Reader boundary

Seeding elements around the border of a ocean model domain (NorKyst800) to demonstrate autmatic transition back and forth with another model covering a larger domain (Topaz).

from datetime import datetime
import numpy as np
from opendrift.readers import reader_netCDF_CF_generic
from opendrift.models.oceandrift import OceanDrift

o = OceanDrift(loglevel=20)  # Set loglevel to 0 for debug information

# Norkyst
reader_norkyst = reader_netCDF_CF_generic.Reader('https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be')

# Topaz
reader_topaz = reader_netCDF_CF_generic.Reader('https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml')

o.add_reader([reader_norkyst, reader_topaz])
o.set_config('environment:fallback:land_binary_mask', 0)
o.set_config('drift:vertical_mixing', False)

12:21:42 INFO    opendrift:568: OpenDriftSimulation initialised (version 1.14.9 / v1.14.9-47-gbdbbf88)
12:21:42 INFO    opendrift.readers:67: Opening file with xr.open_dataset
12:21:43 INFO    opendrift.readers.reader_netCDF_CF_generic:340: Detected dimensions: {'x': 'X', 'y': 'Y', 'z': 'depth', 'time': 'time'}
12:21:43 INFO    opendrift.readers.basereader:178: Variable x_sea_water_velocity will be rotated from eastward_sea_water_velocity
12:21:43 INFO    opendrift.readers.basereader:178: Variable y_sea_water_velocity will be rotated from northward_sea_water_velocity
12:21:43 INFO    opendrift.readers.basereader:178: Variable x_wind will be rotated from eastward_wind
12:21:43 INFO    opendrift.readers.basereader:178: Variable y_wind will be rotated from northward_wind
12:21:43 INFO    opendrift.readers:67: Opening file with xr.open_dataset
12:21:45 INFO    opendrift.readers.reader_netCDF_CF_generic:340: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}

Seeding some particles

lons = np.linspace(5, 8, 50)
lats = np.linspace(69.8, 70.8, 50)
lons, lats = np.meshgrid(lons, lats)

Seed oil elements at defined position and time

o.seed_elements(lons, lats, radius=0, number=2500,
                time=datetime.now())

12:21:45 INFO    opendrift.models.basemodel.environment:203: Adding a global landmask from GSHHG
12:21:49 INFO    opendrift.models.basemodel.environment:227: Fallback values will be used for the following variables which have no readers:
12:21:49 INFO    opendrift.models.basemodel.environment:230:    horizontal_diffusivity: 0.000000
12:21:49 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_significant_height: 0.000000
12:21:49 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
12:21:49 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
12:21:49 INFO    opendrift.models.basemodel.environment:230:    ocean_mixed_layer_thickness: 50.000000

Running model

o.run(steps=16*4, time_step=900, time_step_output=1800)

12:21:49 INFO    opendrift:1894: Skipping environment variable ocean_vertical_diffusivity because of condition ['drift:vertical_mixing', 'is', False]
12:21:49 INFO    opendrift:1894: Skipping environment variable ocean_mixed_layer_thickness because of condition ['drift:vertical_mixing', 'is', False]
12:21:49 INFO    opendrift:1905: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
12:21:49 INFO    opendrift:1905: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
12:21:49 INFO    opendrift:1913: Storing previous values of environment variable sea_surface_height because of condition ['drift:vertical_advection', 'is', True]
12:21:49 INFO    opendrift:947: Using existing reader for land_binary_mask to move elements to ocean
12:21:49 INFO    opendrift:978: All points are in ocean
12:21:49 INFO    opendrift:2202: 2026-05-11 12:21:45.262061 - step 1 of 64 - 2500 active elements (0 deactivated)
12:21:53 INFO    opendrift:2202: 2026-05-11 12:36:45.262061 - step 2 of 64 - 2500 active elements (0 deactivated)
12:21:54 INFO    opendrift:2202: 2026-05-11 12:51:45.262061 - step 3 of 64 - 2500 active elements (0 deactivated)
12:21:54 INFO    opendrift:2202: 2026-05-11 13:06:45.262061 - step 4 of 64 - 2500 active elements (0 deactivated)
12:21:56 INFO    opendrift:2202: 2026-05-11 13:21:45.262061 - step 5 of 64 - 2500 active elements (0 deactivated)
12:21:57 INFO    opendrift:2202: 2026-05-11 13:36:45.262061 - step 6 of 64 - 2500 active elements (0 deactivated)
12:21:58 INFO    opendrift:2202: 2026-05-11 13:51:45.262061 - step 7 of 64 - 2500 active elements (0 deactivated)
12:21:58 INFO    opendrift:2202: 2026-05-11 14:06:45.262061 - step 8 of 64 - 2500 active elements (0 deactivated)
12:22:00 INFO    opendrift:2202: 2026-05-11 14:21:45.262061 - step 9 of 64 - 2500 active elements (0 deactivated)
12:22:01 INFO    opendrift:2202: 2026-05-11 14:36:45.262061 - step 10 of 64 - 2500 active elements (0 deactivated)
12:22:02 INFO    opendrift:2202: 2026-05-11 14:51:45.262061 - step 11 of 64 - 2500 active elements (0 deactivated)
12:22:02 INFO    opendrift:2202: 2026-05-11 15:06:45.262061 - step 12 of 64 - 2500 active elements (0 deactivated)
12:22:04 INFO    opendrift:2202: 2026-05-11 15:21:45.262061 - step 13 of 64 - 2500 active elements (0 deactivated)
12:22:05 INFO    opendrift:2202: 2026-05-11 15:36:45.262061 - step 14 of 64 - 2500 active elements (0 deactivated)
12:22:06 INFO    opendrift:2202: 2026-05-11 15:51:45.262061 - step 15 of 64 - 2500 active elements (0 deactivated)
12:22:06 INFO    opendrift:2202: 2026-05-11 16:06:45.262061 - step 16 of 64 - 2500 active elements (0 deactivated)
12:22:08 INFO    opendrift:2202: 2026-05-11 16:21:45.262061 - step 17 of 64 - 2500 active elements (0 deactivated)
12:22:09 INFO    opendrift:2202: 2026-05-11 16:36:45.262061 - step 18 of 64 - 2500 active elements (0 deactivated)
12:22:10 INFO    opendrift:2202: 2026-05-11 16:51:45.262061 - step 19 of 64 - 2500 active elements (0 deactivated)
12:22:10 INFO    opendrift:2202: 2026-05-11 17:06:45.262061 - step 20 of 64 - 2500 active elements (0 deactivated)
12:22:12 INFO    opendrift:2202: 2026-05-11 17:21:45.262061 - step 21 of 64 - 2500 active elements (0 deactivated)
12:22:13 INFO    opendrift:2202: 2026-05-11 17:36:45.262061 - step 22 of 64 - 2500 active elements (0 deactivated)
12:22:14 INFO    opendrift:2202: 2026-05-11 17:51:45.262061 - step 23 of 64 - 2500 active elements (0 deactivated)
12:22:15 INFO    opendrift:2202: 2026-05-11 18:06:45.262061 - step 24 of 64 - 2500 active elements (0 deactivated)
12:22:17 INFO    opendrift:2202: 2026-05-11 18:21:45.262061 - step 25 of 64 - 2500 active elements (0 deactivated)
12:22:17 INFO    opendrift:2202: 2026-05-11 18:36:45.262061 - step 26 of 64 - 2500 active elements (0 deactivated)
12:22:18 INFO    opendrift:2202: 2026-05-11 18:51:45.262061 - step 27 of 64 - 2500 active elements (0 deactivated)
12:22:19 INFO    opendrift:2202: 2026-05-11 19:06:45.262061 - step 28 of 64 - 2500 active elements (0 deactivated)
12:22:21 INFO    opendrift:2202: 2026-05-11 19:21:45.262061 - step 29 of 64 - 2500 active elements (0 deactivated)
12:22:21 INFO    opendrift:2202: 2026-05-11 19:36:45.262061 - step 30 of 64 - 2500 active elements (0 deactivated)
12:22:22 INFO    opendrift:2202: 2026-05-11 19:51:45.262061 - step 31 of 64 - 2500 active elements (0 deactivated)
12:22:23 INFO    opendrift:2202: 2026-05-11 20:06:45.262061 - step 32 of 64 - 2500 active elements (0 deactivated)
12:22:25 INFO    opendrift:2202: 2026-05-11 20:21:45.262061 - step 33 of 64 - 2500 active elements (0 deactivated)
12:22:25 INFO    opendrift:2202: 2026-05-11 20:36:45.262061 - step 34 of 64 - 2500 active elements (0 deactivated)
12:22:26 INFO    opendrift:2202: 2026-05-11 20:51:45.262061 - step 35 of 64 - 2500 active elements (0 deactivated)
12:22:27 INFO    opendrift:2202: 2026-05-11 21:06:45.262061 - step 36 of 64 - 2500 active elements (0 deactivated)
12:22:29 INFO    opendrift:2202: 2026-05-11 21:21:45.262061 - step 37 of 64 - 2500 active elements (0 deactivated)
12:22:29 INFO    opendrift:2202: 2026-05-11 21:36:45.262061 - step 38 of 64 - 2500 active elements (0 deactivated)
12:22:30 INFO    opendrift:2202: 2026-05-11 21:51:45.262061 - step 39 of 64 - 2500 active elements (0 deactivated)
12:22:31 INFO    opendrift:2202: 2026-05-11 22:06:45.262061 - step 40 of 64 - 2500 active elements (0 deactivated)
12:22:33 INFO    opendrift:2202: 2026-05-11 22:21:45.262061 - step 41 of 64 - 2500 active elements (0 deactivated)
12:22:33 INFO    opendrift:2202: 2026-05-11 22:36:45.262061 - step 42 of 64 - 2500 active elements (0 deactivated)
12:22:34 INFO    opendrift:2202: 2026-05-11 22:51:45.262061 - step 43 of 64 - 2500 active elements (0 deactivated)
12:22:35 INFO    opendrift:2202: 2026-05-11 23:06:45.262061 - step 44 of 64 - 2500 active elements (0 deactivated)
12:22:37 INFO    opendrift:2202: 2026-05-11 23:21:45.262061 - step 45 of 64 - 2500 active elements (0 deactivated)
12:22:37 INFO    opendrift:2202: 2026-05-11 23:36:45.262061 - step 46 of 64 - 2500 active elements (0 deactivated)
12:22:38 INFO    opendrift:2202: 2026-05-11 23:51:45.262061 - step 47 of 64 - 2500 active elements (0 deactivated)
12:22:39 INFO    opendrift:2202: 2026-05-12 00:06:45.262061 - step 48 of 64 - 2500 active elements (0 deactivated)
12:22:41 INFO    opendrift:2202: 2026-05-12 00:21:45.262061 - step 49 of 64 - 2500 active elements (0 deactivated)
12:22:42 INFO    opendrift:2202: 2026-05-12 00:36:45.262061 - step 50 of 64 - 2500 active elements (0 deactivated)
12:22:43 INFO    opendrift:2202: 2026-05-12 00:51:45.262061 - step 51 of 64 - 2500 active elements (0 deactivated)
12:22:43 INFO    opendrift:2202: 2026-05-12 01:06:45.262061 - step 52 of 64 - 2500 active elements (0 deactivated)
12:22:45 INFO    opendrift:2202: 2026-05-12 01:21:45.262061 - step 53 of 64 - 2500 active elements (0 deactivated)
12:22:46 INFO    opendrift:2202: 2026-05-12 01:36:45.262061 - step 54 of 64 - 2500 active elements (0 deactivated)
12:22:47 INFO    opendrift:2202: 2026-05-12 01:51:45.262061 - step 55 of 64 - 2500 active elements (0 deactivated)
12:22:47 INFO    opendrift:2202: 2026-05-12 02:06:45.262061 - step 56 of 64 - 2500 active elements (0 deactivated)
12:22:50 INFO    opendrift:2202: 2026-05-12 02:21:45.262061 - step 57 of 64 - 2500 active elements (0 deactivated)
12:22:50 INFO    opendrift:2202: 2026-05-12 02:36:45.262061 - step 58 of 64 - 2500 active elements (0 deactivated)
12:22:51 INFO    opendrift:2202: 2026-05-12 02:51:45.262061 - step 59 of 64 - 2500 active elements (0 deactivated)
12:22:51 INFO    opendrift:2202: 2026-05-12 03:06:45.262061 - step 60 of 64 - 2500 active elements (0 deactivated)
12:22:54 INFO    opendrift:2202: 2026-05-12 03:21:45.262061 - step 61 of 64 - 2500 active elements (0 deactivated)
12:22:54 INFO    opendrift:2202: 2026-05-12 03:36:45.262061 - step 62 of 64 - 2500 active elements (0 deactivated)
12:22:55 INFO    opendrift:2202: 2026-05-12 03:51:45.262061 - step 63 of 64 - 2500 active elements (0 deactivated)
12:22:55 INFO    opendrift:2202: 2026-05-12 04:06:45.262061 - step 64 of 64 - 2500 active elements (0 deactivated)

<xarray.Dataset> Size: 7MB
Dimensions:                                   (trajectory: 2500, time: 33)
Coordinates:
  * trajectory                                (trajectory) int64 20kB 0 ... 2499
  * time                                      (time) datetime64[ns] 264B 2026...
Data variables: (12/22)
    status                                    (trajectory, time) float32 330kB ...
    moving                                    (trajectory, time) float32 330kB ...
    age_seconds                               (trajectory, time) float32 330kB ...
    origin_marker                             (trajectory, time) float32 330kB ...
    lon                                       (trajectory, time) float32 330kB ...
    lat                                       (trajectory, time) float32 330kB ...
    ...                                        ...
    horizontal_diffusivity                    (trajectory, time) float32 330kB ...
    sea_surface_wave_significant_height       (trajectory, time) float32 330kB ...
    sea_surface_wave_stokes_drift_x_velocity  (trajectory, time) float32 330kB ...
    sea_surface_wave_stokes_drift_y_velocity  (trajectory, time) float32 330kB ...
    sea_floor_depth_below_sea_level           (trajectory, time) float32 330kB ...
    land_binary_mask                          (trajectory, time) float32 330kB ...
Attributes: (12/121)
    Conventions:                                                           CF...
    standard_name_vocabulary:                                              CF...
    featureType:                                                           tr...
    title:                                                                 Op...
    summary:                                                               Ou...
    keywords:                                                              tr...
    ...                                                                    ...
    geospatial_lon_units:                                                  de...
    geospatial_lon_resolution:                                             point
    runtime:                                                               0:...
    geospatial_vertical_min:                                               0.0
    geospatial_vertical_max:                                               0.0
    geospatial_vertical_positive:                                          up

xarray.Dataset

• Dimensions:
  • trajectory: 2500
  • time: 33
• Coordinates: (2)
  • trajectory
    (trajectory)
    int64
    0 1 2 3 4 ... 2496 2497 2498 2499

    cf_role :

    trajectory_id

    dtype :

    <class 'numpy.int32'>

    array([   0,    1,    2, ..., 2497, 2498, 2499], shape=(2500,))

  • time
    (time)
    datetime64[ns]
    2026-05-11T12:21:45.262061 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2026-05-11T12:21:45.262061000', '2026-05-11T12:51:45.262061000',
           '2026-05-11T13:21:45.262061000', '2026-05-11T13:51:45.262061000',
           '2026-05-11T14:21:45.262061000', '2026-05-11T14:51:45.262061000',
           '2026-05-11T15:21:45.262061000', '2026-05-11T15:51:45.262061000',
           '2026-05-11T16:21:45.262061000', '2026-05-11T16:51:45.262061000',
           '2026-05-11T17:21:45.262061000', '2026-05-11T17:51:45.262061000',
           '2026-05-11T18:21:45.262061000', '2026-05-11T18:51:45.262061000',
           '2026-05-11T19:21:45.262061000', '2026-05-11T19:51:45.262061000',
           '2026-05-11T20:21:45.262061000', '2026-05-11T20:51:45.262061000',
           '2026-05-11T21:21:45.262061000', '2026-05-11T21:51:45.262061000',
           '2026-05-11T22:21:45.262061000', '2026-05-11T22:51:45.262061000',
           '2026-05-11T23:21:45.262061000', '2026-05-11T23:51:45.262061000',
           '2026-05-12T00:21:45.262061000', '2026-05-12T00:51:45.262061000',
           '2026-05-12T01:21:45.262061000', '2026-05-12T01:51:45.262061000',
           '2026-05-12T02:21:45.262061000', '2026-05-12T02:51:45.262061000',
           '2026-05-12T03:21:45.262061000', '2026-05-12T03:51:45.262061000',
           '2026-05-12T04:21:45.262061000'], dtype='datetime64[ns]')

• Data variables: (22)
  • 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=(2500, 33), 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=(2500, 33), dtype=float32)

  • age_seconds
    (trajectory, time)
    float32
    0.0 1.8e+03 ... 5.58e+04 5.76e+04

    dtype :

    <class 'numpy.float32'>

    units :

    s

    minval :

    0.0

    maxval :

    57600.0

    array([[    0.,  1800.,  3600., ..., 54000., 55800., 57600.],
           [    0.,  1800.,  3600., ..., 54000., 55800., 57600.],
           [    0.,  1800.,  3600., ..., 54000., 55800., 57600.],
           ...,
           [    0.,  1800.,  3600., ..., 54000., 55800., 57600.],
           [    0.,  1800.,  3600., ..., 54000., 55800., 57600.],
           [    0.,  1800.,  3600., ..., 54000., 55800., 57600.]],
          shape=(2500, 33), 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=(2500, 33), dtype=float32)

  • lon
    (trajectory, time)
    float32
    5.0 4.996 4.991 ... 7.732 7.724

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    4.85294

    maxval :

    8.253415

    array([[5.       , 4.995617 , 4.9910073, ..., 4.9175134, 4.912397 ,
            4.9076123],
           [5.0612245, 5.0570583, 5.0526824, ..., 4.9856343, 4.980694 ,
            4.976081 ],
           [5.122449 , 5.118395 , 5.1141214, ..., 5.053514 , 5.048819 ,
            5.044453 ],
           ...,
           [7.877551 , 7.8692546, 7.8622856, ..., 7.5587344, 7.5509143,
            7.5438676],
           [7.9387755, 7.9321475, 7.9268274, ..., 7.6414576, 7.6335135,
            7.6259427],
           [8.       , 7.99456  , 7.990343 , ..., 7.7408366, 7.7324543,
            7.7237616]], shape=(2500, 33), dtype=float32)

  • lat
    (trajectory, time)
    float32
    69.8 69.8 69.8 ... 70.73 70.73

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    69.7921

    maxval :

    70.88583

    array([[69.8     , 69.79988 , 69.799934, ..., 69.82208 , 69.82298 ,
            69.82408 ],
           [69.8     , 69.79985 , 69.79988 , ..., 69.82137 , 69.82222 ,
            69.823265],
           [69.8     , 69.79984 , 69.79989 , ..., 69.82071 , 69.821495,
            69.82247 ],
           ...,
           [70.8     , 70.800606, 70.80078 , ..., 70.74895 , 70.74388 ,
            70.73816 ],
           [70.8     , 70.800255, 70.80004 , ..., 70.74649 , 70.74144 ,
            70.73581 ],
           [70.8     , 70.80009 , 70.7997  , ..., 70.739296, 70.73386 ,
            70.72806 ]], shape=(2500, 33), 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=(2500, 33), dtype=float32)

  • wind_drift_factor
    (trajectory, time)
    float32
    0.02 0.02 0.02 ... 0.02 0.02 0.02

    dtype :

    <class 'numpy.float32'>

    units :

    1

    description :

    Elements at surface are moved with this fraction of the vind vector, in addition to currents and Stokes drift

    minval :

    0.02

    maxval :

    0.02

    array([[0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           ...,
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02]],
          shape=(2500, 33), dtype=float32)

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

    dtype :

    <class 'numpy.float32'>

    units :

    1

    description :

    Elements are moved with this fraction of the current vector, in addition to currents and Stokes drift

    minval :

    1.0

    maxval :

    1.0

    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=(2500, 33), dtype=float32)

  • terminal_velocity
    (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/s

    description :

    Terminal rise/sinking velocity (buoyancy) in the ocean column

    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=(2500, 33), dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    -0.09227 -0.09793 ... -0.08007

    minval :

    -0.24594238

    maxval :

    0.3273398

    array([[-0.09227265, -0.0979291 , -0.10037775, ..., -0.11093526,
            -0.10442217, -0.10030557],
           [-0.08768491, -0.09303117, -0.09508842, ..., -0.10716525,
            -0.10072437, -0.0966582 ],
           [-0.08527897, -0.09068485, -0.0932234 , ..., -0.1019311 ,
            -0.09543497, -0.09137891],
           ...,
           [-0.07462395, -0.0542976 , -0.03715127, ..., -0.04962316,
            -0.04765007, -0.04963738],
           [-0.04140244, -0.02129238, -0.0056363 , ..., -0.05168569,
            -0.05607879, -0.05937124],
           [-0.01765484,  0.00143572,  0.01499468, ..., -0.05994768,
            -0.07254265, -0.08007334]], shape=(2500, 33), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    -0.01016 0.0003088 ... -0.1934

    minval :

    -0.3983047

    maxval :

    0.31588918

    array([[-0.01015952,  0.00030884,  0.01214568, ...,  0.05232316,
             0.06533112,  0.07099849],
           [-0.01216467, -0.00104387,  0.01184514, ...,  0.04929077,
             0.0618741 ,  0.06730548],
           [-0.01269871, -0.00085194,  0.01335449, ...,  0.04561054,
             0.05763276,  0.06287707],
           ...,
           [-0.0090338 , -0.02298431, -0.0405475 , ..., -0.14876884,
            -0.18129697, -0.19590881],
           [-0.02756091, -0.04444838, -0.06450924, ..., -0.14208922,
            -0.17206724, -0.18514708],
           [-0.03507739, -0.05318118, -0.07417593, ..., -0.16387814,
            -0.18510652, -0.19335186]], shape=(2500, 33), dtype=float32)

  • sea_surface_height
    (trajectory, time)
    float32
    -1.038 -1.051 ... -0.7718 -0.7344

    minval :

    -1.1185799

    maxval :

    -0.24305029

    array([[-1.0383973 , -1.0505219 , -1.0414613 , ..., -0.6761644 ,
            -0.5978228 , -0.55751365],
           [-1.0387341 , -1.0509403 , -1.0419449 , ..., -0.6765771 ,
            -0.59810746, -0.5577398 ],
           [-1.0393349 , -1.0516443 , -1.042727  , ..., -0.6771045 ,
            -0.59850645, -0.5580757 ],
           ...,
           [-1.0558817 , -1.0931904 , -1.1016741 , ..., -0.8272884 ,
            -0.7618033 , -0.72473824],
           [-1.0600117 , -1.0979636 , -1.1067076 , ..., -0.832078  ,
            -0.76642627, -0.7291719 ],
           [-1.0647753 , -1.1028411 , -1.1117799 , ..., -0.8377818 ,
            -0.7718458 , -0.7343922 ]], shape=(2500, 33), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    0.0 0.0 0.0 ... -5.552 -5.09 -5.074

    minval :

    -8.76716

    maxval :

    0.0

    array([[ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           [ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           [ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           ...,
           [-5.0836587, -4.6737413, -4.6021395, ..., -5.7548323, -4.8848944,
            -4.669189 ],
           [-5.0415373, -4.6306944, -4.54939  , ..., -5.681584 , -4.938564 ,
            -4.781286 ],
           [-4.9961653, -4.6201334, -4.527892 , ..., -5.552365 , -5.0898123,
            -5.0740895]], shape=(2500, 33), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    0.0 0.0 0.0 ... -8.544 -8.463

    minval :

    -9.065202

    maxval :

    4.363595

    array([[ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           [ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           [ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           ...,
           [ 2.65675  ,  2.03598  ,  1.5028695, ..., -7.7223425, -8.262978 ,
            -8.315208 ],
           [ 2.52467  ,  1.9334146,  1.4388831, ..., -8.060506 , -8.522335 ,
            -8.531185 ],
           [ 2.3877358,  1.8271487,  1.3632096, ..., -8.3327675, -8.54376  ,
            -8.463486 ]], shape=(2500, 33), dtype=float32)

  • upward_sea_water_velocity
    (trajectory, time)
    float32
    0.0 0.0 0.0 ... 3.776e-05 4.113e-05

    minval :

    -0.00908157

    maxval :

    0.004522767

    array([[ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00, ...,
             0.0000000e+00,  0.0000000e+00,  0.0000000e+00],
           [ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00, ...,
             0.0000000e+00,  0.0000000e+00,  0.0000000e+00],
           [ 0.0000000e+00,  0.0000000e+00,  0.0000000e+00, ...,
             0.0000000e+00,  0.0000000e+00,  0.0000000e+00],
           ...,
           [-2.2748543e-05, -1.2748544e-05, -2.7485441e-06, ...,
             2.3184260e-05,  2.8488525e-05,  3.1065567e-05],
           [-2.2748543e-05, -1.2748544e-05, -2.7485441e-06, ...,
             3.7251455e-05,  4.7251455e-05,  4.9999999e-05],
           [-2.2748543e-05, -1.2748544e-05, -2.7485441e-06, ...,
             2.9679042e-05,  3.7760099e-05,  4.1125728e-05]],
          shape=(2500, 33), dtype=float32)

  • horizontal_diffusivity
    (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=(2500, 33), dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    0.0 0.0 0.0 ... 2.466 2.433 2.395

    minval :

    0.0

    maxval :

    2.7714448

    array([[0.        , 0.        , 0.        , ..., 0.        , 0.        ,
            0.        ],
           [0.        , 0.        , 0.        , ..., 0.        , 0.        ,
            0.        ],
           [0.        , 0.        , 0.        , ..., 0.        , 0.        ,
            0.        ],
           ...,
           [0.80938685, 0.6393312 , 0.57658225, ..., 2.2817154 , 2.266619  ,
            2.2372227 ],
           [0.78205997, 0.61946297, 0.56007636, ..., 2.392403  , 2.3866825 ,
            2.3527884 ],
           [0.7543085 , 0.60722893, 0.55005956, ..., 2.4664886 , 2.4329898 ,
            2.3954735 ]], shape=(2500, 33), dtype=float32)

  • sea_surface_wave_stokes_drift_x_velocity
    (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=(2500, 33), dtype=float32)

  • sea_surface_wave_stokes_drift_y_velocity
    (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=(2500, 33), dtype=float32)

  • sea_floor_depth_below_sea_level
    (trajectory, time)
    float32
    3.238e+03 3.238e+03 ... 2.95e+03

    minval :

    2890.3042

    maxval :

    3245.0366

    array([[3237.6445, 3238.107 , 3238.5894, ..., 3244.3792, 3244.8313,
            3245.0366],
           [3231.7305, 3232.0881, 3232.463 , ..., 3237.1826, 3237.5815,
            3237.7622],
           [3226.8374, 3227.1543, 3227.4858, ..., 3231.155 , 3231.5098,
            3231.6494],
           ...,
           [2909.3318, 2910.2336, 2910.9937, ..., 2966.166 , 2965.2595,
            2964.907 ],
           [2900.6626, 2901.657 , 2902.509 , ..., 2966.6584, 2968.5503,
            2969.2178],
           [2890.7188, 2891.6113, 2892.3667, ..., 2944.8376, 2948.2722,
            2949.8467]], shape=(2500, 33), 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=(2500, 33), dtype=float32)

• Indexes: (2)
  • trajectory
    PandasIndex

    PandasIndex(Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,
           ...
           2490, 2491, 2492, 2493, 2494, 2495, 2496, 2497, 2498, 2499],
          dtype='int64', name='trajectory', length=2500))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2026-05-11 12:21:45.262061', '2026-05-11 12:51:45.262061',
                   '2026-05-11 13:21:45.262061', '2026-05-11 13:51:45.262061',
                   '2026-05-11 14:21:45.262061', '2026-05-11 14:51:45.262061',
                   '2026-05-11 15:21:45.262061', '2026-05-11 15:51:45.262061',
                   '2026-05-11 16:21:45.262061', '2026-05-11 16:51:45.262061',
                   '2026-05-11 17:21:45.262061', '2026-05-11 17:51:45.262061',
                   '2026-05-11 18:21:45.262061', '2026-05-11 18:51:45.262061',
                   '2026-05-11 19:21:45.262061', '2026-05-11 19:51:45.262061',
                   '2026-05-11 20:21:45.262061', '2026-05-11 20:51:45.262061',
                   '2026-05-11 21:21:45.262061', '2026-05-11 21:51:45.262061',
                   '2026-05-11 22:21:45.262061', '2026-05-11 22:51:45.262061',
                   '2026-05-11 23:21:45.262061', '2026-05-11 23:51:45.262061',
                   '2026-05-12 00:21:45.262061', '2026-05-12 00:51:45.262061',
                   '2026-05-12 01:21:45.262061', '2026-05-12 01:51:45.262061',
                   '2026-05-12 02:21:45.262061', '2026-05-12 02:51:45.262061',
                   '2026-05-12 03:21:45.262061', '2026-05-12 03:51:45.262061',
                   '2026-05-12 04:21:45.262061'],
                  dtype='datetime64[ns]', name='time', freq='30min'))

• Attributes: (121)

  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 2026-05-11 12:21:49.324083

  date_created :

  2026-05-11T12:21:49.324094

  source :

  Output from simulation with OpenDrift

  model_url :

  https://github.com/OpenDrift/opendrift

  opendrift_class :

  OceanDrift

  opendrift_module :

  opendrift.models.oceandrift

  readers :

  odict_keys(['https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be', 'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'global_landmask'])

  time_coverage_start :

  2026-05-11 12:21:45.262061

  time_step_calculation :

  0:15:00

  time_step_output :

  0:30:00

  config_environment:constant:x_sea_water_velocity :

  None

  config_environment:fallback:x_sea_water_velocity :

  0

  config_environment:constant:y_sea_water_velocity :

  None

  config_environment:fallback:y_sea_water_velocity :

  0

  config_environment:constant:sea_surface_height :

  None

  config_environment:fallback:sea_surface_height :

  0

  config_environment:constant:x_wind :

  None

  config_environment:fallback:x_wind :

  0

  config_environment:constant:y_wind :

  None

  config_environment:fallback:y_wind :

  0

  config_environment:constant:upward_sea_water_velocity :

  None

  config_environment:fallback:upward_sea_water_velocity :

  0

  config_environment:constant:ocean_vertical_diffusivity :

  None

  config_environment:fallback:ocean_vertical_diffusivity :

  0

  config_environment:constant:horizontal_diffusivity :

  None

  config_environment:fallback:horizontal_diffusivity :

  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_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:ocean_mixed_layer_thickness :

  None

  config_environment:fallback:ocean_mixed_layer_thickness :

  50

  config_environment:constant:sea_floor_depth_below_sea_level :

  None

  config_environment:fallback:sea_floor_depth_below_sea_level :

  10000

  config_environment:constant:land_binary_mask :

  None

  config_environment:fallback:land_binary_mask :

  0.0

  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: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:wind_drift_factor :

  0.02

  config_seed:current_drift_factor :

  1

  config_seed:terminal_velocity :

  0.0

  config_drift:vertical_advection :

  True

  config_drift:vertical_advection_at_surface :

  False

  config_drift:water_column_stretching :

  False

  config_drift:vertical_advection_correction :

  False

  config_drift:vertical_mixing :

  False

  config_drift:vertical_mixing_at_surface :

  False

  config_vertical_mixing:timestep :

  60

  config_vertical_mixing:diffusivitymodel :

  environment

  config_vertical_mixing:background_diffusivity :

  1.2e-05

  config_vertical_mixing:TSprofiles :

  False

  config_drift:wind_drift_depth :

  0.1

  config_drift:stokes_drift :

  True

  config_drift:stokes_drift_profile :

  Phillips

  config_drift:use_tabularised_stokes_drift :

  False

  config_drift:tabularised_stokes_drift_fetch :

  25000

  config_general:seafloor_action :

  lift_to_seafloor

  config_drift:truncate_ocean_model_below_m :

  None

  config_seed:seafloor :

  False

  opendrift_version :

  1.14.9

  seed_geojson :

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

  simulation_time :

  2026-05-11 12:21:49.331428

  reader_x_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be', '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/fou-hi/norkystv3_800m_m00_be', 'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml']

  reader_sea_surface_height :

  ['https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be', 'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml']

  reader_x_wind :

  ['https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be']

  reader_y_wind :

  ['https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be']

  reader_upward_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be']

  reader_horizontal_diffusivity :

  0

  reader_sea_surface_wave_significant_height :

  0

  reader_sea_surface_wave_stokes_drift_x_velocity :

  0

  reader_sea_surface_wave_stokes_drift_y_velocity :

  0

  reader_sea_floor_depth_below_sea_level :

  ['https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be', 'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml']

  reader_land_binary_mask :

  ['global_landmask']

  time_coverage_end :

  2026-05-12 04:21:45.262061

  time_coverage_duration :

  P0DT16H0M0S

  time_coverage_resolution :

  P0DT0H15M0S

  performance :

  -------------------- Reader performance: -------------------- https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be 0:00:28.8 total 0:00:00.0 preparing 0:00:28.4 reading 0:00:00.3 interpolation 0:00:00.0 interpolation_time 0:00:00.3 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml 0:00:38.1 total 0:00:00.0 preparing 0:00:37.9 reading 0:00:00.0 interpolation 0:00:00.0 interpolation_time 0:00:00.1 rotating vectors 0:00:00.0 masking -------------------- global_landmask 0:00:00.0 total 0:00:00.0 preparing 0:00:00.0 reading 0:00:00.0 masking -------------------- Performance: 1:16.1 total time 7.3 configuration 0.0 preparing main loop 0.0 moving elements to ocean 1:08.8 main loop 0.2 updating elements 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  69.7921

  geospatial_lat_max :

  70.88583

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  4.85294

  geospatial_lon_max :

  8.253415

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:01:16.142207

  geospatial_vertical_min :

  0.0

  geospatial_vertical_max :

  0.0

  geospatial_vertical_positive :

  up

Print and plot results

print(o)
o.animation(fast=True)

===========================
--------------------
Reader performance:
--------------------
https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be
 0:00:28.8  total
 0:00:00.0  preparing
 0:00:28.4  reading
 0:00:00.3  interpolation
 0:00:00.0  interpolation_time
 0:00:00.3  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
 0:00:38.1  total
 0:00:00.0  preparing
 0:00:37.9  reading
 0:00:00.0  interpolation
 0:00:00.0  interpolation_time
 0:00:00.1  rotating vectors
 0:00:00.0  masking
--------------------
global_landmask
 0:00:00.0  total
 0:00:00.0  preparing
 0:00:00.0  reading
 0:00:00.0  masking
--------------------
Performance:
 1:16.1 total time
    7.3 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
 1:08.8 main loop
      0.2 updating elements
    0.0 cleaning up
--------------------
===========================
Model:  OceanDrift     (OpenDrift version 1.14.9)
        2500 active Lagrangian3DArray particles  (0 deactivated, 0 scheduled)
-------------------
Environment variables:
  -----
  sea_floor_depth_below_sea_level
  sea_surface_height
  x_sea_water_velocity
  y_sea_water_velocity
     1) https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be
     2) https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
  -----
  upward_sea_water_velocity
  x_wind
  y_wind
     1) https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be
  -----
  land_binary_mask
     1) global_landmask
  -----
Readers not added for the following variables:
  horizontal_diffusivity
  sea_surface_wave_significant_height
  sea_surface_wave_stokes_drift_x_velocity
  sea_surface_wave_stokes_drift_y_velocity

Discarded readers:

Time:
        Start: 2026-05-11 12:21:45.262061 UTC
        Present: 2026-05-12 04:21:45.262061 UTC
        Calculation steps: 64 * 0:15:00 - total time: 16:00:00
        Output steps: 33 * 0:30:00
===========================

12:22:58 WARNING opendrift:2565: Plotting fast. This will make your plots less accurate.
12:22:59 INFO    opendrift:4768: Saving animation to /root/project/docs/source/gallery/animations/example_reader_boundary_0.gif...
12:23:21 INFO    opendrift:3191: Time to make animation: 0:00:23.345146

o.plot(fast=True)

12:23:21 WARNING opendrift:2565: Plotting fast. This will make your plots less accurate.

(<GeoAxes: title={'center': 'OpenDrift - OceanDrift\n2026-05-11 12:21 to 2026-05-12 04:21 UTC (33 steps)'}>, <Figure size 952.576x1100 with 1 Axes>)