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)

12:27:17 INFO    opendrift:568: OpenDriftSimulation initialised (version 1.14.9 / v1.14.9-49-gf94e1e5)
12:27:17 INFO    opendrift.readers:67: Opening file with xr.open_dataset
12:27:20 INFO    opendrift.readers.reader_netCDF_CF_generic:340: Detected dimensions: {'x': 'X', 'y': 'Y', 'z': 'depth', 'time': 'time'}
12:27:20 INFO    opendrift.readers.basereader:178: Variable x_sea_water_velocity will be rotated from eastward_sea_water_velocity
12:27:20 INFO    opendrift.readers.basereader:178: Variable y_sea_water_velocity will be rotated from northward_sea_water_velocity
12:27:20 INFO    opendrift.readers.basereader:178: Variable x_wind will be rotated from eastward_wind
12:27:20 INFO    opendrift.readers.basereader:178: Variable y_wind will be rotated from northward_wind
12:27:20 INFO    opendrift.readers:67: Opening file with xr.open_dataset
12:27:24 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())

12:27:24 INFO    opendrift.models.basemodel.environment:203: Adding a global landmask from GSHHG
12:27:28 INFO    opendrift.models.basemodel.environment:227: Fallback values will be used for the following variables which have no readers:
12:27:28 INFO    opendrift.models.basemodel.environment:230:    horizontal_diffusivity: 0.000000
12:27:28 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_significant_height: 0.000000
12:27:28 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
12:27:28 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
12:27:28 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)

12:27:28 INFO    opendrift:1894: Skipping environment variable ocean_vertical_diffusivity because of condition ['drift:vertical_mixing', 'is', False]
12:27:28 INFO    opendrift:1894: Skipping environment variable ocean_mixed_layer_thickness because of condition ['drift:vertical_mixing', 'is', False]
12:27:28 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']))
12:27:28 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']))
12:27:28 INFO    opendrift:1913: Storing previous values of environment variable sea_surface_height because of condition ['drift:vertical_advection', 'is', True]
12:27:28 INFO    opendrift:947: Using existing reader for land_binary_mask to move elements to ocean
12:27:28 INFO    opendrift:978: All points are in ocean
12:27:28 INFO    opendrift:2202: 2026-05-11 12:27:24.650125 - step 1 of 64 - 2500 active elements (0 deactivated)
12:27:33 INFO    opendrift:2202: 2026-05-11 12:42:24.650125 - step 2 of 64 - 2500 active elements (0 deactivated)
12:27:34 INFO    opendrift:2202: 2026-05-11 12:57:24.650125 - step 3 of 64 - 2500 active elements (0 deactivated)
12:27:35 INFO    opendrift:2202: 2026-05-11 13:12:24.650125 - step 4 of 64 - 2500 active elements (0 deactivated)
12:27:37 INFO    opendrift:2202: 2026-05-11 13:27:24.650125 - step 5 of 64 - 2500 active elements (0 deactivated)
12:27:38 INFO    opendrift:2202: 2026-05-11 13:42:24.650125 - step 6 of 64 - 2500 active elements (0 deactivated)
12:27:38 INFO    opendrift:2202: 2026-05-11 13:57:24.650125 - step 7 of 64 - 2500 active elements (0 deactivated)
12:27:39 INFO    opendrift:2202: 2026-05-11 14:12:24.650125 - step 8 of 64 - 2500 active elements (0 deactivated)
12:27:41 INFO    opendrift:2202: 2026-05-11 14:27:24.650125 - step 9 of 64 - 2500 active elements (0 deactivated)
12:27:42 INFO    opendrift:2202: 2026-05-11 14:42:24.650125 - step 10 of 64 - 2500 active elements (0 deactivated)
12:27:42 INFO    opendrift:2202: 2026-05-11 14:57:24.650125 - step 11 of 64 - 2500 active elements (0 deactivated)
12:27:43 INFO    opendrift:2202: 2026-05-11 15:12:24.650125 - step 12 of 64 - 2500 active elements (0 deactivated)
12:27:45 INFO    opendrift:2202: 2026-05-11 15:27:24.650125 - step 13 of 64 - 2500 active elements (0 deactivated)
12:27:46 INFO    opendrift:2202: 2026-05-11 15:42:24.650125 - step 14 of 64 - 2500 active elements (0 deactivated)
12:27:47 INFO    opendrift:2202: 2026-05-11 15:57:24.650125 - step 15 of 64 - 2500 active elements (0 deactivated)
12:27:47 INFO    opendrift:2202: 2026-05-11 16:12:24.650125 - step 16 of 64 - 2500 active elements (0 deactivated)
12:27:49 INFO    opendrift:2202: 2026-05-11 16:27:24.650125 - step 17 of 64 - 2500 active elements (0 deactivated)
12:27:50 INFO    opendrift:2202: 2026-05-11 16:42:24.650125 - step 18 of 64 - 2500 active elements (0 deactivated)
12:27:51 INFO    opendrift:2202: 2026-05-11 16:57:24.650125 - step 19 of 64 - 2500 active elements (0 deactivated)
12:27:51 INFO    opendrift:2202: 2026-05-11 17:12:24.650125 - step 20 of 64 - 2500 active elements (0 deactivated)
12:27:54 INFO    opendrift:2202: 2026-05-11 17:27:24.650125 - step 21 of 64 - 2500 active elements (0 deactivated)
12:27:54 INFO    opendrift:2202: 2026-05-11 17:42:24.650125 - step 22 of 64 - 2500 active elements (0 deactivated)
12:27:55 INFO    opendrift:2202: 2026-05-11 17:57:24.650125 - step 23 of 64 - 2500 active elements (0 deactivated)
12:27:56 INFO    opendrift:2202: 2026-05-11 18:12:24.650125 - step 24 of 64 - 2500 active elements (0 deactivated)
12:27:58 INFO    opendrift:2202: 2026-05-11 18:27:24.650125 - step 25 of 64 - 2500 active elements (0 deactivated)
12:27:59 INFO    opendrift:2202: 2026-05-11 18:42:24.650125 - step 26 of 64 - 2500 active elements (0 deactivated)
12:27:59 INFO    opendrift:2202: 2026-05-11 18:57:24.650125 - step 27 of 64 - 2500 active elements (0 deactivated)
12:28:00 INFO    opendrift:2202: 2026-05-11 19:12:24.650125 - step 28 of 64 - 2500 active elements (0 deactivated)
12:28:02 INFO    opendrift:2202: 2026-05-11 19:27:24.650125 - step 29 of 64 - 2500 active elements (0 deactivated)
12:28:03 INFO    opendrift:2202: 2026-05-11 19:42:24.650125 - step 30 of 64 - 2500 active elements (0 deactivated)
12:28:03 INFO    opendrift:2202: 2026-05-11 19:57:24.650125 - step 31 of 64 - 2500 active elements (0 deactivated)
12:28:04 INFO    opendrift:2202: 2026-05-11 20:12:24.650125 - step 32 of 64 - 2500 active elements (0 deactivated)
12:28:07 INFO    opendrift:2202: 2026-05-11 20:27:24.650125 - step 33 of 64 - 2500 active elements (0 deactivated)
12:28:08 INFO    opendrift:2202: 2026-05-11 20:42:24.650125 - step 34 of 64 - 2500 active elements (0 deactivated)
12:28:08 INFO    opendrift:2202: 2026-05-11 20:57:24.650125 - step 35 of 64 - 2500 active elements (0 deactivated)
12:28:09 INFO    opendrift:2202: 2026-05-11 21:12:24.650125 - step 36 of 64 - 2500 active elements (0 deactivated)
12:28:13 INFO    opendrift:2202: 2026-05-11 21:27:24.650125 - step 37 of 64 - 2500 active elements (0 deactivated)
12:28:13 INFO    opendrift:2202: 2026-05-11 21:42:24.650125 - step 38 of 64 - 2500 active elements (0 deactivated)
12:28:14 INFO    opendrift:2202: 2026-05-11 21:57:24.650125 - step 39 of 64 - 2500 active elements (0 deactivated)
12:28:14 INFO    opendrift:2202: 2026-05-11 22:12:24.650125 - step 40 of 64 - 2500 active elements (0 deactivated)
12:28:18 INFO    opendrift:2202: 2026-05-11 22:27:24.650125 - step 41 of 64 - 2500 active elements (0 deactivated)
12:28:18 INFO    opendrift:2202: 2026-05-11 22:42:24.650125 - step 42 of 64 - 2500 active elements (0 deactivated)
12:28:19 INFO    opendrift:2202: 2026-05-11 22:57:24.650125 - step 43 of 64 - 2500 active elements (0 deactivated)
12:28:20 INFO    opendrift:2202: 2026-05-11 23:12:24.650125 - step 44 of 64 - 2500 active elements (0 deactivated)
12:28:22 INFO    opendrift:2202: 2026-05-11 23:27:24.650125 - step 45 of 64 - 2500 active elements (0 deactivated)
12:28:23 INFO    opendrift:2202: 2026-05-11 23:42:24.650125 - step 46 of 64 - 2500 active elements (0 deactivated)
12:28:23 INFO    opendrift:2202: 2026-05-11 23:57:24.650125 - step 47 of 64 - 2500 active elements (0 deactivated)
12:28:24 INFO    opendrift:2202: 2026-05-12 00:12:24.650125 - step 48 of 64 - 2500 active elements (0 deactivated)
12:28:27 INFO    opendrift:2202: 2026-05-12 00:27:24.650125 - step 49 of 64 - 2500 active elements (0 deactivated)
12:28:28 INFO    opendrift:2202: 2026-05-12 00:42:24.650125 - step 50 of 64 - 2500 active elements (0 deactivated)
12:28:28 INFO    opendrift:2202: 2026-05-12 00:57:24.650125 - step 51 of 64 - 2500 active elements (0 deactivated)
12:28:29 INFO    opendrift:2202: 2026-05-12 01:12:24.650125 - step 52 of 64 - 2500 active elements (0 deactivated)
12:28:31 INFO    opendrift:2202: 2026-05-12 01:27:24.650125 - step 53 of 64 - 2500 active elements (0 deactivated)
12:28:32 INFO    opendrift:2202: 2026-05-12 01:42:24.650125 - step 54 of 64 - 2500 active elements (0 deactivated)
12:28:32 INFO    opendrift:2202: 2026-05-12 01:57:24.650125 - step 55 of 64 - 2500 active elements (0 deactivated)
12:28:33 INFO    opendrift:2202: 2026-05-12 02:12:24.650125 - step 56 of 64 - 2500 active elements (0 deactivated)
12:28:35 INFO    opendrift:2202: 2026-05-12 02:27:24.650125 - step 57 of 64 - 2500 active elements (0 deactivated)
12:28:36 INFO    opendrift:2202: 2026-05-12 02:42:24.650125 - step 58 of 64 - 2500 active elements (0 deactivated)
12:28:36 INFO    opendrift:2202: 2026-05-12 02:57:24.650125 - step 59 of 64 - 2500 active elements (0 deactivated)
12:28:37 INFO    opendrift:2202: 2026-05-12 03:12:24.650125 - step 60 of 64 - 2500 active elements (0 deactivated)
12:28:39 INFO    opendrift:2202: 2026-05-12 03:27:24.650125 - step 61 of 64 - 2500 active elements (0 deactivated)
12:28:40 INFO    opendrift:2202: 2026-05-12 03:42:24.650125 - step 62 of 64 - 2500 active elements (0 deactivated)
12:28:41 INFO    opendrift:2202: 2026-05-12 03:57:24.650125 - step 63 of 64 - 2500 active elements (0 deactivated)
12:28:41 INFO    opendrift:2202: 2026-05-12 04:12:24.650125 - 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]
    2026-05-11T12:27:24.650125 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2026-05-11T12:27:24.650125000', '2026-05-11T12:57:24.650125000',
           '2026-05-11T13:27:24.650125000', '2026-05-11T13:57:24.650125000',
           '2026-05-11T14:27:24.650125000', '2026-05-11T14:57:24.650125000',
           '2026-05-11T15:27:24.650125000', '2026-05-11T15:57:24.650125000',
           '2026-05-11T16:27:24.650125000', '2026-05-11T16:57:24.650125000',
           '2026-05-11T17:27:24.650125000', '2026-05-11T17:57:24.650125000',
           '2026-05-11T18:27:24.650125000', '2026-05-11T18:57:24.650125000',
           '2026-05-11T19:27:24.650125000', '2026-05-11T19:57:24.650125000',
           '2026-05-11T20:27:24.650125000', '2026-05-11T20:57:24.650125000',
           '2026-05-11T21:27:24.650125000', '2026-05-11T21:57:24.650125000',
           '2026-05-11T22:27:24.650125000', '2026-05-11T22:57:24.650125000',
           '2026-05-11T23:27:24.650125000', '2026-05-11T23:57:24.650125000',
           '2026-05-12T00:27:24.650125000', '2026-05-12T00:57:24.650125000',
           '2026-05-12T01:27:24.650125000', '2026-05-12T01:57:24.650125000',
           '2026-05-12T02:27:24.650125000', '2026-05-12T02:57:24.650125000',
           '2026-05-12T03:27:24.650125000', '2026-05-12T03:57:24.650125000',
           '2026-05-12T04:27:24.650125000'], 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 ... 7.733 7.724

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    4.8525558

    maxval :

    8.254829

    array([[5.       , 4.9955635, 4.99093  , ..., 4.917389 , 4.912326 ,
            4.9076147],
           [5.0612245, 5.057007 , 5.052608 , ..., 4.9855266, 4.9806404,
            4.9761024],
           [5.122449 , 5.118343 , 5.114042 , ..., 5.0534244, 5.0487847,
            5.0444937],
           ...,
           [7.877551 , 7.86956  , 7.8628354, ..., 7.559077 , 7.551455 ,
            7.5444455],
           [7.9387755, 7.932441 , 7.927346 , ..., 7.6419344, 7.6340833,
            7.6264744],
           [8.       , 7.994821 , 7.990794 , ..., 7.7411466, 7.7327323,
            7.7238536]], 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 :

    69.79175

    maxval :

    70.885666

    array([[69.8     , 69.79991 , 69.799995, ..., 69.822266, 69.823204,
            69.82433 ],
           [69.8     , 69.79988 , 69.79995 , ..., 69.82155 , 69.82243 ,
            69.82351 ],
           [69.8     , 69.79988 , 69.799965, ..., 69.82088 , 69.8217  ,
            69.8227  ],
           ...,
           [70.8     , 70.800514, 70.8006  , ..., 70.74795 , 70.74275 ,
            70.73695 ],
           [70.8     , 70.80016 , 70.79986 , ..., 70.74539 , 70.74022 ,
            70.734505],
           [70.8     , 70.8     , 70.79952 , ..., 70.73815 , 70.732635,
            70.72681 ]], 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
    -0.09357 -0.09866 ... -0.08424

    minval :

    -0.2468615

    maxval :

    0.32751986

    array([[-0.09357346, -0.09865746, -0.10058912, ..., -0.10991456,
            -0.10294325, -0.09862985],
           [-0.08899321, -0.09373543, -0.09527066, ..., -0.10611768,
            -0.09922284, -0.09496541],
           [-0.08663222, -0.09147543, -0.09341096, ..., -0.10086671,
            -0.09392423, -0.08968856],
           ...,
           [-0.07001039, -0.04953773, -0.03331286, ..., -0.0488175 ,
            -0.04710897, -0.05147088],
           [-0.03701416, -0.01675854, -0.00239341, ..., -0.05241072,
            -0.05664185, -0.06228824],
           [-0.01377612,  0.00540769,  0.01740652, ..., -0.06206241,
            -0.07565243, -0.0842433 ]], shape=(2500, 33), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    -0.008324 0.002412 ... -0.1952

    minval :

    -0.3948528

    maxval :

    0.31755143

    array([[-0.00832373,  0.00241176,  0.01462373, ...,  0.05489958,
             0.06753534,  0.07295448],
           [-0.01020849,  0.00124256,  0.01457566, ...,  0.05177886,
             0.06397617,  0.06915563],
           [-0.01058861,  0.00166257,  0.01628077, ...,  0.04801799,
             0.0596464 ,  0.06466231],
           ...,
           [-0.01215941, -0.02612116, -0.04476471, ..., -0.15416877,
            -0.18720242, -0.19983447],
           [-0.03100635, -0.04785775, -0.06879882, ..., -0.14781182,
            -0.1781836 , -0.1887981 ],
           [-0.03847801, -0.05654342, -0.07828806, ..., -0.1682716 ,
            -0.1893915 , -0.19516332]], shape=(2500, 33), dtype=float32)

  • sea_surface_height
    (trajectory, time)
    float32
    -1.043 -1.051 ... -0.7594 -0.7184

    minval :

    -1.1179625

    maxval :

    -0.24123266

    array([[-1.0427005 , -1.0507048 , -1.0376315 , ..., -0.6618967 ,
            -0.5827693 , -0.54214   ],
           [-1.0430604 , -1.0511385 , -1.0381274 , ..., -0.6622895 ,
            -0.5830309 , -0.54234576],
           [-1.0436852 , -1.0518577 , -1.0389216 , ..., -0.6627981 ,
            -0.58340794, -0.5426613 ],
           ...,
           [-1.0630467 , -1.1003885 , -1.1013478 , ..., -0.81508887,
            -0.7496347 , -0.70887476],
           [-1.0672709 , -1.1052572 , -1.1063944 , ..., -0.8198489 ,
            -0.75408036, -0.7132496 ],
           [-1.0720345 , -1.110132  , -1.1114776 , ..., -0.825469  ,
            -0.75944406, -0.7183595 ]], shape=(2500, 33), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    0.0 0.0 0.0 ... -5.003 -5.179

    minval :

    -8.893522

    maxval :

    0.043157894

    array([[ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           [ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           [ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           ...,
           [-5.0049057, -4.5949016, -4.6108146, ..., -5.594035 , -4.7182007,
            -4.6952353],
           [-4.9634247, -4.552036 , -4.5570674, ..., -5.542495 , -4.796777 ,
            -4.8276772],
           [-4.925145 , -4.548283 , -4.531175 , ..., -5.466885 , -5.0031343,
            -5.1786103]], shape=(2500, 33), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    0.0 0.0 0.0 ... -8.375 -8.58 -8.338

    minval :

    -9.098717

    maxval :

    4.313146

    array([[ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           [ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           [ 0.       ,  0.       ,  0.       , ...,  0.       ,  0.       ,
             0.       ],
           ...,
           [ 2.5372481,  1.9153472,  1.4065363, ..., -7.833845 , -8.371123 ,
            -8.237519 ],
           [ 2.4110794,  1.818678 ,  1.3507922, ..., -8.154352 , -8.609507 ,
            -8.42967  ],
           [ 2.2802856,  1.718668 ,  1.2811241, ..., -8.374799 , -8.580258 ,
            -8.337524 ]], shape=(2500, 33), dtype=float32)

  • upward_sea_water_velocity
    (trajectory, time)
    float32
    0.0 0.0 0.0 ... 3.926e-05 4.207e-05

    minval :

    -0.008930016

    maxval :

    0.00452402

    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],
           ...,
           [-2.0863054e-05, -1.0863055e-05, -8.6305482e-07, ...,
             2.4436629e-05,  2.9564513e-05,  3.2326298e-05],
           [-2.0863054e-05, -1.0863055e-05, -8.6305482e-07, ...,
             3.9136943e-05,  4.9136943e-05,  4.9999999e-05],
           [-2.0863054e-05, -1.0863055e-05, -8.6305482e-07, ...,
             3.0754069e-05,  3.9259099e-05,  4.2068470e-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 ... 2.461 2.427 2.37

    minval :

    0.0

    maxval :

    2.796492

    array([[0.        , 0.        , 0.        , ..., 0.        , 0.        ,
            0.        ],
           [0.        , 0.        , 0.        , ..., 0.        , 0.        ,
            0.        ],
           [0.        , 0.        , 0.        , ..., 0.        , 0.        ,
            0.        ],
           ...,
           [0.774573  , 0.6096292 , 0.57165366, ..., 2.279494  , 2.2714932 ,
            2.211588  ],
           [0.74904263, 0.5911041 , 0.5557509 , ..., 2.3914325 , 2.3894634 ,
            2.321399  ],
           [0.72463614, 0.5815612 , 0.5454515 , ..., 2.4605925 , 2.4268436 ,
            2.3697753 ]], 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 :

    3245.0093

    array([[3237.644 , 3238.1113, 3238.594 , ..., 3244.3699, 3244.8105,
            3245.0093],
           [3231.73  , 3232.091 , 3232.4656, ..., 3237.1733, 3237.562 ,
            3237.737 ],
           [3226.8372, 3227.1572, 3227.4895, ..., 3231.1497, 3231.4963,
            3231.6248],
           ...,
           [2909.3318, 2910.2136, 2910.9617, ..., 2966.1492, 2965.299 ,
            2964.9727],
           [2900.6626, 2901.6245, 2902.4546, ..., 2966.695 , 2968.5762,
            2969.295 ],
           [2890.7188, 2891.5803, 2892.317 , ..., 2945.115 , 2948.5388,
            2950.0232]], 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 12:27:24.650125', '2026-05-11 12:57:24.650125',
                   '2026-05-11 13:27:24.650125', '2026-05-11 13:57:24.650125',
                   '2026-05-11 14:27:24.650125', '2026-05-11 14:57:24.650125',
                   '2026-05-11 15:27:24.650125', '2026-05-11 15:57:24.650125',
                   '2026-05-11 16:27:24.650125', '2026-05-11 16:57:24.650125',
                   '2026-05-11 17:27:24.650125', '2026-05-11 17:57:24.650125',
                   '2026-05-11 18:27:24.650125', '2026-05-11 18:57:24.650125',
                   '2026-05-11 19:27:24.650125', '2026-05-11 19:57:24.650125',
                   '2026-05-11 20:27:24.650125', '2026-05-11 20:57:24.650125',
                   '2026-05-11 21:27:24.650125', '2026-05-11 21:57:24.650125',
                   '2026-05-11 22:27:24.650125', '2026-05-11 22:57:24.650125',
                   '2026-05-11 23:27:24.650125', '2026-05-11 23:57:24.650125',
                   '2026-05-12 00:27:24.650125', '2026-05-12 00:57:24.650125',
                   '2026-05-12 01:27:24.650125', '2026-05-12 01:57:24.650125',
                   '2026-05-12 02:27:24.650125', '2026-05-12 02:57:24.650125',
                   '2026-05-12 03:27:24.650125', '2026-05-12 03:57:24.650125',
                   '2026-05-12 04:27:24.650125'],
                  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 12:27:28.635938

  date_created :

  2026-05-11T12:27:28.635948

  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 12:27:24.650125

  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 12:27:28.642681

  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 04:27:24.650125

  time_coverage_duration :

  P0DT16H0M0S

  time_coverage_resolution :

  P0DT0H15M0S

  performance :

  -------------------- Reader performance: -------------------- https://thredds.met.no/thredds/dodsC/fou-hi/norkystv3_800m_m00_be 0:00:32.5 total 0:00:00.0 preparing 0:00:32.1 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 0:00:41.0 total 0:00:00.0 preparing 0:00:40.8 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: 1:26.3 total time 11.0 configuration 0.0 preparing main loop 0.0 moving elements to ocean 1:15.2 main loop 0.2 updating elements 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  69.79175

  geospatial_lat_max :

  70.885666

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  4.8525558

  geospatial_lon_max :

  8.254829

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:01:26.317169

  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
 0:00:32.5  total
 0:00:00.0  preparing
 0:00:32.1  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
 0:00:41.0  total
 0:00:00.0  preparing
 0:00:40.8  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:
 1:26.3 total time
   11.0 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
 1:15.2 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 12:27:24.650125 UTC
        Present: 2026-05-12 04:27:24.650125 UTC
        Calculation steps: 64 * 0:15:00 - total time: 16:00:00
        Output steps: 33 * 0:30:00
===========================

12:28:43 WARNING opendrift:2565: Plotting fast. This will make your plots less accurate.
12:28:45 INFO    opendrift:4768: Saving animation to /root/project/docs/source/gallery/animations/example_reader_boundary_0.gif...
12:29:08 INFO    opendrift:3191: Time to make animation: 0:00:24.535681

o.plot(fast=True)

12:29:08 WARNING opendrift:2565: Plotting fast. This will make your plots less accurate.

(<GeoAxes: title={'center': 'OpenDrift - OceanDrift\n2026-05-11 12:27 to 2026-05-12 04:27 UTC (33 steps)'}>, <Figure size 952.768x1100 with 1 Axes>)