The page documents two python utilities to analyze E3SM map files. It checks the the key properties that can be examined by NCO (ncks --checkmapscheck_map), and several additional properties, including consistency with the land/ocean fractions induced by the flux maps.
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From https://github.com/mt5555/remap-ncl , one needs “mfa.py”, “test_fields.py” and (optionally, for plots) “polyplot_hv“plotpoly_mpl.py”. To run the code, one needs to specify the mapfile type (o2a, a2o, l2a, etc…), the mapfile name, the flux map name (needed to compute land/ocean partial cell fractions) and the domain.lnd file (needed to determine lfrin for the caseextract lfrin when analyzing a l2a maps).
Running the code on the l2a map map_r0125_to_ne256pg2_bilin.200212.nc, which is known to produce problems in E3SM simulations, we get:
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% usage: ./mfa.py map_type map_file_name.nc [o2a_flux_map.nc] [domain.lnd.nc] % map_type=a2o, o2a, a2l, l2a, g2g % ocean->atm flux map (needed for a2o, o2a and l2a maps) % domain land file (land fraction, needed for l2a maps python mfa.py l2a \ /lcrc/group/e3sm/data/inputdata/cpl/gridmaps/ne256pg2/map_r0125_to_ne256pg2_bilin.200212.nc \ /lcrc/group/e3sm/data/inputdata/cpl/gridmaps/ne256pg2/map_oRRS18to6v3_to_ne256pg2_nco.200212.nc /lcrc/group/e3sm/data/inputdata/share/domains/domain.lnd.r0125_oRRS18to6v3.200212.nc % output: src grid (bad area) n_a=4147200 dst grid dx min=16.47km max=19.57km area/4pi=1.000 n_b=1572864 o2a flux map: n_a=3693225 n_b=1572864 land domain file: n_a=4147200 map weights: min,max=0.0000000000000 0.9918838095466 rowsums min/max=1.0000000000000 1.0000000000000 skipping colsums due to bad area min,max=0.0000000000000 0.0000000000113 data zeroset-fraction max=0.2970986902642 (990 cells have err>.001) Y16_32 pointwise relative error, full cells: l2=1.708e-05 max=6.337e-05 Y16_32 pointwise relative error, partial cells: l2=1.327e-03 max=1.128e-02 |
For this map, the weights are good (all between 0 and 1), the rowsums are good. The colsums are bad not computed because “bilin” maps often dont include the needed cell area and so these cant be calculated (noted by “bad area” in the source grid). The L2 and max errors are quite low for full land cells (and significantly larger over partial land cells, as expected). The problem with this map is the “zeroset-fraction”: there are 990 partial land cells on the atmosphere grid that dont get any data from the land model with this map. The largest land fraction over such cells in 0.29, resulting in a 29% error in the surface temperature on the atmosphere grid.
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