Ship drift

from datetime import datetime
from opendrift.models.shipdrift import ShipDrift

o = ShipDrift(loglevel=20)

o.add_readers_from_list([
    'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml',
    'https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc',
    'https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml'
    ])

16:09:01 INFO    opendrift:579: OpenDriftSimulation initialised (version 1.14.11 / v1.14.12-75-gf9e7122)

Seed ship elements at defined position and time Note: beam/length ratio is larger than allowed, but is then clipped internally

o.seed_elements(lon=5.0, lat=63.0, radius=1000, number=1000,
                time=datetime.now(),
                length=80.0, beam=20.0, height=9.0, draft=4.0)

16:09:01 WARNING opendrift.models.shipdrift:180: Ratio of beam to length should be in range 0.12 to 0.18, given range is 0.25-0.25. Using border value.
16:09:01 INFO    opendrift.models.basemodel.environment:203: Adding a global landmask from GSHHG
16:09:07 INFO    opendrift.models.basemodel.environment:227: Fallback values will be used for the following variables which have no readers:
16:09:07 INFO    opendrift.models.basemodel.environment:230:    horizontal_diffusivity: 100.000000
16:09:07 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
16:09:07 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
16:09:07 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_significant_height: 0.000000
16:09:07 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000

Running model

o.run(steps=24, stop_on_error=True)

16:09:07 INFO    opendrift:1932: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
16:09:07 INFO    opendrift:1932: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
16:09:07 INFO    opendrift:968: Using existing reader for land_binary_mask to move elements to ocean
16:09:07 INFO    opendrift:1000: All points are in ocean
16:09:07 INFO    opendrift:2248: 2026-11-12 16:09:01.041743 - step 1 of 24 - 1000 active elements (0 deactivated)
16:09:07 INFO    opendrift.readers:67: Opening file with xr.open_dataset
16:09:14 INFO    opendrift.readers.reader_netCDF_CF_generic:340: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}
16:09:14 INFO    opendrift.readers:67: Opening file with xr.open_dataset
16:09:15 INFO    opendrift.readers.reader_netCDF_CF_generic:340: Detected dimensions: {'time': 'time', 'x': 'x', 'y': 'y'}
16:09:15 INFO    opendrift.readers:67: Opening file with xr.open_dataset
16:10:02 INFO    opendrift.readers.reader_netCDF_CF_generic:340: Detected dimensions: {'y': 'rlat', 'x': 'rlon', 'time': 'time'}
16:10:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:07 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:07 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:11 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:11 INFO    opendrift:2248: 2026-11-12 17:09:01.041743 - step 2 of 24 - 1000 active elements (0 deactivated)
16:10:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:18 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:18 INFO    opendrift:2248: 2026-11-12 18:09:01.041743 - step 3 of 24 - 1000 active elements (0 deactivated)
16:10:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:23 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:23 INFO    opendrift:2248: 2026-11-12 19:09:01.041743 - step 4 of 24 - 1000 active elements (0 deactivated)
16:10:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:28 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:28 INFO    opendrift:2248: 2026-11-12 20:09:01.041743 - step 5 of 24 - 1000 active elements (0 deactivated)
16:10:31 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:31 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:32 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:32 INFO    opendrift:2248: 2026-11-12 21:09:01.041743 - step 6 of 24 - 1000 active elements (0 deactivated)
16:10:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:36 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:36 INFO    opendrift:2248: 2026-11-12 22:09:01.041743 - step 7 of 24 - 1000 active elements (0 deactivated)
16:10:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:41 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:41 INFO    opendrift:2248: 2026-11-12 23:09:01.041743 - step 8 of 24 - 1000 active elements (0 deactivated)
16:10:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:47 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:47 INFO    opendrift:2248: 2026-11-13 00:09:01.041743 - step 9 of 24 - 1000 active elements (0 deactivated)
16:10:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:51 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:51 INFO    opendrift:2248: 2026-11-13 01:09:01.041743 - step 10 of 24 - 1000 active elements (0 deactivated)
16:10:54 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:54 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:55 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:55 INFO    opendrift:2248: 2026-11-13 02:09:01.041743 - step 11 of 24 - 1000 active elements (0 deactivated)
16:10:58 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:58 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:10:59 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:10:59 INFO    opendrift:2248: 2026-11-13 03:09:01.041743 - step 12 of 24 - 1000 active elements (0 deactivated)
16:11:02 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:02 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:04 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:04 INFO    opendrift:2248: 2026-11-13 04:09:01.041743 - step 13 of 24 - 1000 active elements (0 deactivated)
16:11:06 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:06 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:08 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:08 INFO    opendrift:2248: 2026-11-13 05:09:01.041743 - step 14 of 24 - 1000 active elements (0 deactivated)
16:11:11 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:11 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:12 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:12 INFO    opendrift:2248: 2026-11-13 06:09:01.041743 - step 15 of 24 - 1000 active elements (0 deactivated)
16:11:15 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:15 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:17 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:17 INFO    opendrift:2248: 2026-11-13 07:09:01.041743 - step 16 of 24 - 1000 active elements (0 deactivated)
16:11:20 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:20 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:22 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:22 INFO    opendrift:2248: 2026-11-13 08:09:01.041743 - step 17 of 24 - 1000 active elements (0 deactivated)
16:11:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:26 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:26 INFO    opendrift:2248: 2026-11-13 09:09:01.041743 - step 18 of 24 - 1000 active elements (0 deactivated)
16:11:29 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:29 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:30 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:30 INFO    opendrift:2248: 2026-11-13 10:09:01.041743 - step 19 of 24 - 1000 active elements (0 deactivated)
16:11:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:36 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:36 INFO    opendrift:2248: 2026-11-13 11:09:01.041743 - step 20 of 24 - 1000 active elements (0 deactivated)
16:11:39 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:39 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:40 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:40 INFO    opendrift:2248: 2026-11-13 12:09:01.041743 - step 21 of 24 - 1000 active elements (0 deactivated)
16:11:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:45 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:45 INFO    opendrift:2248: 2026-11-13 13:09:01.041743 - step 22 of 24 - 1000 active elements (0 deactivated)
16:11:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:50 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:50 INFO    opendrift:2248: 2026-11-13 14:09:01.041743 - step 23 of 24 - 1000 active elements (0 deactivated)
16:11:53 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:53 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:54 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction
16:11:54 INFO    opendrift:2248: 2026-11-13 15:09:01.041743 - step 24 of 24 - 1000 active elements (0 deactivated)
16:11:57 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:57 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
16:11:59 INFO    opendrift.models.shipdrift:310: Using Stokes drift direction as wave direction

<xarray.Dataset> Size: 3MB
Dimensions:                                                                              (
                                                                                          trajectory: 1000,
                                                                                          time: 25)
Coordinates:
  * trajectory                                                                           (trajectory) int64 8kB ...
  * time                                                                                 (time) datetime64[us] 200B ...
Data variables: (12/25)
    status                                                                               (trajectory, time) float32 100kB ...
    moving                                                                               (trajectory, time) float32 100kB ...
    age_seconds                                                                          (trajectory, time) float32 100kB ...
    origin_marker                                                                        (trajectory, time) float32 100kB ...
    lon                                                                                  (trajectory, time) float32 100kB ...
    lat                                                                                  (trajectory, time) float32 100kB ...
    ...                                                                                   ...
    y_sea_water_velocity                                                                 (trajectory, time) float32 100kB ...
    horizontal_diffusivity                                                               (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_x_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_stokes_drift_y_velocity                                             (trajectory, time) float32 100kB ...
    sea_surface_wave_significant_height                                                  (trajectory, time) float32 100kB ...
    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment  (trajectory, time) float32 100kB ...
Attributes: (12/99)
    Conventions:                                                             ...
    standard_name_vocabulary:                                                ...
    featureType:                                                             ...
    title:                                                                   ...
    summary:                                                                 ...
    keywords:                                                                ...
    ...                                                                                                               ...
    geospatial_lon_units:                                                    ...
    geospatial_lon_resolution:                                               ...
    runtime:                                                                 ...
    geospatial_vertical_min:                                                 ...
    geospatial_vertical_max:                                                 ...
    geospatial_vertical_positive:                                            ...

xarray.Dataset

• Dimensions:
  • trajectory: 1000
  • time: 25
• Coordinates: (2)
  • trajectory
    (trajectory)
    int64
    0 1 2 3 4 5 ... 995 996 997 998 999

    cf_role :

    trajectory_id

    dtype :

    <class 'numpy.int32'>

    array([  0,   1,   2, ..., 997, 998, 999], shape=(1000,))

  • time
    (time)
    datetime64[us]
    2026-11-12T16:09:01.041743 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2026-11-12T16:09:01.041743', '2026-11-12T17:09:01.041743',
           '2026-11-12T18:09:01.041743', '2026-11-12T19:09:01.041743',
           '2026-11-12T20:09:01.041743', '2026-11-12T21:09:01.041743',
           '2026-11-12T22:09:01.041743', '2026-11-12T23:09:01.041743',
           '2026-11-13T00:09:01.041743', '2026-11-13T01:09:01.041743',
           '2026-11-13T02:09:01.041743', '2026-11-13T03:09:01.041743',
           '2026-11-13T04:09:01.041743', '2026-11-13T05:09:01.041743',
           '2026-11-13T06:09:01.041743', '2026-11-13T07:09:01.041743',
           '2026-11-13T08:09:01.041743', '2026-11-13T09:09:01.041743',
           '2026-11-13T10:09:01.041743', '2026-11-13T11:09:01.041743',
           '2026-11-13T12:09:01.041743', '2026-11-13T13:09:01.041743',
           '2026-11-13T14:09:01.041743', '2026-11-13T15:09:01.041743',
           '2026-11-13T16:09:01.041743'], dtype='datetime64[us]')

• Data variables: (25)
  • status
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    valid_range :

    [0 0]

    flag_values :

    [0]

    flag_meanings :

    active

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • moving
    (trajectory, time)
    float32
    1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.int32'>

    minval :

    1

    maxval :

    1

    array([[1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(1000, 25), dtype=float32)

  • age_seconds
    (trajectory, time)
    float32
    0.0 3.6e+03 ... 8.28e+04 8.64e+04

    dtype :

    <class 'numpy.float32'>

    units :

    s

    minval :

    0.0

    maxval :

    86400.0

    array([[    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           ...,
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.],
           [    0.,  3600.,  7200., ..., 79200., 82800., 86400.]],
          shape=(1000, 25), dtype=float32)

  • origin_marker
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    unit :

    description :

    An integer kept constant during the simulation. Different values may be used for different seedings, to separate elements during analysis. With GUI, only a single seeding is possible.

    flag_values :

    [0]

    flag_meanings :

    Seed_0

    minval :

    0

    maxval :

    0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • lon
    (trajectory, time)
    float32
    5.035 4.979 4.959 ... 4.786 4.82

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    4.306167

    maxval :

    5.4743013

    array([[5.0348186, 4.9786253, 4.95943  , ..., 4.7125077, 4.7431483,
            4.7663307],
           [5.007899 , 4.952192 , 4.9576445, ..., 4.9027944, 4.9228454,
            4.902842 ],
           [5.0193124, 4.9865956, 4.960671 , ..., 5.0937705, 5.1282835,
            5.166445 ],
           ...,
           [5.0018587, 4.9652576, 4.947213 , ..., 4.953062 , 4.999689 ,
            5.02793  ],
           [4.9773602, 4.9204817, 4.887189 , ..., 4.676903 , 4.7193756,
            4.7729735],
           [4.9929357, 4.952493 , 4.9263663, ..., 4.7873015, 4.7857485,
            4.8204436]], shape=(1000, 25), dtype=float32)

  • lat
    (trajectory, time)
    float32
    63.0 63.01 63.0 ... 62.77 62.76

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    62.728428

    maxval :

    63.03414

    array([[63.004982, 63.009727, 63.003227, ..., 62.840626, 62.85111 ,
            62.843433],
           [63.008007, 63.002327, 62.984352, ..., 62.80765 , 62.809498,
            62.79703 ],
           [62.99621 , 62.98672 , 62.965927, ..., 62.831303, 62.835835,
            62.833256],
           ...,
           [63.001423, 62.990685, 62.977898, ..., 62.84809 , 62.825287,
            62.822044],
           [62.989754, 62.992474, 62.98848 , ..., 62.866158, 62.861004,
            62.869762],
           [62.98824 , 62.970886, 62.962963, ..., 62.762676, 62.766853,
            62.76087 ]], shape=(1000, 25), dtype=float32)

  • z
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    standard_name :

    z

    long_name :

    vertical position

    axis :

    Z

    positive :

    up

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • orientation
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.uint8'>

    units :

    1

    minval :

    0

    maxval :

    1

    array([[0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [0., 0., 0., ..., 0., 0., 0.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(1000, 25), dtype=float32)

  • length
    (trajectory, time)
    float32
    80.0 80.0 80.0 ... 80.0 80.0 80.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    500

    description :

    Length of ship

    level :

    1

    minval :

    80.0

    maxval :

    80.0

    array([[80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           ...,
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.],
           [80., 80., 80., ..., 80., 80., 80.]],
          shape=(1000, 25), dtype=float32)

  • height
    (trajectory, time)
    float32
    9.0 9.0 9.0 9.0 ... 9.0 9.0 9.0 9.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    100

    description :

    Total height of ship (above and below waterline)

    level :

    1

    minval :

    9.0

    maxval :

    9.0

    array([[9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           ...,
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.],
           [9., 9., 9., ..., 9., 9., 9.]], shape=(1000, 25), dtype=float32)

  • draft
    (trajectory, time)
    float32
    4.0 4.0 4.0 4.0 ... 4.0 4.0 4.0 4.0

    dtype :

    <class 'numpy.float32'>

    units :

    m

    min :

    1

    max :

    30

    description :

    Draft of ship (depth below water)

    level :

    1

    minval :

    4.0

    maxval :

    4.0

    array([[4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           ...,
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.],
           [4., 4., 4., ..., 4., 4., 4.]], shape=(1000, 25), dtype=float32)

  • beam
    (trajectory, time)
    float32
    20.0 20.0 20.0 ... 20.0 20.0 20.0

    dtype :

    <class 'numpy.float32'>

    min :

    1

    max :

    70

    units :

    m

    description :

    Beam (width) of ship

    level :

    1

    minval :

    20.0

    maxval :

    20.0

    array([[20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           ...,
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.],
           [20., 20., 20., ..., 20., 20., 20.]],
          shape=(1000, 25), dtype=float32)

  • wind_drag_coeff
    (trajectory, time)
    float32
    0.815 0.815 0.815 ... 0.815 0.815

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    0.815

    maxval :

    0.815

    array([[0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           ...,
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815],
           [0.815, 0.815, 0.815, ..., 0.815, 0.815, 0.815]],
          shape=(1000, 25), dtype=float32)

  • water_drag_coeff
    (trajectory, time)
    float32
    1.32 1.32 1.32 ... 1.32 1.32 1.32

    dtype :

    <class 'numpy.float32'>

    units :

    1

    minval :

    1.32

    maxval :

    1.32

    array([[1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           ...,
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32],
           [1.32, 1.32, 1.32, ..., 1.32, 1.32, 1.32]],
          shape=(1000, 25), dtype=float32)

  • jibeProbability
    (trajectory, time)
    float32
    0.04 0.04 0.04 ... 0.04 0.04 0.04

    dtype :

    <class 'numpy.float32'>

    units :

    1/h

    minval :

    0.04

    maxval :

    0.04

    array([[0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           ...,
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04],
           [0.04, 0.04, 0.04, ..., 0.04, 0.04, 0.04]],
          shape=(1000, 25), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    -4.034 -3.486 ... 6.192 6.192

    minval :

    -7.9897027

    maxval :

    7.089704

    array([[-4.033619  , -3.4858656 , -6.1349516 , ...,  4.4872146 ,
             6.1802955 ,  6.1802955 ],
           [ 1.2305052 ,  0.97720855,  3.3332214 , ...,  4.004324  ,
             3.6045458 ,  3.6045458 ],
           [-4.8982186 , -3.9469473 , -1.2816032 , ...,  0.4755464 ,
             2.1076536 ,  2.1076536 ],
           ...,
           [-1.8733867 , -2.5276937 , -2.214357  , ...,  0.9350833 ,
             0.9565558 ,  0.9565558 ],
           [-5.846977  , -6.9175386 , -6.347185  , ...,  0.26461503,
             0.64425164,  0.64425164],
           [-4.910819  , -2.6251867 , -6.996393  , ...,  1.7533537 ,
             6.192247  ,  6.192247  ]], shape=(1000, 25), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    -5.329 -8.704 ... -3.695 -3.695

    minval :

    -15.437743

    maxval :

    0.1976677

    array([[ -5.3291035,  -8.703574 ,  -6.997218 , ...,  -4.518258 ,
             -2.7057743,  -2.7057743],
           [-10.160727 , -12.879843 , -11.402824 , ...,  -5.117559 ,
             -4.7660203,  -4.7660203],
           [ -6.6677713,  -6.8429904, -10.040913 , ...,  -4.3805137,
             -4.8250437,  -4.8250437],
           ...,
           [-10.620295 ,  -7.817051 ,  -4.875028 , ...,  -6.6174207,
             -5.714722 ,  -5.714722 ],
           [ -7.2713857,  -4.686101 ,  -5.525547 , ...,  -2.5389454,
             -1.0794282,  -1.0794282],
           [-10.5252695,  -8.108609 ,  -9.35395  , ...,  -5.8912454,
             -3.6947129,  -3.6947129]], shape=(1000, 25), dtype=float32)

  • land_binary_mask
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(1000, 25), dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    -0.3485 -0.3352 ... 0.1788 0.1788

    minval :

    -0.3836041

    maxval :

    0.5597193

    array([[-0.34851754, -0.33523905, -0.31647632, ...,  0.28061083,
             0.27423564,  0.27423564],
           [-0.35626212, -0.34809422, -0.3345769 , ...,  0.32894236,
             0.32931992,  0.32931992],
           [-0.3594891 , -0.3461731 , -0.32333693, ...,  0.46448216,
             0.5047872 ,  0.5047872 ],
           ...,
           [-0.36632755, -0.35253894, -0.3348134 , ...,  0.41851345,
             0.40451074,  0.40451074],
           [-0.37525433, -0.35842937, -0.32592475, ...,  0.25238964,
             0.27512035,  0.27512035],
           [-0.3684899 , -0.34422135, -0.319302  , ...,  0.18191394,
             0.17882587,  0.17882587]], shape=(1000, 25), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    0.03396 0.05127 ... 0.2742 0.2742

    minval :

    -0.10008222

    maxval :

    0.38126642

    array([[ 0.03396087,  0.05127012,  0.04275988, ...,  0.23643702,
             0.20898665,  0.20898665],
           [ 0.04716749,  0.04435081,  0.01070542, ...,  0.24093601,
             0.19484277,  0.19484277],
           [ 0.02255264,  0.00356865, -0.02418139, ...,  0.20662957,
             0.14402783,  0.14402783],
           ...,
           [ 0.03792831,  0.01828653,  0.00300076, ...,  0.17476234,
             0.17063592,  0.17063592],
           [ 0.01860383,  0.03201863,  0.03940064, ...,  0.2247399 ,
             0.21434744,  0.21434744],
           [ 0.01314622, -0.01608085, -0.01693305, ...,  0.30565378,
             0.27417985,  0.27417985]], shape=(1000, 25), dtype=float32)

  • horizontal_diffusivity
    (trajectory, time)
    float32
    100.0 100.0 100.0 ... 100.0 100.0

    minval :

    100.0

    maxval :

    100.0

    array([[100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.],
           ...,
           [100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.],
           [100., 100., 100., ..., 100., 100., 100.]],
          shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_x_velocity
    (trajectory, time)
    float32
    -0.02759 -0.02112 ... 0.03187

    minval :

    -0.041148312

    maxval :

    0.042669825

    array([[-0.027592  , -0.02111738, -0.01593422, ...,  0.03389344,
             0.03130249,  0.03130249],
           [-0.02715153, -0.02066827, -0.01519398, ...,  0.03606721,
             0.03259695,  0.03259695],
           [-0.02711613, -0.02027691, -0.01435972, ...,  0.03730898,
             0.03352559,  0.03352559],
           ...,
           [-0.02695693, -0.02026291, -0.01495612, ...,  0.03619412,
             0.03256057,  0.03256057],
           [-0.02608874, -0.02017013, -0.01564468, ...,  0.03441669,
             0.03138351,  0.03138351],
           [-0.02627572, -0.01928925, -0.01429314, ...,  0.03383099,
             0.03186776,  0.03186776]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_y_velocity
    (trajectory, time)
    float32
    -0.1011 -0.09452 ... -0.04652

    minval :

    -0.15041299

    maxval :

    -0.042324446

    array([[-0.1010842 , -0.09452128, -0.08828627, ..., -0.05255569,
            -0.0466746 , -0.0466746 ],
           [-0.10314191, -0.09741063, -0.08973574, ..., -0.05585692,
            -0.04964152, -0.04964152],
           [-0.10330882, -0.09649225, -0.09154712, ..., -0.05802665,
            -0.05218291, -0.05218291],
           ...,
           [-0.10445034, -0.09744305, -0.09093114, ..., -0.056049  ,
            -0.05058518, -0.05058518],
           [-0.10852551, -0.10108206, -0.09433118, ..., -0.05063839,
            -0.04508225, -0.04508225],
           [-0.10720901, -0.10099167, -0.09368105, ..., -0.05134986,
            -0.04651578, -0.04651578]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    2.619 2.59 2.558 ... 1.832 1.832

    minval :

    1.7079046

    maxval :

    2.6889102

    array([[2.6188574, 2.5902753, 2.5581944, ..., 1.8746477, 1.7809484,
            1.7809484],
           [2.636362 , 2.6115794, 2.5626214, ..., 1.8673086, 1.7700719,
            1.7700719],
           [2.6353078, 2.5900683, 2.5569472, ..., 1.8290492, 1.7389677,
            1.7389677],
           ...,
           [2.644492 , 2.6037638, 2.566653 , ..., 1.8194534, 1.7370793,
            1.7370793],
           [2.6626225, 2.632879 , 2.6044443, ..., 1.8759819, 1.7857502,
            1.7857502],
           [2.6531138, 2.6096272, 2.5732288, ..., 1.9171124, 1.8319262,
            1.8319262]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
    (trajectory, time)
    float32
    6.222 6.277 6.327 ... 5.686 5.686

    minval :

    5.3516173

    maxval :

    6.342824

    array([[6.222236 , 6.277364 , 6.3265195, ..., 5.6709204, 5.6536417,
            5.6536417],
           [6.219045 , 6.267468 , 6.3336525, ..., 5.619828 , 5.6102386,
            5.6102386],
           [6.226692 , 6.276534 , 6.3189173, ..., 5.5601597, 5.5491295,
            5.5491295],
           ...,
           [6.2209682, 6.274301 , 6.3256974, ..., 5.579306 , 5.574645 ,
            5.574645 ],
           [6.202503 , 6.25016  , 6.2958493, ..., 5.6699266, 5.6691465,
            5.6691465],
           [6.2085013, 6.2502084, 6.3036013, ..., 5.717258 , 5.686106 ,
            5.686106 ]], shape=(1000, 25), dtype=float32)

• Attributes: (99)

  Conventions :

  CF-1.11, ACDD-1.3

  standard_name_vocabulary :

  CF Standard Name Table v85

  featureType :

  trajectory

  title :

  OpenDrift trajectory simulation

  summary :

  Output from simulation with OpenDrift framework

  keywords :

  trajectory, drift, lagrangian, simulation

  history :

  Created 2026-11-12 16:09:07.612104

  date_created :

  2026-11-12T16:09:07.612117

  source :

  Output from simulation with OpenDrift

  model_url :

  https://github.com/OpenDrift/opendrift

  opendrift_class :

  ShipDrift

  opendrift_module :

  opendrift.models.shipdrift

  readers :

  odict_keys(['LazyReader: https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'LazyReader: https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc', 'LazyReader: https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml', 'global_landmask'])

  time_coverage_start :

  2026-11-12 16:09:01.041743

  time_step_calculation :

  1:00:00

  time_step_output :

  1:00:00

  config_environment:constant:x_wind :

  None

  config_environment:fallback:x_wind :

  None

  config_environment:constant:y_wind :

  None

  config_environment:fallback:y_wind :

  None

  config_environment:constant:land_binary_mask :

  None

  config_environment:fallback:land_binary_mask :

  None

  config_environment:constant:x_sea_water_velocity :

  None

  config_environment:fallback:x_sea_water_velocity :

  None

  config_environment:constant:y_sea_water_velocity :

  None

  config_environment:fallback:y_sea_water_velocity :

  None

  config_environment:constant:horizontal_diffusivity :

  None

  config_environment:fallback:horizontal_diffusivity :

  100

  config_environment:constant:sea_surface_wave_stokes_drift_x_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_x_velocity :

  0

  config_environment:constant:sea_surface_wave_stokes_drift_y_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_y_velocity :

  0

  config_environment:constant:sea_surface_wave_significant_height :

  None

  config_environment:fallback:sea_surface_wave_significant_height :

  0

  config_environment:constant:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  None

  config_environment:fallback:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  0

  config_general:use_auto_landmask :

  True

  config_drift:current_uncertainty :

  0

  config_drift:current_uncertainty_uniform :

  0

  config_drift:max_speed :

  2.0

  config_readers:max_number_of_fails :

  1

  config_general:simulation_name :

  config_general:coastline_action :

  stranding

  config_general:coastline_approximation_precision :

  0.001

  config_general:time_step_minutes :

  60

  config_general:time_step_output_minutes :

  None

  config_seed:ocean_only :

  True

  config_seed:number :

  1

  config_drift:max_age_seconds :

  None

  config_drift:advection_scheme :

  euler

  config_drift:profiles_depth :

  50

  config_drift:wind_uncertainty :

  0

  config_drift:relative_wind :

  False

  config_drift:wind_drift_angle :

  0

  config_drift:deactivate_north_of :

  None

  config_drift:deactivate_south_of :

  None

  config_drift:deactivate_east_of :

  None

  config_drift:deactivate_west_of :

  None

  config_seed:origin_marker :

  0

  config_seed:z :

  0

  config_seed:orientation :

  random

  config_seed:length :

  80

  config_seed:height :

  8

  config_seed:draft :

  4.0

  config_seed:beam :

  10

  config_seed:wind_drag_coeff :

  1

  config_seed:water_drag_coeff :

  1

  config_seed:jibeProbability :

  0.04

  opendrift_version :

  1.14.11

  seed_geojson :

  {"features": [], "type": "FeatureCollection"}

  simulation_time :

  2026-11-12 16:09:07.752023

  reader_x_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_y_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_land_binary_mask :

  ['global_landmask']

  reader_x_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml']

  reader_y_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml']

  reader_horizontal_diffusivity :

  100

  reader_sea_surface_wave_stokes_drift_x_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_stokes_drift_y_velocity :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_significant_height :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  reader_sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  ['https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml']

  time_coverage_end :

  2026-11-13 16:09:01.041743

  time_coverage_duration :

  P1DT0H0M0S

  time_coverage_resolution :

  P0DT1H0M0S

  performance :

  -------------------- Reader performance: -------------------- global_landmask 0:00:00.0 total 0:00:00.0 preparing 0:00:00.0 reading 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml 0:00:54.9 total 0:00:00.0 preparing 0:00:54.9 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc 0:00:18.4 total 0:00:00.0 preparing 0:00:18.4 reading 0:00:00.2 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml 0:00:42.6 total 0:00:00.0 preparing 0:00:42.6 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- Performance: 2:58.6 total time 6.5 configuration 0.1 preparing main loop 0.0 moving elements to ocean 2:51.8 main loop 0.5 updating elements 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  62.728428

  geospatial_lat_max :

  63.03414

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  4.306167

  geospatial_lon_max :

  5.4743013

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:02:58.605054

  geospatial_vertical_min :

  0.0

  geospatial_vertical_max :

  0.0

  geospatial_vertical_positive :

  up

Print and plot results

print(o)
o.plot(linecolor='orientation')
#o.animation(color='orientation', markersize=20, filename="orientation.gif", legend=['left','right'],colorbar=False,cmap='bwr')
o.animation(color='orientation', legend=['left','right'], markersize=20, colorbar=False, cmap='bwr')

===========================
--------------------
Reader performance:
--------------------
global_landmask
 0:00:00.0  total
 0:00:00.0  preparing
 0:00:00.0  reading
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
 0:00:54.9  total
 0:00:00.0  preparing
 0:00:54.9  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
 0:00:18.4  total
 0:00:00.0  preparing
 0:00:18.4  reading
 0:00:00.2  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
 0:00:42.6  total
 0:00:00.0  preparing
 0:00:42.6  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
Performance:
 2:58.6 total time
    6.5 configuration
    0.1 preparing main loop
      0.0 moving elements to ocean
 2:51.8 main loop
      0.5 updating elements
    0.0 cleaning up
--------------------
===========================
Model:  ShipDrift     (OpenDrift version 1.14.11)
        1000 active ShipObject particles  (0 deactivated, 0 scheduled)
-------------------
Environment variables:
  -----
  land_binary_mask
     1) global_landmask
  -----
  x_sea_water_velocity
  y_sea_water_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
  -----
  x_wind
  y_wind
     1) https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
  -----
  sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
  sea_surface_wave_significant_height
  sea_surface_wave_stokes_drift_x_velocity
  sea_surface_wave_stokes_drift_y_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-be.ncml
  -----
Readers not added for the following variables:
  horizontal_diffusivity

Discarded readers:

Time:
        Start: 2026-11-12 16:09:01.041743 UTC
        Present: 2026-11-13 16:09:01.041743 UTC
        Calculation steps: 24 * 1:00:00 - total time: 1 day, 0:00:00
        Output steps: 25 * 1:00:00
===========================

16:12:13 INFO    opendrift:4899: Saving animation to /root/project/docs/source/gallery/animations/example_shipdrift_0.gif...
16:12:22 INFO    opendrift:3307: Time to make animation: 0:00:11.246553