux shallow and deep
Sub-grid scale orographic drag
Lott and Miller (1997)
blocking, GWD
Turbulent transfer / diffusion
Raschendorfer (2001)
prognostic TKE
Soil/surface
Heise and Schrodin (2002)
Mironov and Ritter (2004)
Mironov (2008)
TERRA (tiled + multi-layer snow)
SEAICE
FLAKE(fresh water lake scheme)
GME/COSMO
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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
Empirical
corrections
Radiative transfer
computations
every 30min
downscaling
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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
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13. Flat-MPI performance Recall goal: scalability up to O(104+) cores
time (s)
1024
4096
1024
4096
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)
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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.
ICON40L90
GME40L60
hor. resolution
40 km
vertical levels 90 60
top height
75 km
36 km
analysis data
IFS
Basic requirement for operational use of ICON
ICON must outperform GME in terms of forecast quality/scores
Daniel Reinert –

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 –

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)
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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 –

18. Roadmap towards operational application
Daniel Reinert –

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 –

20. Thank you for your attention !!