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Conservative Cascade Remapping for Spherical Grid Interpolation" (83 characters)

This presentation introduces the Cascade Remapping between Spherical Grids (CaRS) method, focusing on higher-order accurate interpolation while maintaining conservation and monotonicity. Details implementation and performance compared to existing methods. Discusses the cubed-sphere latitudes, gnomonic projection, and cascade interpolation algorithm. Summary includes results and conclusions on employing length-based CaRS. Future work explores RLL grid applications. Appendices cover remapping methods and measurement projections. (491 characters)

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Conservative Cascade Remapping for Spherical Grid Interpolation" (83 characters)

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  1. NCAR, SIParCS Student Internship Presentations, Friday 10th August, 2007. Conservative Cascade Remapping between Spherical grids (CaRS) Arunasalam Rahunanthan Department of Mathematics, University of Wyoming.

  2. Introduction • Need for CaRS • For a better higher order method. • For the coupling between different model components data. • Goal • Higher order accurate interpolation of field variables from one spherical grid to another without violating conservation and monotonicity.

  3. Implementation • SCRIP – a conservative remapping procedure on the sphere (Jones, Mon.Wea.Rev, 1999) • Advantage - Great geometric flexibility and capable of handling different types of spherical grids. • Disadvantage – Low order method. • CaRS – a cascade remapping between cubed-sphere grids and the RLL grids • CaRS – area based (Lauritzen & Nair, Mon.Wea.Rev, July 2007) • CaRS performance compared with SCRIP • CaRS – length based • CaRS length based approach compared with CaRS area based approach

  4. Cascade interpolation • Algorithm based on cascade interpolation method developed for semi-Lagrangian advection schemes • A two dimensional interpolation problem split into two one dimensional problems • First sweep - Interpolation from ‘o’ to ‘x’ along the source grid lines • Second sweep – The resulting field interpolated from ‘x’ to • Allows for high-order sub grid cell construction and advanced monotone filters

  5. Cubed-sphere latitudes and longitudes • The entire cubed-sphere grid reconstructed with a family of horizontal and vertical grid lines. • The cubed-sphere latitudes as vertically stacked closed curves (squared patterns) • The cubed-sphere latitudes belts intersected by a set of cubed-sphere longitudes

  6. Gnomonic projection and cubed-sphere grid Gnomonic projection North pole South pole • Great circle arcs are straight lines on gnomonic projection

  7. First sweep Source grid

  8. First sweep Source grid

  9. First sweep Source grid

  10. First sweep Source grid

  11. First sweep Target grid (intermediate grid) Source grid

  12. First sweep Target grid (intermediate grid) Source grid

  13. First sweep Target grid (intermediate grid) Source grid

  14. First sweep Target grid (intermediate grid) Source grid North pole North pole South pole South pole

  15. Second sweep Source grid (intermediate grid)

  16. Second sweep Source grid (intermediate grid)

  17. Second sweep Source grid (intermediate grid)

  18. Second sweep Source grid (intermediate grid) Target grid (cubed-sphere grid)

  19. Second sweep Source grid (intermediate grid) Target grid (cubed-sphere grid)

  20. Second sweep Source grid (intermediate grid) Target grid (cubed-sphere grid)

  21. Fields used for testing CaRS

  22. Results – Mapping from a coarse RLL grid to a fine cubed-sphere grid (a) Field :: Y3216 Reconstruction :: PCM Nc = 130,Nλ= 128, Nµ=64 Length based CaRS Area based CaRS

  23. Results – Mapping from a fine cubed-sphere grid to a coarse RLL grid (b) Field :: Vortex, Reconstruction :: PPM Nc = 130,Nλ= 128, Nµ=64 Length based CaRS Area based CaRS

  24. Results – Mapping between a coarse RLL grid and a fine cubed-sphere grid Nc = 130,Nλ= 128, Nµ=64 (a) Field :: Y3216 ,Mapping :: RLL grid  Cubed-sphere grid (b) Field :: Vortex, Mapping :: Cubed-sphere grid  RLL grid

  25. Conclusions • The length based CaRS is true representation of the one-dimensional remapping and it could be easily employed in more complicated problems. • We need to sacrifice little bit of accuracy while employing the length based CaRS compared to the area based CaRS.

  26. Future works RLL grid RLL grid - longitude RLL grid - latitude Cubed- sphere grid :: top panel • By projecting the spherical grids on a Tangent plane, the lengths will be measured for the cascade remapping. • Area preserving projection. • Both grid lines in unified co-ordinate system.

  27. Appendix A - Remapping between 1D grids • Given source grid and cell average values on source grid remap to target grid. • Reconstruction of sub-grid scale distribution with mass-conservation and monotonicity as constraints. • Piecewise Constant Method (PCoM) • Piecewise Linear Method (PLM) • Piecewise Parabolic Method (PPM) • Piecewise Cubic Method (PCM)

  28. Appendix B - Length measured on different projections Nc = 33,Nλ= 128, Nµ=64 Field = Y3216 , Reconstruction :: PCM First sweep – based on length measured on (λ,µ=sinθ) plane Second sweep – based on length measured on (λ,µ=sinθ) plane First sweep – based on length measured on (λ,θ) plane Second sweep – based on length measured on (λ,θ) plane First sweep – based on arc length Second sweep – based on arc length

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