Topography and bathymetry of Southern Africa

This dataset consists in a regular grid with topography and bathymetry over Southern Africa. It was generated by cropping the ETOPO1 global topography grid to the desired area. The topography and bathymetry heights are referenced to sea level (what can be considered as the geoid).

Original source: ETOPO1

Pre-processing: Source code for preparation of the original dataset for redistribution in Ensaio

import pygmt
import xarray as xr

import ensaio

Download and cache the data and return the path to it on disk

fname = ensaio.fetch_southern_africa_topography(version=1)
print(fname)

/home/runner/work/_temp/cache/ensaio/v1/southern-africa-topography.nc

Load the netCDF file with xarray (netcdf4 is required)

data = xr.load_dataarray(fname)
data

<xarray.DataArray 'topography' (latitude: 1182, longitude: 1371)> Size: 13MB
array([[-5039., -5027., -5014., ..., -3846., -3867., -3873.],
       [-5036., -5021., -5007., ..., -3839., -3863., -3872.],
       [-5031., -5016., -5001., ..., -3835., -3860., -3870.],
       ...,
       [-2906., -2901., -2884., ...,   173.,   134.,   118.],
       [-2908., -2906., -2888., ...,   132.,   119.,   118.],
       [-2912., -2910., -2894., ...,   122.,   120.,   128.]])
Coordinates:
  * longitude  (longitude) float64 11kB 10.92 10.93 10.95 ... 33.72 33.73 33.75
  * latitude   (latitude) float64 9kB -36.0 -35.98 -35.97 ... -16.33 -16.32
Attributes:
    Conventions:    CF-1.8
    title:          Topographic and bathymetric height for Southern Africa ob...
    crs:            WGS84
    source:         Downloaded from NOAA website (https://ngdc.noaa.gov/mgg/g...
    license:        public domain
    references:     https://doi.org/10.7289/V5C8276M
    long_name:      topographic height above mean sea level
    standard_name:  height_above_mean_sea_level
    description:    height topography/bathymetry referenced to mean sea level
    units:          m
    actual_range:   [-5685.  3376.]
    noaa_metadata:  Conventions: COARDS/CF-1.0\ntitle: ETOPO1_Ice_g_gmt4.grd\...

xarray.DataArray

'topography'

• latitude: 1182
• longitude: 1371

• -5.039e+03 -5.027e+03 -5.014e+03 -5.006e+03 ... 122.0 120.0 128.0

  array([[-5039., -5027., -5014., ..., -3846., -3867., -3873.],
         [-5036., -5021., -5007., ..., -3839., -3863., -3872.],
         [-5031., -5016., -5001., ..., -3835., -3860., -3870.],
         ...,
         [-2906., -2901., -2884., ...,   173.,   134.,   118.],
         [-2908., -2906., -2888., ...,   132.,   119.,   118.],
         [-2912., -2910., -2894., ...,   122.,   120.,   128.]])

• Coordinates: (2)
  • longitude
    (longitude)
    float64
    10.92 10.93 10.95 ... 33.73 33.75

    long_name :

    longitude

    standard_name :

    longitude

    units :

    degrees_east

    actual_range :

    [10.91666667 33.75 ]

    array([10.916667, 10.933333, 10.95    , ..., 33.716667, 33.733333, 33.75    ])

  • latitude
    (latitude)
    float64
    -36.0 -35.98 ... -16.33 -16.32

    long_name :

    latitude

    standard_name :

    latitude

    units :

    degrees_north

    actual_range :

    [-36. -16.31666667]

    array([-36.      , -35.983333, -35.966667, ..., -16.35    , -16.333333,
           -16.316667])

• Indexes: (2)
  • longitude
    PandasIndex

    PandasIndex(Index([10.916666666666664,  10.93333333333333, 10.949999999999998,
           10.966666666666663,  10.98333333333333, 10.999999999999998,
           11.016666666666664, 11.033333333333331, 11.049999999999997,
           11.066666666666665,
           ...
           33.599999999999994,  33.61666666666667,  33.63333333333333,
                        33.65, 33.666666666666664,  33.68333333333333,
           33.699999999999996,  33.71666666666666,  33.73333333333333,
                        33.75],
          dtype='float64', name='longitude', length=1371))

  • latitude
    PandasIndex

    PandasIndex(Index([ -35.99999999999997, -35.983333333333306,  -35.96666666666664,
           -35.949999999999974,  -35.93333333333331, -35.916666666666636,
            -35.89999999999997, -35.883333333333304,  -35.86666666666664,
            -35.84999999999997,
           ...
            -16.46666666666664,  -16.44999999999997, -16.433333333333305,
            -16.41666666666664, -16.399999999999974, -16.383333333333304,
            -16.36666666666664, -16.349999999999973, -16.333333333333307,
           -16.316666666666638],
          dtype='float64', name='latitude', length=1182))

• Attributes: (12)

  Conventions :

  CF-1.8

  title :

  Topographic and bathymetric height for Southern Africa obtained from ETOPO1 (ice surface)

  crs :

  WGS84

  source :

  Downloaded from NOAA website (https://ngdc.noaa.gov/mgg/global/global.html)

  license :

  public domain

  references :

  https://doi.org/10.7289/V5C8276M

  long_name :

  topographic height above mean sea level

  standard_name :

  height_above_mean_sea_level

  description :

  height topography/bathymetry referenced to mean sea level

  units :

  m

  actual_range :

  [-5685. 3376.]

  noaa_metadata :

  Conventions: COARDS/CF-1.0 title: ETOPO1_Ice_g_gmt4.grd GMT_version: 4.4.0 node_offset: 0

Make a PyGMT map of the topography and bathymetry data

fig = pygmt.Figure()
fig.grdimage(data, cmap="etopo1", projection="M15c")
fig.colorbar(frame='af+l"topography [m]"', position="JCR")
fig.basemap(frame=True)
fig.coast(shorelines="0.1p", area_thresh=1e4)
fig.show()