Sample Data

pop-tools provides some sample data through the pop_tools.datasets module.

Where are the sample data files?

The sample data files are downloaded automatically by pooch the first time you load them.

import xarray as xr

import pop_tools

To find which data files are available via pop_tools, you can run the following:

pop_tools.DATASETS.registry_files

['tend_zint_100m_Fe.nc',
 'iron_tracer.nc',
 'daily_surface_potential_temperature.nc',
 'monthly_dissolved_oxygen.nc',
 'cesm_pop_monthly.T62_g17.nc',
 'lateral_fill_np_array_filled_ref.npz',
 'lateral_fill_np_array_tripole_filled_ref.npz',
 'lateral_fill_np_array_tripole_filled_ref.20200818.npz',
 'lateral_fill_np_array_filled_SOR_ref.20200820.npz',
 'lateral_fill_np_array_tripole_filled_SOR_ref.20200820.npz',
 'POP_gx3v7.nc',
 'g.e20.G.TL319_t13.control.001_hfreq.nc',
 'g.e20.G.TL319_t13.control.001_hfreq-coarsen.nc',
 'Pac_POP0.1_JRA_IAF_1993-12-6-test.nc',
 'Pac_grid_pbc_1301x305x62.tx01_62l.2013-07-13.nc',
 'comp-grid.tx9.1v3.20170718.zarr.zip']

Once you know which file you are interested in, you can pass the name to the pop_tools.DATASETS.fetch() function. This function will download the file if it does not exist already on your local system. After the file has been downloaded, the fetch function returns the path:

filepath = pop_tools.DATASETS.fetch('cesm_pop_monthly.T62_g17.nc')
print(filepath)

/home/docs/.pop_tools/data/cesm_pop_monthly.T62_g17.nc

Now, we can pass the file path to the appropriate I/O package for loading the content of the file:

ds = xr.open_dataset(filepath)
ds

<xarray.Dataset>
Dimensions:       (time: 1, z_t: 60, nlat: 384, nlon: 320, lat_aux_grid: 395,
                   d2: 2)
Coordinates:
    TLAT          (nlat, nlon) float64 ...
    TLONG         (nlat, nlon) float64 ...
    ULAT          (nlat, nlon) float64 ...
    ULONG         (nlat, nlon) float64 ...
  * lat_aux_grid  (lat_aux_grid) float32 -79.49 -78.95 -78.42 ... 89.47 90.0
  * time          (time) object 0173-01-01 00:00:00
  * z_t           (z_t) float32 500.0 1.5e+03 2.5e+03 ... 5.125e+05 5.375e+05
Dimensions without coordinates: nlat, nlon, d2
Data variables:
    SALT          (time, z_t, nlat, nlon) float32 ...
    TEMP          (time, z_t, nlat, nlon) float32 ...
    UVEL          (time, z_t, nlat, nlon) float32 ...
    VVEL          (time, z_t, nlat, nlon) float32 ...
    time_bound    (time, d2) object ...
Attributes:
    title:             g.e21.G1850ECOIAF.T62_g17.004
    history:           Sun May 26 14:13:02 2019: ncks -4 -L 9 cesm_pop_monthl...
    Conventions:       CF-1.0; http://www.cgd.ucar.edu/cms/eaton/netcdf/CF-cu...
    time_period_freq:  month_1
    model_doi_url:     https://doi.org/10.5065/D67H1H0V
    contents:          Diagnostic and Prognostic Variables
    source:            CCSM POP2, the CCSM Ocean Component
    revision:          $Id: tavg.F90 90507 2019-01-18 20:54:19Z altuntas@ucar...
    calendar:          All years have exactly  365 days.
    start_time:        This dataset was created on 2019-05-26 at 11:20:07.5
    cell_methods:      cell_methods = time: mean ==> the variable values are ...
    NCO:               netCDF Operators version 4.7.4 (http://nco.sf.net)

xarray.Dataset

• Dimensions:
  • time: 1
  • z_t: 60
  • nlat: 384
  • nlon: 320
  • lat_aux_grid: 395
  • d2: 2
• Coordinates: (7)
  • TLAT
    (nlat, nlon)
    float64
    ...

    long_name :

    array of t-grid latitudes

    units :

    degrees_north

    [122880 values with dtype=float64]

  • TLONG
    (nlat, nlon)
    float64
    ...

    long_name :

    array of t-grid longitudes

    units :

    degrees_east

    [122880 values with dtype=float64]

  • ULAT
    (nlat, nlon)
    float64
    ...

    long_name :

    array of u-grid latitudes

    units :

    degrees_north

    [122880 values with dtype=float64]

  • ULONG
    (nlat, nlon)
    float64
    ...

    long_name :

    array of u-grid longitudes

    units :

    degrees_east

    [122880 values with dtype=float64]

  • lat_aux_grid
    (lat_aux_grid)
    float32
    -79.49 -78.95 -78.42 ... 89.47 90.0

    long_name :

    latitude grid for transport diagnostics

    units :

    degrees_north

    valid_min :

    -79.48815

    valid_max :

    90.0

    array([-79.48815 , -78.952896, -78.418655, ...,  88.948814,  89.47441 ,
            90.      ], dtype=float32)

  • time
    (time)
    object
    0173-01-01 00:00:00

    long_name :

    time

    bounds :

    time_bound

    array([cftime.DatetimeNoLeap(173, 1, 1, 0, 0, 0, 0, has_year_zero=True)],
          dtype=object)

  • z_t
    (z_t)
    float32
    500.0 1.5e+03 ... 5.375e+05

    long_name :

    depth from surface to midpoint of layer

    units :

    centimeters

    positive :

    down

    valid_min :

    500.0

    valid_max :

    537500.0

    array([5.000000e+02, 1.500000e+03, 2.500000e+03, 3.500000e+03, 4.500000e+03,
           5.500000e+03, 6.500000e+03, 7.500000e+03, 8.500000e+03, 9.500000e+03,
           1.050000e+04, 1.150000e+04, 1.250000e+04, 1.350000e+04, 1.450000e+04,
           1.550000e+04, 1.650984e+04, 1.754790e+04, 1.862913e+04, 1.976603e+04,
           2.097114e+04, 2.225783e+04, 2.364088e+04, 2.513702e+04, 2.676542e+04,
           2.854837e+04, 3.051192e+04, 3.268680e+04, 3.510935e+04, 3.782276e+04,
           4.087846e+04, 4.433777e+04, 4.827367e+04, 5.277280e+04, 5.793729e+04,
           6.388626e+04, 7.075633e+04, 7.870025e+04, 8.788252e+04, 9.847059e+04,
           1.106204e+05, 1.244567e+05, 1.400497e+05, 1.573946e+05, 1.764003e+05,
           1.968944e+05, 2.186457e+05, 2.413972e+05, 2.649001e+05, 2.889385e+05,
           3.133405e+05, 3.379793e+05, 3.627670e+05, 3.876452e+05, 4.125768e+05,
           4.375392e+05, 4.625190e+05, 4.875083e+05, 5.125028e+05, 5.375000e+05],
          dtype=float32)

• Data variables: (5)
  • SALT
    (time, z_t, nlat, nlon)
    float32
    ...

    long_name :

    Salinity

    units :

    gram/kilogram

    grid_loc :

    3111

    cell_methods :

    time: mean

    [7372800 values with dtype=float32]

  • TEMP
    (time, z_t, nlat, nlon)
    float32
    ...

    long_name :

    Potential Temperature

    units :

    degC

    grid_loc :

    3111

    cell_methods :

    time: mean

    [7372800 values with dtype=float32]

  • UVEL
    (time, z_t, nlat, nlon)
    float32
    ...

    long_name :

    Velocity in grid-x direction

    units :

    centimeter/s

    grid_loc :

    3221

    cell_methods :

    time: mean

    [7372800 values with dtype=float32]

  • VVEL
    (time, z_t, nlat, nlon)
    float32
    ...

    long_name :

    Velocity in grid-y direction

    units :

    centimeter/s

    grid_loc :

    3221

    cell_methods :

    time: mean

    [7372800 values with dtype=float32]

  • time_bound
    (time, d2)
    object
    ...

    long_name :

    boundaries for time-averaging interval

    [2 values with dtype=object]

• Indexes: (3)
  • lat_aux_grid
    PandasIndex

    PandasIndex(Index([-79.48815155029297, -78.95289611816406, -78.41865539550781,
           -77.88441467285156, -77.35017395019531, -76.81593322753906,
           -76.28169250488281, -75.74745178222656, -75.21321868896484,
            -74.6789779663086,
           ...
            85.26966857910156,  85.79525756835938,  86.32085418701172,
            86.84644317626953,  87.37203979492188,  87.89762878417969,
            88.42322540283203,  88.94881439208984,  89.47441101074219,
                         90.0],
          dtype='float32', name='lat_aux_grid', length=395))

  • time
    PandasIndex

    PandasIndex(CFTimeIndex([0173-01-01 00:00:00],
                dtype='object', length=1, calendar='noleap', freq=None))

  • z_t
    PandasIndex

    PandasIndex(Index([          500.0,          1500.0,          2500.0,          3500.0,
                    4500.0,          5500.0,          6500.0,          7500.0,
                    8500.0,          9500.0,         10500.0,         11500.0,
                   12500.0,         13500.0,         14500.0,         15500.0,
            16509.83984375, 17547.904296875, 18629.126953125,  19766.02734375,
           20971.138671875,    22257.828125,   23640.8828125,    25137.015625,
           26765.419921875, 28548.365234375,    30511.921875, 32686.798828125,
            35109.34765625,  37822.76171875,  40878.46484375,  44337.76953125,
              48273.671875,  52772.80078125,   57937.2890625,  63886.26171875,
              70756.328125,        78700.25,   87882.5234375,   98470.5859375,
             110620.421875,     124456.6875,    140049.71875,   157394.640625,
             176400.328125,   196894.421875,    218645.65625,    241397.15625,
                264900.125,    288938.46875,    313340.46875,    337979.34375,
              362767.03125,     387645.1875,     412576.8125,       437539.25,
              462519.03125,    487508.34375,     512502.8125,        537500.0],
          dtype='float32', name='z_t'))

• Attributes: (12)

  title :

  g.e21.G1850ECOIAF.T62_g17.004

  history :

  Sun May 26 14:13:02 2019: ncks -4 -L 9 cesm_pop_monthly.T62_g17.nc cesm_pop_monthly.T62_g17.nc Sun May 26 14:12:41 2019: ncks -v SALT,TEMP,UVEL,VVEL,lat_aux_grid -O g.e21.G1850ECOIAF.T62_g17.004.pop.h.0172-12.nc cesm_pop_monthly.T62_g17.nc none

  Conventions :

  CF-1.0; http://www.cgd.ucar.edu/cms/eaton/netcdf/CF-current.htm

  time_period_freq :

  month_1

  model_doi_url :

  https://doi.org/10.5065/D67H1H0V

  contents :

  Diagnostic and Prognostic Variables

  source :

  CCSM POP2, the CCSM Ocean Component

  revision :

  $Id: tavg.F90 90507 2019-01-18 20:54:19Z altuntas@ucar.edu $

  calendar :

  All years have exactly 365 days.

  start_time :

  This dataset was created on 2019-05-26 at 11:20:07.5

  cell_methods :

  cell_methods = time: mean ==> the variable values are averaged over the time interval between the previous time coordinate and the current one. cell_methods absent ==> the variable values are at the time given by the current time coordinate.

  NCO :

  netCDF Operators version 4.7.4 (http://nco.sf.net)

%load_ext watermark
%watermark -d -iv -m -g -h

Compiler    : GCC 11.3.0
OS          : Linux
Release     : 5.15.0-1004-aws
Machine     : x86_64
Processor   : x86_64
CPU cores   : 2
Architecture: 64bit

Hostname: build-21213814-project-451810-pop-tools

Git hash: d3c80c0576ae4838c0e04a0157734eb0c977e613

xarray   : 2023.6.0
pop_tools: 2023.3.0.post2+dirty