clouddrift.datasets.glad

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clouddrift.datasets.glad#

clouddrift.datasets.glad(decode_times: bool = True) → Dataset[source]#

Returns the Grand LAgrangian Deployment (GLAD) dataset as a ragged array Xarray dataset.

The function will first look for the ragged-array dataset on the local filesystem. If it is not found, the dataset will be downloaded using the corresponding adapter function and stored for later access.

The upstream data is available at https://doi.org/10.7266/N7VD6WC8.

Parameters#

decode_timesbool, optional

If True, decode the time coordinate into a datetime object. If False, the time coordinate will be an int64 or float64 array of increments since the origin time indicated in the units attribute. Default is True.

Returns#

xarray.Dataset

GLAD dataset as a ragged array

Examples#

>>> from clouddrift.datasets import glad
>>> ds = glad()
>>> ds
<xarray.Dataset>
Dimensions:         (obs: 1602883, traj: 297)
Coordinates:
  time            (obs) datetime64[ns] ...
  id              (traj) object ...
Data variables:
  latitude        (obs) float32 ...
  longitude       (obs) float32 ...
  position_error  (obs) float32 ...
  u               (obs) float32 ...
  v               (obs) float32 ...
  velocity_error  (obs) float32 ...
  rowsize         (traj) int64 ...
Attributes:
  title:        GLAD experiment CODE-style drifter trajectories (low-pass f...
  institution:  Consortium for Advanced Research on Transport of Hydrocarbo...
  source:       CODE-style drifters
  history:      Downloaded from https://data.gulfresearchinitiative.org/dat...
  references:   Özgökmen, Tamay. 2013. GLAD experiment CODE-style drifter t...

Reference#

Özgökmen, Tamay. 2013. GLAD experiment CODE-style drifter trajectories (low-pass filtered, 15 minute interval records), northern Gulf of Mexico near DeSoto Canyon, July-October 2012. Distributed by: Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC), Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7VD6WC8

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