1 / 28

Improvement of the Semi-Lagrangian advection by ‘selective filling diffusion (SFD)'

Improvement of the Semi-Lagrangian advection by ‘selective filling diffusion (SFD)'. WG2-meeting COSMO-GM, Moscow, 06.09.2010 Michael Baldauf (FE13). COSMO-Modell contains several methods for tracer advection: simple centered differences Lin, Rood-scheme

giles
Télécharger la présentation

Improvement of the Semi-Lagrangian advection by ‘selective filling diffusion (SFD)'

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Improvement of the Semi-Lagrangian advection by ‘selective filling diffusion (SFD)' WG2-meeting COSMO-GM, Moscow, 06.09.2010 Michael Baldauf (FE13)

  2. COSMO-Modell contains several methods for tracer advection: • simple centered differences • Lin, Rood-scheme • In particular in combination with Runge-Kutta dynamical core: • Bott-scheme (Finite Volume scheme)+ locally conserving (at least for C<1)- direction splitting of 1D-steps  potential source of instabilities • Semi-Lagrangian-scheme- not locally conserving+ relatively robust- sometimes 'stripe patterns' along coordinate lines occur- in singular points high precipitation values can occur

  3. COSMO-EU '02.05.2010' 0 UTC run 24h-precipitation sum SL with MF

  4. COSMO-EU '02.05.2010' SL with SFD

  5. Semi-Lagrangian-Advection advection eq. (1-dim.) rewritten as ~ step 1: calculation of backward trajectory xjn-1in principle any ODE-solver can be used (here: 2nd order) Staniforth, Côté (1991) MWR Baldauf, Schulz (2004) COSMO-Newsl.

  6. Semi-Lagrangian Advection 2nd step: Interpolation from neighbouring points i,j,k = -1,0 for tri-linear interpol.  8 grid points i,j,k = -2, ...,1 for tri-cubic interpol.  64 grid points x,y,z[0,1] = position in the grid cell (from backtrajectory calculation) qi,j,k = grid point value of q linear weighting polynomials: cubic weighting polynomials:

  7. properties of Semi-Lagrangian advection + unconditionally stable (i.e. no CFL condition, but Lifshitz-condition) + fully multi-dimensional scheme (no directional splitting necessary  quite robust) + increased efficiency if used for many tracers (calculation of backtrajectory only once) + linear scheme, if used without clipping + can be implemented also in unstructured grids + no non-linear instability if used for velocity advection - non-conserving scheme; but for higher order schemes conservation properties are not bad (without clipping):example: tri-cubic interpolation is exactly conserving in the case v=const (and cartesian grid) - multi-cubic interpolation  generates over-/undershoots not positive definite for tracer advection: clipping of negative values necessary; this is a tremendous source of mass = strong violation of conservation (multi-linear interpolation  monotone, but highly diffusive)

  8. 1D-Advection with v=const (CFL=0.6) exact solution cubic interpol. with clipping cubic interpol. without clipping cubic interpol. with SFD

  9. up to now: • Multiplicative Filling (Rood, 1987) SL - MF • clipped values are globally summed and distributed over the whole field • easy • fast • but only global conservation • Problem of reproducibility: • a sum of 'real' (=floating point) numbers is not associative: • (a + b) + c  a + ( b + c ) • solution: a sum of integer numbers is associative map the Real number space to the Integer number space( subroutine sum_DDI( field(:,:) ) in numeric_utilities_rk.f90 ) but this is an unsatisfying solution moreover on massively parallel computers: a global operation is needed

  10. to get closer to local conservation: • fill negative values from positive values from the environment • proposal: Semi-Lagrangian scheme with 'selective filling diffusion' (SFD) • tri-cubic interpolation • artificial 3D-diffusion only in the vicinity of negative values fills up negative values • diffusion itself can be formulated mass-conserving (FV) • diffusion is ‘well-tempered’: only low requirements to the accuracy of the flux calculation,  relativiely efficient • if grid points with negative values remain  clipping PBPV – 03/2010

  11. 1D-Advektion mit v=const (CFL=0.6) exact solution cubic interpol. with clipping cubic interpol. without clipping cubic interpol. with SFD

  12. Idealised advection tests (with prescribed v-field) in the COSMO-Model Initialisierung '3D-Kegel-fkt.' initial distribution: 3D-cone in the following plots: difference against the analytic solution

  13. Test 1: advection with v=const in terrain following grid (CFL=0.107) SL - MF SL- SFD SL - clip Bott

  14. Test 1: advection with v=const in terrain following grid (CFL=0.107) SL with Clipping:5% mass increase! SL with 'SFD':0.2% mass increase Bott: exactly conserving PBPV – 03/2010

  15. Test 2: advection with v=const in terrain following grid (CFL=1.5 SL with clipping: 2.7% mass increase! SL with 'SFD':0.15% mass increase Bott: 0.1% mass increase PBPV – 03/2010

  16. Test 3: Solid body rotation test  = (-3.5, -3.5, 280) * const ( 1 turn around in 2 h) initial field: 3D-cone

  17. Test 3: Solid body rotation test  = (-3.5, -3.5, 280) * const ( 1 turn around in 2 h) SL - MF SL- SFD SL - clip Bott

  18. Test 3: Solid body rotation test  = (-3.5, -3.5, 280) * const ( 1 turn around in 2 h) SL - MF SL- SFD SL - clip Bott

  19. Conservation in the solid body rotation test SL with clipping: 8.5% mass increase! SL with 'SFD'0.7% mass increase Bott: exactly conserving

  20. Test 4: 'LeVeque'-test (initial field: 3D-sphere) SL - MF SL- SFD SL - clip Bott crashed

  21. Synop-Verification: COSMO-EU (7km) 27.07.-27.08.2010 red: SL with SFD blue: SL with MF

  22. Synop-Verification: COSMO-EU (7km) 27.07.-27.08.2010 red: SL with SFD blue: SL with MF

  23. Summary • ‘selective filling diffusion (SFD)’ in the Semi-Lagrangian scheme • improves local conservation properties (if non-negativeness is needed) • often the 'best' scheme in idealised advection experiments • ‘multiplicative filling’ no longer needed (but could be applied afterwards) • improves linear properties of the tracer-advection • synop-verification COSMO-EU (7km) (for 'August 2010'): • small (but probably insignificant) improvements in RMSE • slightly higher biases • in general 'stripe-patterns' and tendency to spots with high precipitation hasnot improved • outlook: • some tuning of the SFD necessary (?) (Thresholds) • Efficiency on vector computers (NEC SXx): • 'diffusion in only a few points' ?  'diffusion everywhere with a lot K=0' ? • tri-cubic interpolation not optimised for the NEC-SX9 (vectorisation degree is 99.8%, but a lot of bank conflicts)

  24. Initialisation '3D-sphere'

More Related