The page documents a two python utility 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.
Analyze single E3SM mapping file:
From https://github.com/mt5555/remap-ncl , one needs “mfa.py”, “test_fields.py” and “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 extract 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:
| Code Block |
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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 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 not computed because “bilin” maps often dont include the needed cell area. 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.
Analyze entire E3SM case:
The second utillity will examine all mapping files from a working E3SM case by parsing the XML files after running ./case.setup. It produces a latex file, which can then be processed into a PDF report. The report starts with one page for each unique grid, with some mesh size metrics, a plot of the grid and a plot of the analytic test function (spherical harmonic Y16,32) used to compute map file errors. The report then gives one page for each unique map file, with map algorithm statistics (min and max weights, row sums (consistency) and column sums (conservation)) as well as the L2 and max errors for mapping our test function. For non-global maps (i.e. ocean->atmsphere), the errors are given over the full range of the map (including coastal regions with partial land/ocean fractions) and over the subdomain of 100% land or ocean points (where the maps usually perform better). The map file pages list the important characteristics that should be checked for each map including metrics for conservation, consistency and monotonicity. For ocean maps, plots are included to verify the above properties hold over ocean points and remain well behaved in coastal regions.
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