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aave: Maps which compute a common refinement (intersection) mesh and then integrate a piecewise-constant reconstruction.
pros: conservative, montonone, downscaling
cons: 1st order accurate, not suitable for upscalings (blocky results if source grid resolution << source grid resolution)
bilin: ESMF’s bilinear interpolation
pros: monotone, 2nd order accurate
cons: non-conservative. not suitable for downscaling (aliasing errors if source grid resolution >> target grid resolution )
patch: ESMF’s patch based algorithm (L2 projection?).
pros: accurate. is it downscaling? should be good for upscaling.
cons: can have small non-monotone weights
mono: TR developed algorithms which use a spectral element with monotone basis functions. The degrees of freedom for the basis function (“np”) is usually denoted in the grid name, such as ne30np4. For FV grids, only np=1 is supported.
monoSE2FV: SE monotonic basis reconstruction integrated over FV (np=1) cells
monoSE2SE: projection between source and target grid monotonic reconstructions
monoFV2SE: does this exist?
monoFV2FV: identical to aave, recommend using aave suffix.
pros: conservative, monotone, downscaling.
cons: 1st order accurate
upscaling properties? Probably except for FV source grids.
intbilin: Integrated bilinear. For finite element grids, the shape functions are replaced by a piecewise linear shape functions which are then integrated using a common refinement mesh
pros: monotone, 2nd order, downscaling and upscaling.
cons: only supported for SE2FV? Does it work SE2SE?
inttrilin: Integrated linear reconstruction using triangular grids?
pros: monotone, 2nd order(?), downscaling and upscaling.
cons: does not exist yet!
volumetric: should we add a convention for TR’s volumetric maps?
might be useful for FV->SE maps. currently not used
highorder: Use of SE shape functions or higher order FV for reconstruction, projected onto SE shape functions, or integrated over FV cell (np=1)
The most accurate SE2SE and SE2FV maps.
Currently not recommended due to large negative weights
{algorithm}trn: For any map from gridA to gridB, one can compute an area weighted transpose map from gridB to gradA. In general, the transpose map will not preserve the properties of the original map. However, the transpose of a conservative map will be conservative. The transpose of a monotone conservative map will be monotone and conservative.
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