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maping error for the Y16_32 test function, oEC60to30v3 → ne30pg2

Algorithm

L2 Error

Max Error

ESMF bilin

9.698e-04 

1.931e-03

TR bilin

2.022e-03

2.338e-02

TR intbilin

1.334e-02

1.206e-01

TR aave

l2=41.332e260e-01 02 

91.599e189e-01

Initially Mark Taylor was concerned that the ESMF bilin had significantly lower errors than TR bilin. But this is due to the fact that ESMF bilin map was produced with the “-i” option, which tells ESMF to ignore cells on the atmosphere grid which are not fully covered by cells on the ocean grid. Without the “-i” option, ESMF 8.2.0 would crash with a segfault. ( ESMF can be run with an extrapolation option, which produces results over the entire atmosphere grid, including all land - not looked at here.). Below is a close up of the error (around the UK) when mapping the Y16_32 test function. Examining individual cells, it appears that for cells where ESMF and TR both produce data, the errors are identical.

ESMF bilin

Y16_32 error plot

map_oEC60to30v3_to_ne30pg2_bilin_esmf_error.png

TR bilin

Errors away from coastline identical to ESMF bilin errors

Large errors are at coastlines, where TR bilin is mapping data to cells ignored by ESMF bilin

map_oEC60to30v3_to_ne30pg2_bilin_error.png

TR intbilin

Note that TR’s intbilin does have significantly larger errors as compared to bilin

intbilin remains an excellent algorithm, since:

  • more accurate than ‘aave’

  • monotone

  • built in downsampling (will avoid aliasing errors when mapping from high-res to low-res grids)

    is of interest since it will produce good results when downsampling and upsampling.

    intbilin appears to have similar accuracy as ‘aave’ for this mesh, but the error appears slightly smoother.

    map_oEC60to30v3_to_ne30pg2_intbilin_error.png

    TR aave

    monotone and conservative 1st order flux map

    map_oEC60to30v3_to_ne30pg2_mono_error.pngImage Removedmap_oEC60to30v3_to_ne30pg2_mono_error.pngImage Added