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'
    ])

10:06:53 INFO    opendrift:568: OpenDriftSimulation initialised (version 1.14.3 / v1.14.3-6-g4ace059)

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)

10:06:53 WARNING opendrift.models.shipdrift:181: Ratio of beam to length should be in range 0.12 to 0.18, given range is 0.25-0.25. Using border value.
10:06:53 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
10:06:58 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
10:06:58 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
10:06:58 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
10:06:58 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_significant_height: 0.000000
10:06:58 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000

Running model

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

10:06:58 INFO    opendrift:1789: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
10:06:58 INFO    opendrift:1789: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
10:06:58 INFO    opendrift:944: Using existing reader for land_binary_mask to move elements to ocean
10:06:58 INFO    opendrift:974: All points are in ocean
10:06:58 INFO    opendrift:2085: 2025-09-18 10:06:53.933031 - step 1 of 24 - 1000 active elements (0 deactivated)
10:06:58 INFO    opendrift.readers:61: Opening file with xr.open_dataset
10:07:00 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}
10:07:00 INFO    opendrift.readers:61: Opening file with xr.open_dataset
10:07:00 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'time': 'time', 'x': 'x', 'y': 'y'}
10:07:00 INFO    opendrift.readers:61: Opening file with xr.open_dataset
10:07:03 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'y': 'rlat', 'x': 'rlon', 'time': 'time'}
10:07:04 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:04 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:04 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:04 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:06 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:06 INFO    opendrift:2085: 2025-09-18 11:06:53.933031 - step 2 of 24 - 1000 active elements (0 deactivated)
10:07:07 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:07 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:08 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:08 INFO    opendrift:2085: 2025-09-18 12:06:53.933031 - step 3 of 24 - 1000 active elements (0 deactivated)
10:07:09 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:09 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:09 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:09 INFO    opendrift:2085: 2025-09-18 13:06:53.933031 - step 4 of 24 - 1000 active elements (0 deactivated)
10:07:10 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:10 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:11 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:11 INFO    opendrift:2085: 2025-09-18 14:06:53.933031 - step 5 of 24 - 1000 active elements (0 deactivated)
10:07:12 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:12 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:13 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:13 INFO    opendrift:2085: 2025-09-18 15:06:53.933031 - step 6 of 24 - 1000 active elements (0 deactivated)
10:07:14 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:14 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:14 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:14 INFO    opendrift:2085: 2025-09-18 16:06:53.933031 - step 7 of 24 - 1000 active elements (0 deactivated)
10:07:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:16 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:16 INFO    opendrift:2085: 2025-09-18 17:06:53.933031 - step 8 of 24 - 1000 active elements (0 deactivated)
10:07:17 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:17 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:18 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:18 INFO    opendrift:2085: 2025-09-18 18:06:53.933031 - step 9 of 24 - 1000 active elements (0 deactivated)
10:07:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:19 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:19 INFO    opendrift:2085: 2025-09-18 19:06:53.933031 - step 10 of 24 - 1000 active elements (0 deactivated)
10:07:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:21 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:21 INFO    opendrift:2085: 2025-09-18 20:06:53.933031 - step 11 of 24 - 1000 active elements (0 deactivated)
10:07:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:23 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:23 INFO    opendrift:2085: 2025-09-18 21:06:53.933031 - step 12 of 24 - 1000 active elements (0 deactivated)
10:07:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:25 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:25 INFO    opendrift:2085: 2025-09-18 22:06:53.933031 - step 13 of 24 - 1000 active elements (0 deactivated)
10:07:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:26 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:26 INFO    opendrift:2085: 2025-09-18 23:06:53.933031 - step 14 of 24 - 1000 active elements (0 deactivated)
10:07:28 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:28 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:29 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:29 INFO    opendrift:2085: 2025-09-19 00:06:53.933031 - step 15 of 24 - 1000 active elements (0 deactivated)
10:07:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:31 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:31 INFO    opendrift:2085: 2025-09-19 01:06:53.933031 - step 16 of 24 - 1000 active elements (0 deactivated)
10:07:32 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:32 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:33 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:33 INFO    opendrift:2085: 2025-09-19 02:06:53.933031 - step 17 of 24 - 1000 active elements (0 deactivated)
10:07:34 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:34 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:35 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:35 INFO    opendrift:2085: 2025-09-19 03:06:53.933031 - step 18 of 24 - 1000 active elements (0 deactivated)
10:07:36 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:36 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:37 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:37 INFO    opendrift:2085: 2025-09-19 04:06:53.933031 - step 19 of 24 - 1000 active elements (0 deactivated)
10:07:38 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:38 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:39 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:39 INFO    opendrift:2085: 2025-09-19 05:06:53.933031 - step 20 of 24 - 1000 active elements (0 deactivated)
10:07:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:41 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:41 INFO    opendrift:2085: 2025-09-19 06:06:53.933031 - step 21 of 24 - 1000 active elements (0 deactivated)
10:07:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:43 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:43 INFO    opendrift:2085: 2025-09-19 07:06:53.933031 - step 22 of 24 - 1000 active elements (0 deactivated)
10:07:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:45 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:45 INFO    opendrift:2085: 2025-09-19 08:06:53.933031 - step 23 of 24 - 1000 active elements (0 deactivated)
10:07:46 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:46 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:47 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction
10:07:47 INFO    opendrift:2085: 2025-09-19 09:06:53.933031 - step 24 of 24 - 1000 active elements (0 deactivated)
10:07:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
10:07:49 INFO    opendrift.models.shipdrift:311: Using Stokes drift direction as wave direction

<xarray.Dataset> Size: 2MB
Dimensions:                                                                              (
                                                                                          trajectory: 1000,
                                                                                          time: 25)
Coordinates:
  * trajectory                                                                           (trajectory) int64 8kB ...
  * time                                                                                 (time) datetime64[ns] 200B ...
Data variables: (12/24)
    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 ...
    ...                                                                                   ...
    x_sea_water_velocity                                                                 (trajectory, time) float32 100kB ...
    y_sea_water_velocity                                                                 (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: (12/96)
    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[ns]
    2025-09-18T10:06:53.933031 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2025-09-18T10:06:53.933031000', '2025-09-18T11:06:53.933031000',
           '2025-09-18T12:06:53.933031000', '2025-09-18T13:06:53.933031000',
           '2025-09-18T14:06:53.933031000', '2025-09-18T15:06:53.933031000',
           '2025-09-18T16:06:53.933031000', '2025-09-18T17:06:53.933031000',
           '2025-09-18T18:06:53.933031000', '2025-09-18T19:06:53.933031000',
           '2025-09-18T20:06:53.933031000', '2025-09-18T21:06:53.933031000',
           '2025-09-18T22:06:53.933031000', '2025-09-18T23:06:53.933031000',
           '2025-09-19T00:06:53.933031000', '2025-09-19T01:06:53.933031000',
           '2025-09-19T02:06:53.933031000', '2025-09-19T03:06:53.933031000',
           '2025-09-19T04:06:53.933031000', '2025-09-19T05:06:53.933031000',
           '2025-09-19T06:06:53.933031000', '2025-09-19T07:06:53.933031000',
           '2025-09-19T08:06:53.933031000', '2025-09-19T09:06:53.933031000',
           '2025-09-19T10:06:53.933031000'], dtype='datetime64[ns]')

• Data variables: (24)
  • 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 5.014 5.034 ... 5.331 5.361

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    4.8170166

    maxval :

    5.619599

    array([[5.0348186, 5.014489 , 5.0339594, ..., 5.0870852, 5.1127725,
            5.1277757],
           [5.007899 , 4.986482 , 5.028743 , ..., 5.422505 , 5.436212 ,
            5.4111834],
           [5.0193124, 5.02953  , 5.045134 , ..., 5.459559 , 5.4742007,
            5.49058  ],
           ...,
           [5.0018587, 5.005481 , 5.0320897, ..., 5.4354935, 5.4639673,
            5.4744887],
           [4.9773602, 4.967345 , 4.9843607, ..., 5.219338 , 5.246696 ,
            5.285708 ],
           [4.9929357, 4.999125 , 5.017297 , ..., 5.332583 , 5.330848 ,
            5.361234 ]], shape=(1000, 25), dtype=float32)

  • lat
    (trajectory, time)
    float32
    63.0 63.03 63.04 ... 63.04 63.03

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    62.886673

    maxval :

    63.31053

    array([[63.004982, 63.028103, 63.041645, ..., 63.144096, 63.160034,
            63.158165],
           [63.008007, 63.023758, 63.02837 , ..., 63.055325, 63.057156,
            63.047867],
           [62.99621 , 63.003994, 63.000053, ..., 62.985367, 62.990444,
            62.99523 ],
           ...,
           [63.001423, 63.011284, 63.01674 , ..., 63.046623, 63.02263 ,
            63.019188],
           [62.989754, 63.011906, 63.022045, ..., 63.166   , 63.164616,
            63.178123],
           [62.98824 , 62.99242 , 63.004242, ..., 63.03941 , 63.03776 ,
            63.02669 ]], 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
    -6.447 -6.071 ... -1.719 -1.719

    minval :

    -10.502217

    maxval :

    8.347746

    array([[-6.447473 , -6.0710425, -6.8520713, ...,  1.4984596,  2.225428 ,
             2.225428 ],
           [-5.879851 , -5.819908 , -5.4026093, ...,  3.533621 ,  4.2589097,
             4.2589097],
           [-5.5608525, -6.346435 , -6.736084 , ...,  3.688123 ,  4.8395605,
             4.8395605],
           ...,
           [-6.828809 , -6.212266 , -6.274232 , ..., -1.6445618, -1.5462422,
            -1.5462422],
           [-6.553261 , -6.8859577, -7.0422354, ..., -2.4666593, -2.3239565,
            -2.3239565],
           [-7.0249677, -6.8911457, -6.2897   , ..., -2.770754 , -1.7185673,
            -1.7185673]], shape=(1000, 25), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    2.084 2.395 1.31 ... 0.446 0.446

    minval :

    -8.137788

    maxval :

    8.823657

    array([[ 2.0842254 ,  2.3948803 ,  1.3104718 , ...,  1.558189  ,
             2.1564023 ,  2.1564023 ],
           [ 2.220009  ,  1.2742833 ,  1.1768909 , ...,  2.8420923 ,
             3.6560383 ,  3.6560383 ],
           [ 0.57508904, -0.31123418, -0.37410647, ...,  2.4798021 ,
             4.952156  ,  4.952156  ],
           ...,
           [ 1.0131531 ,  0.8731764 ,  0.3446664 , ..., -2.267898  ,
            -1.3621976 , -1.3621976 ],
           [ 2.006528  , -1.2158052 ,  0.02786432, ...,  2.0561879 ,
             2.2859209 ,  2.2859209 ],
           [ 1.9803077 ,  1.8552706 ,  0.9808116 , ..., -0.6430834 ,
             0.44601542,  0.44601542]], 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
    0.2835 0.3273 ... 0.2783 0.2783

    minval :

    -0.045409907

    maxval :

    0.4916474

    array([[0.28354567, 0.32728067, 0.35035473, ..., 0.29344967, 0.2611988 ,
            0.2611988 ],
           [0.30496198, 0.35832018, 0.3765896 , ..., 0.22323065, 0.21335696,
            0.21335696],
           [0.3073837 , 0.35099065, 0.39414957, ..., 0.12706307, 0.13348134,
            0.13348134],
           ...,
           [0.32153636, 0.3629949 , 0.39240375, ..., 0.206369  , 0.17250931,
            0.17250931],
           [0.3524203 , 0.39466074, 0.41552976, ..., 0.18977226, 0.20117033,
            0.20117033],
           [0.33783382, 0.38538754, 0.41285637, ..., 0.2797806 , 0.27829143,
            0.27829143]], shape=(1000, 25), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    0.3195 0.3178 ... 0.03276 0.03276

    minval :

    -0.17785582

    maxval :

    0.38715848

    array([[ 0.3194849 ,  0.31782064,  0.30230355, ...,  0.28337044,
             0.27961487,  0.27961487],
           [ 0.3175835 ,  0.309124  ,  0.28829616, ...,  0.00274118,
             0.03072836,  0.03072836],
           [ 0.30153513,  0.291959  ,  0.24964288, ...,  0.01560389,
             0.06848743,  0.06848743],
           ...,
           [ 0.3085121 ,  0.29827544,  0.2742899 , ...,  0.01594023,
             0.05215707,  0.05215707],
           [ 0.29118833,  0.29422143,  0.27631298, ...,  0.24375033,
             0.2553725 ,  0.2553725 ],
           [ 0.2863409 ,  0.26847672,  0.2559156 , ..., -0.0052102 ,
             0.0327643 ,  0.0327643 ]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_x_velocity
    (trajectory, time)
    float32
    -0.01837 -0.01764 ... 0.01406

    minval :

    -0.043334283

    maxval :

    0.019526552

    array([[-0.01836533, -0.01763766, -0.01485763, ...,  0.00509032,
             0.0055273 ,  0.0055273 ],
           [-0.01611903, -0.01543239, -0.01363306, ...,  0.01354379,
             0.01515576,  0.01515576],
           [-0.01595431, -0.01467527, -0.01075315, ...,  0.01417493,
             0.01622898,  0.01622898],
           ...,
           [-0.01475319, -0.01428224, -0.01219453, ...,  0.0138785 ,
             0.01569834,  0.01569834],
           [-0.01378521, -0.01364977, -0.01212439, ...,  0.00441776,
             0.00631905,  0.00631905],
           [-0.0142156 , -0.01278498, -0.01074548, ...,  0.01294927,
             0.01405606,  0.01405606]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_stokes_drift_y_velocity
    (trajectory, time)
    float32
    -0.02646 -0.02567 ... -0.01101

    minval :

    -0.035532013

    maxval :

    0.033069998

    array([[-0.02646018, -0.02567286, -0.02483371, ..., -0.01564204,
            -0.0144108 , -0.0144108 ],
           [-0.02728563, -0.02618694, -0.02498451, ..., -0.01466507,
            -0.01184543, -0.01184543],
           [-0.02684721, -0.0256536 , -0.0250321 , ..., -0.01281455,
            -0.01020026, -0.01020026],
           ...,
           [-0.0274263 , -0.0261982 , -0.02493339, ..., -0.01475236,
            -0.01152141, -0.01152141],
           [-0.02705693, -0.02608451, -0.02535255, ..., -0.0154918 ,
            -0.01391408, -0.01391408],
           [-0.02704336, -0.02590463, -0.02530002, ..., -0.01343222,
            -0.01100569, -0.01100569]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    2.12 2.134 2.154 ... 2.741 2.741

    minval :

    2.0861197

    maxval :

    3.040323

    array([[2.120044 , 2.1340537, 2.1542127, ..., 2.836939 , 2.784755 ,
            2.784755 ],
           [2.1144862, 2.1239035, 2.1508982, ..., 2.8166084, 2.7608764,
            2.7608764],
           [2.1109853, 2.1239886, 2.1387131, ..., 2.8203855, 2.7629392,
            2.7629392],
           ...,
           [2.1091945, 2.121795 , 2.1454566, ..., 2.823625 , 2.7677765,
            2.7677765],
           [2.095513 , 2.1133282, 2.1359634, ..., 2.7899625, 2.740439 ,
            2.740439 ],
           [2.0984433, 2.1085474, 2.1339579, ..., 2.7968903, 2.7406623,
            2.7406623]], shape=(1000, 25), dtype=float32)

  • sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
    (trajectory, time)
    float32
    6.853 6.877 7.0 ... 8.001 8.001

    minval :

    6.811706

    maxval :

    8.566909

    array([[6.8534265, 6.877492 , 6.9997272, ..., 8.1276245, 8.099469 ,
            8.099469 ],
           [6.8752418, 6.9085317, 7.0112233, ..., 8.075791 , 8.000953 ,
            8.000953 ],
           [6.8801217, 6.9235134, 7.051747 , ..., 8.123933 , 8.026135 ,
            8.026135 ],
           ...,
           [6.893407 , 6.923579 , 7.035432 , ..., 8.083757 , 7.999345 ,
            7.999345 ],
           [6.921329 , 6.9346943, 7.0226455, ..., 8.115089 , 8.080936 ,
            8.080936 ],
           [6.908166 , 6.941147 , 7.0442758, ..., 8.066032 , 8.001246 ,
            8.001246 ]], shape=(1000, 25), dtype=float32)

• Indexes: (2)
  • trajectory
    PandasIndex

    PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
           ...
           990, 991, 992, 993, 994, 995, 996, 997, 998, 999],
          dtype='int64', name='trajectory', length=1000))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2025-09-18 10:06:53.933031', '2025-09-18 11:06:53.933031',
                   '2025-09-18 12:06:53.933031', '2025-09-18 13:06:53.933031',
                   '2025-09-18 14:06:53.933031', '2025-09-18 15:06:53.933031',
                   '2025-09-18 16:06:53.933031', '2025-09-18 17:06:53.933031',
                   '2025-09-18 18:06:53.933031', '2025-09-18 19:06:53.933031',
                   '2025-09-18 20:06:53.933031', '2025-09-18 21:06:53.933031',
                   '2025-09-18 22:06:53.933031', '2025-09-18 23:06:53.933031',
                   '2025-09-19 00:06:53.933031', '2025-09-19 01:06:53.933031',
                   '2025-09-19 02:06:53.933031', '2025-09-19 03:06:53.933031',
                   '2025-09-19 04:06:53.933031', '2025-09-19 05:06:53.933031',
                   '2025-09-19 06:06:53.933031', '2025-09-19 07:06:53.933031',
                   '2025-09-19 08:06:53.933031', '2025-09-19 09:06:53.933031',
                   '2025-09-19 10:06:53.933031'],
                  dtype='datetime64[ns]', name='time', freq='h'))

• Attributes: (96)

  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 2025-09-18 10:06:58.325767

  date_created :

  2025-09-18T10:06:58.325775

  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 :

  2025-09-18 10:06:53.933031

  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: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:horizontal_diffusivity :

  100.0

  config_drift:profiles_depth :

  50

  config_drift:wind_uncertainty :

  0

  config_drift:relative_wind :

  False

  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 :

  1.14.3

  seed_geojson :

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

  simulation_time :

  2025-09-18 10:06:58.389901

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

  reader_y_sea_water_velocity :

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

  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 :

  2025-09-19 10:06:53.933031

  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 0:00:15.2 total 0:00:00.0 preparing 0:00:15.1 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 0:00:13.9 total 0:00:00.0 preparing 0:00:13.9 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 0:00:16.0 total 0:00:00.0 preparing 0:00:15.9 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- Performance: 55.7 total time 4.4 configuration 0.0 preparing main loop 0.0 moving elements to ocean 51.3 main loop 0.4 updating elements 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  62.886673

  geospatial_lat_max :

  63.31053

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  4.8170166

  geospatial_lon_max :

  5.619599

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:00:55.789968

  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
 0:00:15.2  total
 0:00:00.0  preparing
 0:00:15.1  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
 0:00:13.9  total
 0:00:00.0  preparing
 0:00:13.9  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
 0:00:16.0  total
 0:00:00.0  preparing
 0:00:15.9  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
Performance:
   55.7 total time
    4.4 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
   51.3 main loop
      0.4 updating elements
    0.0 cleaning up
--------------------
===========================
Model:  ShipDrift     (OpenDrift version 1.14.3)
        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
     2) https://thredds.met.no/thredds/dodsC/cmems/mywavewam3km/dataset-wam-arctic-1hr3km-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

Discarded readers:

Time:
        Start: 2025-09-18 10:06:53.933031 UTC
        Present: 2025-09-19 10:06:53.933031 UTC
        Calculation steps: 24 * 1:00:00 - total time: 1 day, 0:00:00
        Output steps: 25 * 1:00:00
===========================

10:08:02 INFO    opendrift:4612: Saving animation to /root/project/docs/source/gallery/animations/example_shipdrift_0.gif...
10:08:16 INFO    opendrift:3053: Time to make animation: 0:00:14.978925