Regrid MLD from Treguier et al., 2023

This notebook documents the steps needed to regrid the MLD dataset to a nominal 2/3 deg MOM grid (tx2_3).

Treguier, A. M., de Boyer Montégut, C., Bozec, A., Chassignet, E. P., Fox-Kemper, B., McC. Hogg, A., Iovino, D., Kiss, A. E., Le Sommer, J., Li, Y., Lin, P., Lique, C., Liu, H., Serazin, G., Sidorenko, D., Wang, Q., Xu, X., and Yeager, S.: The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies, Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, 2023.

%matplotlib inline

import xarray as xr
import xesmf
import numpy as np
import datetime
import numpy as np
import matplotlib.pyplot as plt

today = datetime.date.today().strftime("%y%m%d")
print(today)

260306

fname = '../../mesh/tx2_3v3_grid.nc'
grd_out = xr.open_dataset(fname).rename({'tlon': 'lon','tlat': 'lat', 'qlon': 'lon_b','qlat': 'lat_b',})
grd_out

<xarray.Dataset> Size: 42MB
Dimensions:  (ny: 480, nx: 540, nxp: 541, nyp: 481)
Dimensions without coordinates: ny, nx, nxp, nyp
Data variables: (12/20)
    lon      (ny, nx) float64 2MB ...
    lat      (ny, nx) float64 2MB ...
    ulon     (ny, nxp) float64 2MB ...
    ulat     (ny, nxp) float64 2MB ...
    vlon     (nyp, nx) float64 2MB ...
    vlat     (nyp, nx) float64 2MB ...
    ...       ...
    tarea    (ny, nx) float64 2MB ...
    tmask    (ny, nx) float64 2MB ...
    angle    (ny, nx) float64 2MB ...
    depth    (ny, nx) float64 2MB ...
    ar       (ny, nx) float64 2MB ...
    egs      (ny, nx) float64 2MB ...
Attributes:
    Description:  CESM MOM6 2/3 degree grid
    Author:       Frank, Fred, Gustavo (gmarques@ucar.edu)
    Created:      2026-03-05T14:49:28.971877
    type:         Glogal 2/3 degree grid file

xarray.Dataset

• Dimensions:
  • ny: 480
  • nx: 540
  • nxp: 541
  • nyp: 481
• Data variables: (20)
  • lon
    (ny, nx)
    float64
    ...

    long_name :

    array of t-grid longitudes

    units :

    degrees_east

    [259200 values with dtype=float64]

  • lat
    (ny, nx)
    float64
    ...

    long_name :

    array of t-grid latitudes

    units :

    degrees_north

    [259200 values with dtype=float64]

  • ulon
    (ny, nxp)
    float64
    ...

    long_name :

    array of u-grid longitudes

    units :

    degrees_east

    [259680 values with dtype=float64]

  • ulat
    (ny, nxp)
    float64
    ...

    long_name :

    array of u-grid latitudes

    units :

    degrees_north

    [259680 values with dtype=float64]

  • vlon
    (nyp, nx)
    float64
    ...

    long_name :

    array of v-grid longitudes

    units :

    degrees_east

    [259740 values with dtype=float64]

  • vlat
    (nyp, nx)
    float64
    ...

    long_name :

    array of v-grid latitudes

    units :

    degrees_north

    [259740 values with dtype=float64]

  • lon_b
    (nyp, nxp)
    float64
    ...

    long_name :

    array of q-grid longitudes

    units :

    degrees_east

    [260221 values with dtype=float64]

  • lat_b
    (nyp, nxp)
    float64
    ...

    long_name :

    array of q-grid latitudes

    units :

    degrees_north

    [260221 values with dtype=float64]

  • dxt
    (ny, nx)
    float64
    ...

    long_name :

    x-distance between u-points, centered at t

    units :

    meters

    [259200 values with dtype=float64]

  • dyt
    (ny, nx)
    float64
    ...

    long_name :

    y-distance between v-points, centered at t

    units :

    meters

    [259200 values with dtype=float64]

  • dxCv
    (ny, nx)
    float64
    ...

    long_name :

    x-distance between q-points, centered at v

    units :

    meters

    [259200 values with dtype=float64]

  • dyCu
    (ny, nx)
    float64
    ...

    long_name :

    y-distance between q-points, centered at u

    units :

    meters

    [259200 values with dtype=float64]

  • dxCu
    (ny, nx)
    float64
    ...

    long_name :

    x-distance between t-points, centered at u

    units :

    meters

    [259200 values with dtype=float64]

  • dyCv
    (ny, nx)
    float64
    ...

    long_name :

    y-distance between t-points, centered at v

    units :

    meters

    [259200 values with dtype=float64]

  • tarea
    (ny, nx)
    float64
    ...

    long_name :

    area of t-cells

    units :

    meters^2

    [259200 values with dtype=float64]

  • tmask
    (ny, nx)
    float64
    ...

    long_name :

    ocean fraction at t-cell centers

    units :

    none

    [259200 values with dtype=float64]

  • angle
    (ny, nx)
    float64
    ...

    long_name :

    angle grid makes with latitude line

    units :

    degrees

    [259200 values with dtype=float64]

  • depth
    (ny, nx)
    float64
    ...

    long_name :

    depth at h points

    units :

    meters

    [259200 values with dtype=float64]

  • ar
    (ny, nx)
    float64
    ...

    long_name :

    grid aspect ratio (dyt/dxt)

    units :

    none

    [259200 values with dtype=float64]

  • egs
    (ny, nx)
    float64
    ...

    long_name :

    grid effective grid spacing

    units :

    degrees

    [259200 values with dtype=float64]

• Attributes: (4)

  Description :

  CESM MOM6 2/3 degree grid

  Author :

  Frank, Fred, Gustavo (gmarques@ucar.edu)

  Created :

  2026-03-05T14:49:28.971877

  type :

  Glogal 2/3 degree grid file

infile = '/glade/campaign/cgd/oce/datasets/obs/mld/deBoyer_2023/mld_dr003_ref10m_v2023.nc'
ds_in = xr.open_dataset(infile, decode_times=False)

ds_in.mld_dr003[0,:].plot(vmin=0, vmax=1000);

# mask bad values
for t in range(len(ds_in.time)):
    tmp = np.nan_to_num(ds_in.mld_dr003[t,:].values, copy=True, posinf=0, neginf=0)
    ds_in['mld_dr003'][t,:,:] = tmp #.where(tmp == tmp).where(tmp>=0).where(tmp<1.0e6)

def regrid_mld(fld, ds_in, ds_out, method='bilinear'):

    regrid = xesmf.Regridder(
        ds_in,
        ds_out,
        method=method,
        periodic=True,
    )
    fld_out = regrid(ds_in[fld])
    return fld_out

ds_out = regrid_mld('mld_dr003', ds_in, grd_out).rename('mld').rename({'nx':'xh', 'ny':'yh'})

mask = grd_out.tmask.rename({'ny':'yh', 'nx':'xh'})

ds_out = ds_out.where(mask == 1)

Visual inspection

Make sure original and remapped plots look similar.

# visual inspection. Make sure original and remapped plots look similar
for t in range(len(ds_in.time)):
  fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(18,4))
  ds_out[t,:,:].plot.pcolormesh(ax=axes[0], vmin=10,vmax=500)
  ds_in['mld_dr003'][t,:,:].where(ds_in.mask == 1).plot.pcolormesh(ax=axes[1], vmin=10,vmax=500)
  axes[0].set_title('Remapped')
  axes[1].set_title('Original grid')
  plt.suptitle('Month ='+ str(t+1))

ds_out.attrs['author'] = 'Gustavo Marques (gmarques@ucar.edu)'
ds_out.attrs['description'] = 'Mixed Layer Depth (MLD) estimated through a threshold value (increase) of surface potential density equals to 0.03 kg/m3 with reference to the surface value taken at 10 m depth (Treguier et al., 2023)'
ds_out.attrs['date'] = today
ds_out.attrs['infile'] = infile
ds_out.attrs['url'] = 'https://github.com/NCAR/tx2_3/mld/deBoyer2023/'
# save
fname = 'deBoyer23_MLD_remapped_to_tx2_3v3_{}.nc'.format(today)
ds_out.to_netcdf(fname)

/glade/u/apps/opt/miniforge/envs/npl-2026a/lib/python3.13/site-packages/dask/config.py:786: FutureWarning: Dask configuration key 'allowed-failures' has been deprecated; please use 'distributed.scheduler.allowed-failures' instead
  warnings.warn(