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fitting an MPIOM curvilinear grid

See original GitHub issue

Has anyone worked with MPIOM/MPIESM ocean in xgcm?

I started to play around with xgcm based on the tutorial. I have a large fx file which has a bunch of variables describing the distance between different parameters of a grid box and a ds with a few variables which are saved on different grids 'x','y' for T and S, and for instance 'x_2','y_2' for u-velocities which is just slightly shifted on the corner of that grid box.

Mostly, I am hoping you guys know someone who got this already work. I tried from xgcm.autogenerate import generate_grid_ds but actually dont yet get the concept of xgcm. Eventually, I want to calculate divergence and budgets (with xgcm). Is this possible with these ds and fx file? Right now, I dont get the grid = Grid(ds) command running as in the tutorials.

timestr='3171*'
ds = xr.open_mfdataset(f'/work/bm1124/m300524/experiments/asp_esmControl_PMassim_3014_T_over_3170/outdata/mpiom/asp_esmControl_PMassim_3014_T_over_3170_mpiom_data_3d_mm_{timestr}.nc')
fx = xr.open_dataset('/work/bm1124/m300524/experiments/asp_esmControl_PMassim_3014_T_over_3170/outdata/mpiom/asp_esmControl_PMassim_3014_T_over_3170_mpiom_fx_31700101_31701231.nc')

for v in fx.data_vars:
    try:
        print(v,'\t',fx[v].attrs['long_name'],fx[v].load().coords,'\n')
    except:
        pass

alatv 	 Latitude at v vector point Coordinates:
    lon      (y, x) float64 -47.37 -47.82 -48.26 -48.68 ... 131.3 132.5 133.8
    lat      (y, x) float64 76.41 76.35 76.29 76.22 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

alonv 	 Longitude at v vector point Coordinates:
    lon      (y, x) float64 -47.37 -47.82 -48.26 -48.68 ... 131.3 132.5 133.8
    lat      (y, x) float64 76.41 76.35 76.29 76.22 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

deptho 	 Depth at pressure point Coordinates:
    lon_2    (y_2, x_2) float64 -47.25 -47.69 -48.12 ... 131.3 132.5 133.8
    lat_2    (y_2, x_2) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

dlxp 	 Grid x distance at pressure point Coordinates:
    lon_2    (y_2, x_2) float64 -47.25 -47.69 -48.12 ... 131.3 132.5 133.8
    lat_2    (y_2, x_2) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

dlyp 	 Grid y distance at pressure point Coordinates:
    lon_2    (y_2, x_2) float64 -47.25 -47.69 -48.12 ... 131.3 132.5 133.8
    lat_2    (y_2, x_2) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

areacello 	 Cell area Coordinates:
    lon_2    (y_2, x_2) float64 -47.25 -47.69 -48.12 ... 131.3 132.5 133.8
    lat_2    (y_2, x_2) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

alatu 	 Latitude at u vector point Coordinates:
    lon_3    (y_3, x_3) float64 -47.48 -47.91 -48.34 ... 131.9 133.2 134.4
    lat_3    (y_3, x_3) float64 76.33 76.27 76.21 76.14 ... -77.32 -77.47 -77.61
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

alonu 	 Longitude at u vector point Coordinates:
    lon_3    (y_3, x_3) float64 -47.48 -47.91 -48.34 ... 131.9 133.2 134.4
    lat_3    (y_3, x_3) float64 76.33 76.27 76.21 76.14 ... -77.32 -77.47 -77.61
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

weto 	 Sea binary mask at pressure point Coordinates:
    lon_2    (y_2, x_2) float64 -47.25 -47.69 -48.12 ... 131.3 132.5 133.8
    lat_2    (y_2, x_2) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth_2  (depth_2) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3170-01-01 00:00:00 

dlxpsi 	 Grid x distance at psi point Coordinates:
    lon_4    (y_4, x_4) float64 -47.36 -47.78 -48.2 -48.61 ... 132.2 133.5 133.5
    lat_4    (y_4, x_4) float64 76.28 76.22 76.16 76.09 ... -77.19 -77.33 -77.33
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

dlypsi 	 Grid y distance at psi point Coordinates:
    lon_4    (y_4, x_4) float64 -47.36 -47.78 -48.2 -48.61 ... 132.2 133.5 133.5
    lat_4    (y_4, x_4) float64 76.28 76.22 76.16 76.09 ... -77.19 -77.33 -77.33
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

dduo 	 Ocean level thickness at u vector point Coordinates:
    lon_3    (y_3, x_3) float64 -47.48 -47.91 -48.34 ... 131.9 133.2 134.4
    lat_3    (y_3, x_3) float64 76.33 76.27 76.21 76.14 ... -77.32 -77.47 -77.61
  * depth_2  (depth_2) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3170-01-01 00:00:00 

dlxu 	 Grid x distance at u vector point Coordinates:
    lon_3    (y_3, x_3) float64 -47.48 -47.91 -48.34 ... 131.9 133.2 134.4
    lat_3    (y_3, x_3) float64 76.33 76.27 76.21 76.14 ... -77.32 -77.47 -77.61
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

dlyu 	 Grid y distance at u vector point Coordinates:
    lon_3    (y_3, x_3) float64 -47.48 -47.91 -48.34 ... 131.9 133.2 134.4
    lat_3    (y_3, x_3) float64 76.33 76.27 76.21 76.14 ... -77.32 -77.47 -77.61
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

ddue 	 Ocean level thickness at v vector point Coordinates:
    lon      (y, x) float64 -47.37 -47.82 -48.26 -48.68 ... 131.3 132.5 133.8
    lat      (y, x) float64 76.41 76.35 76.29 76.22 ... -77.25 -77.39 -77.54
  * depth_2  (depth_2) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3170-01-01 00:00:00 

dlxv 	 Grid x distance at v vector point Coordinates:
    lon      (y, x) float64 -47.37 -47.82 -48.26 -48.68 ... 131.3 132.5 133.8
    lat      (y, x) float64 76.41 76.35 76.29 76.22 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

dlyv 	 Grid y distance at v vector point Coordinates:
    lon      (y, x) float64 -47.37 -47.82 -48.26 -48.68 ... 131.3 132.5 133.8
    lat      (y, x) float64 76.41 76.35 76.29 76.22 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

alat 	 Latitude at pressure point Coordinates:
    lon_2    (y_2, x_2) float64 -47.25 -47.69 -48.12 ... 131.3 132.5 133.8
    lat_2    (y_2, x_2) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

alon 	 Longitude at pressure point Coordinates:
    lon_2    (y_2, x_2) float64 -47.25 -47.69 -48.12 ... 131.3 132.5 133.8
    lat_2    (y_2, x_2) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

ddpo 	 Ocean level thickness at pressure point Coordinates:
    lon_2    (y_2, x_2) float64 -47.25 -47.69 -48.12 ... 131.3 132.5 133.8
    lat_2    (y_2, x_2) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth_2  (depth_2) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3170-01-01 00:00:00 

deuto 	 Depth at u vector point Coordinates:
    lon_3    (y_3, x_3) float64 -47.48 -47.91 -48.34 ... 131.9 133.2 134.4
    lat_3    (y_3, x_3) float64 76.33 76.27 76.21 76.14 ... -77.32 -77.47 -77.61
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

amsue 	 Sea binary mask at v vector point Coordinates:
    lon      (y, x) float64 -47.37 -47.82 -48.26 -48.68 ... 131.3 132.5 133.8
    lat      (y, x) float64 76.41 76.35 76.29 76.22 ... -77.25 -77.39 -77.54
  * depth_2  (depth_2) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3170-01-01 00:00:00 

amsuo 	 Sea binary mask at u vector point Coordinates:
    lon_3    (y_3, x_3) float64 -47.48 -47.91 -48.34 ... 131.9 133.2 134.4
    lat_3    (y_3, x_3) float64 76.33 76.27 76.21 76.14 ... -77.32 -77.47 -77.61
  * depth_2  (depth_2) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3170-01-01 00:00:00 

deute 	 Depth at v vector point Coordinates:
    lon      (y, x) float64 -47.37 -47.82 -48.26 -48.68 ... 131.3 132.5 133.8
    lat      (y, x) float64 76.41 76.35 76.29 76.22 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 0.0
  * time     (time) object 3170-01-01 00:00:00 

thkcello 	 Cell thickness Coordinates:
    lon_2    (y_2, x_2) float64 -47.25 -47.69 -48.12 ... 131.3 132.5 133.8
    lat_2    (y_2, x_2) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth_2  (depth_2) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3170-01-01 00:00:00

for v in ds[['thetao','so','umo','vmo','wmo']].data_vars:
    try:
        print(v,'\t',ds[v].attrs['long_name'],ds[v].load().coords,'\n')
    except:
        pass

thetao 	 Sea water potential temperature Coordinates:
    lon      (y, x) float64 -47.25 -47.69 -48.12 -48.54 ... 131.3 132.5 133.8
    lat      (y, x) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3171-01-31 23:15:00 ... 3171-12-31 23:15:00 

so 	 Sea water salinity Coordinates:
    lon      (y, x) float64 -47.25 -47.69 -48.12 -48.54 ... 131.3 132.5 133.8
    lat      (y, x) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3171-01-31 23:15:00 ... 3171-12-31 23:15:00 

umo 	 Ocean mass x transport Coordinates:
    lon_2    (y_2, x_2) float64 -47.48 -47.91 -48.34 ... 131.9 133.2 134.4
    lat_2    (y_2, x_2) float64 76.33 76.27 76.21 76.14 ... -77.32 -77.47 -77.61
  * depth    (depth) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3171-01-31 23:15:00 ... 3171-12-31 23:15:00 

vmo 	 Ocean mass y transport Coordinates:
    lon_3    (y_3, x_3) float64 -47.37 -47.82 -48.26 ... 131.3 132.5 133.8
    lat_3    (y_3, x_3) float64 76.41 76.35 76.29 76.22 ... -77.25 -77.39 -77.54
  * depth    (depth) float64 6.0 17.0 27.0 37.0 ... 4.67e+03 5.17e+03 5.72e+03
  * time     (time) object 3171-01-31 23:15:00 ... 3171-12-31 23:15:00 

wmo 	 Upward ocean mass transport Coordinates:
    lon      (y, x) float64 -47.25 -47.69 -48.12 -48.54 ... 131.3 132.5 133.8
    lat      (y, x) float64 76.36 76.3 76.24 76.17 ... -77.25 -77.39 -77.54
  * depth_2  (depth_2) float64 0.0 12.0 22.0 32.0 ... 4.92e+03 5.42e+03 6.02e+03
  * time     (time) object 3171-01-31 23:15:00 ... 3171-12-31 23:15:00

The files are quite large. fx is 90MB and 6 variables is ds are 70MB. (Where should I upload them?)

https://github.com/xgcm/xgcm/issues/142

Issue Analytics

State:
Created 4 years ago
Comments:15 (7 by maintainers)

Top GitHub Comments

1reaction

jbuseckecommented, Jun 25, 2021

Absolutely understandable. If you have a skeleton notebook and the data accessible I can also polish it and take care of the PR.

1reaction

aaronspringcommented, Jun 24, 2021

I asked a bit around in our institute. Having different priorities now. But this issue isn’t completely forgotten. Probably it fits the examples better than here

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