Missing data at longitude edges about asc_and_heat_transport HOT 10 OPEN

Hi Fabio

Doesn't np.arange skips the last instance of the count? perhaps the second argument of the np.arange should be something like u_along_da_seasons_masked.lon[-1]+(lon_bin/2)

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Hi! Even tho the midpoints are 0.25deg apart, the first binning process have a bin width of 3 degs. so -278.5 mid_point covers [-280 -277]. So the westernmost corner should be covered.....

on another note..... Im not sure tho why the last bin ends on 78.25 instead of 78.5 tho, ... let me check and return the answer

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I see - I'm happy to add the halos, or with the idea of changing the weight on the edges!

Although I'm not really sure I understand the issue... if the 20deg lon_bins are defined as in:
for a lon_mid -270, the bin would cover [-280 to -260], wouldn't they have the same amount of points since the edge of the bins are set to the edge of the grid? or am I missing something?

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The 20deg bins weighting assumes a constant number of points per bins (80 in this case). I just checked the counting and it seems this is true for all the bins. Here is the the counting of number of gridpoints per bin (row) per regime (columns):

array([[80., 0., 0.],
[80., 0., 0.],
[39., 0., 41.],
[39., 0., 41.],
[30., 8., 42.],
[68., 0., 12.],
[80., 0., 0.],
[80., 0., 0.],
[28., 52., 0.],
[ 3., 77., 0.],
[ 0., 80., 0.],
[ 0., 4., 76.],
[55., 0., 25.],
[80., 0., 0.],
[80., 0., 0.],
[80., 0., 0.],
[60., 0., 20.]])

However, for 20deg bins we only have 17 bins (I would expect one more, as 360/20 = 18), so I think I missed something there. It seems to me we're ignoring the last eastern bin between 61.5-80° (I'm runnning these again to double-check)...

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Hmm... I'm not sure tbh. This is how I do the binning:

lon_bin=20 #deg
bin_edges = np.arange(u_along_da_seasons_masked.lon[0], u_along_da_seasons_masked.lon[-1], lon_bin)

print(bin_edges)
array([-278.5, -258.5, -238.5, -218.5, -198.5, -178.5, -158.5, -138.5,
       -118.5,  -98.5,  -78.5,  -58.5,  -38.5,  -18.5,    1.5,   21.5,
         41.5,   61.5])

so there's 18 edges but only 17 bins. Then I just do

ds = u_along_da_mean_masked
u_along_da_mean_binned = ds.groupby_bins('lon', bins=bin_edges).mean()

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Ok, I think we can fix that by re-defining the bin_edges and don't limit the max longitude to lon[-1] (which is 78.25°, so it doesn't fit another 20° bin).

If we do that, the counting (for the weighting) shows that the last bin has a total 68 points ([25., 0., 43.], sfc/rev/deep regimes).

Should I proceed to generated the new statistics?

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I finally got to test two different ways to including the last bin missing on previous analyses (with 20deg bins):

• Test 1 defines bin edges between -280 and 80. In this case, the first and last bins have less points (n=74) than the other bins (n=80), so the weights are applied accordingly (i.e., taking in account the max number of points for each bin).

• Test 2: define bin edges between -278.5 and 81.5. Originally the last bin have less gridpoints (n=68) than all the others, but here we applied a halo in the eastern side, repeating the first 12 points on the western side.
  (longitudes are updates so the groupby gets these points on the correct bin; changing from
  lon =[278.5 , -278.25, -278. , -277.75, -277.5 , -277.25, -277. , -276.75, -276.5 , -276.25, -276. , -275.75]
  to:
  lon = [78.5 , 78.75, 79. , 79.25, 79.5 , 79.75, 80. , 80.25, 80.5 , 80.75, 81. , 81.25]).
  This makes the last bin in test 2 (with edges between 61.5-81.5) to have also n=80.

Bottomline is that both tests 1 and 2 have similar results. But they decrease the high r^2 in the deep regime/monthly climatology (from ~0.8 to ~0.6).

I'm posting below the statistics for the 3 tests, where test 3 is the original one (which is missing the last bin, and is what we used in this comparison).

I've generated the new netcdf files with these statistics here:

/g/data/hh5/tmp/access-om/fbd581/ASC_project/statisctic_lonbin/

Test 1:

Test 2:

Test 3

:

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