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).

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/sea/norkyst800m/1h/aggregate_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)

17:16:22 INFO    opendrift:513: OpenDriftSimulation initialised (version 1.14.2 / v1.14.2-88-gf09b7bd)
17:16:22 INFO    opendrift.readers:61: Opening file with xr.open_dataset
17:16:23 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'X', 'y': 'Y', 'z': 'depth', 'time': 'time'}
17:16:23 INFO    opendrift.readers:61: Opening file with xr.open_dataset
17:16:25 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}

Seeding some particles

lons = np.linspace(10.2, 12.2, 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=reader_topaz.start_time)

17:16:25 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
17:16:30 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
17:16:30 INFO    opendrift.models.basemodel.environment:232:    ocean_vertical_diffusivity: 0.000000
17:16:30 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_significant_height: 0.000000
17:16:30 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
17:16:30 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
17:16:30 INFO    opendrift.models.basemodel.environment:232:    ocean_mixed_layer_thickness: 50.000000

Running model

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

17:16:30 INFO    opendrift:1732: Skipping environment variable ocean_vertical_diffusivity because of condition ['drift:vertical_mixing', 'is', False]
17:16:30 INFO    opendrift:1732: Skipping environment variable ocean_mixed_layer_thickness because of condition ['drift:vertical_mixing', 'is', False]
17:16:30 INFO    opendrift:1743: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
17:16:30 INFO    opendrift:1743: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
17:16:30 INFO    opendrift:1751: Storing previous values of environment variable sea_surface_height because of condition ['drift:vertical_advection', 'is', True]
17:16:30 INFO    opendrift:899: Using existing reader for land_binary_mask
17:16:30 INFO    opendrift:928: All points are in ocean
17:16:30 INFO    opendrift:2035: 2023-01-01 00:00:00 - step 1 of 64 - 2500 active elements (0 deactivated)
17:16:32 INFO    opendrift:2035: 2023-01-01 00:15:00 - step 2 of 64 - 2500 active elements (0 deactivated)
17:16:34 INFO    opendrift:2035: 2023-01-01 00:30:00 - step 3 of 64 - 2500 active elements (0 deactivated)
17:16:35 INFO    opendrift:2035: 2023-01-01 00:45:00 - step 4 of 64 - 2500 active elements (0 deactivated)
17:16:35 INFO    opendrift:2035: 2023-01-01 01:00:00 - step 5 of 64 - 2500 active elements (0 deactivated)
17:16:36 INFO    opendrift:2035: 2023-01-01 01:15:00 - step 6 of 64 - 2500 active elements (0 deactivated)
17:16:38 INFO    opendrift:2035: 2023-01-01 01:30:00 - step 7 of 64 - 2500 active elements (0 deactivated)
17:16:39 INFO    opendrift:2035: 2023-01-01 01:45:00 - step 8 of 64 - 2500 active elements (0 deactivated)
17:16:40 INFO    opendrift:2035: 2023-01-01 02:00:00 - step 9 of 64 - 2500 active elements (0 deactivated)
17:16:40 INFO    opendrift:2035: 2023-01-01 02:15:00 - step 10 of 64 - 2500 active elements (0 deactivated)
17:16:43 INFO    opendrift:2035: 2023-01-01 02:30:00 - step 11 of 64 - 2500 active elements (0 deactivated)
17:16:43 INFO    opendrift:2035: 2023-01-01 02:45:00 - step 12 of 64 - 2500 active elements (0 deactivated)
17:16:44 INFO    opendrift:2035: 2023-01-01 03:00:00 - step 13 of 64 - 2500 active elements (0 deactivated)
17:16:45 INFO    opendrift:2035: 2023-01-01 03:15:00 - step 14 of 64 - 2500 active elements (0 deactivated)
17:16:47 INFO    opendrift:2035: 2023-01-01 03:30:00 - step 15 of 64 - 2500 active elements (0 deactivated)
17:16:48 INFO    opendrift:2035: 2023-01-01 03:45:00 - step 16 of 64 - 2500 active elements (0 deactivated)
17:16:48 INFO    opendrift:2035: 2023-01-01 04:00:00 - step 17 of 64 - 2500 active elements (0 deactivated)
17:16:49 INFO    opendrift:2035: 2023-01-01 04:15:00 - step 18 of 64 - 2500 active elements (0 deactivated)
17:16:51 INFO    opendrift:2035: 2023-01-01 04:30:00 - step 19 of 64 - 2500 active elements (0 deactivated)
17:16:52 INFO    opendrift:2035: 2023-01-01 04:45:00 - step 20 of 64 - 2500 active elements (0 deactivated)
17:16:53 INFO    opendrift:2035: 2023-01-01 05:00:00 - step 21 of 64 - 2500 active elements (0 deactivated)
17:16:53 INFO    opendrift:2035: 2023-01-01 05:15:00 - step 22 of 64 - 2500 active elements (0 deactivated)
17:16:56 INFO    opendrift:2035: 2023-01-01 05:30:00 - step 23 of 64 - 2500 active elements (0 deactivated)
17:16:57 INFO    opendrift:2035: 2023-01-01 05:45:00 - step 24 of 64 - 2500 active elements (0 deactivated)
17:16:57 INFO    opendrift:2035: 2023-01-01 06:00:00 - step 25 of 64 - 2500 active elements (0 deactivated)
17:16:58 INFO    opendrift:2035: 2023-01-01 06:15:00 - step 26 of 64 - 2500 active elements (0 deactivated)
17:17:00 INFO    opendrift:2035: 2023-01-01 06:30:00 - step 27 of 64 - 2500 active elements (0 deactivated)
17:17:01 INFO    opendrift:2035: 2023-01-01 06:45:00 - step 28 of 64 - 2500 active elements (0 deactivated)
17:17:02 INFO    opendrift:2035: 2023-01-01 07:00:00 - step 29 of 64 - 2500 active elements (0 deactivated)
17:17:02 INFO    opendrift:2035: 2023-01-01 07:15:00 - step 30 of 64 - 2500 active elements (0 deactivated)
17:17:04 INFO    opendrift:2035: 2023-01-01 07:30:00 - step 31 of 64 - 2500 active elements (0 deactivated)
17:17:05 INFO    opendrift:2035: 2023-01-01 07:45:00 - step 32 of 64 - 2500 active elements (0 deactivated)
17:17:06 INFO    opendrift:2035: 2023-01-01 08:00:00 - step 33 of 64 - 2500 active elements (0 deactivated)
17:17:07 INFO    opendrift:2035: 2023-01-01 08:15:00 - step 34 of 64 - 2500 active elements (0 deactivated)
17:17:09 INFO    opendrift:2035: 2023-01-01 08:30:00 - step 35 of 64 - 2500 active elements (0 deactivated)
17:17:10 INFO    opendrift:2035: 2023-01-01 08:45:00 - step 36 of 64 - 2500 active elements (0 deactivated)
17:17:10 INFO    opendrift:2035: 2023-01-01 09:00:00 - step 37 of 64 - 2500 active elements (0 deactivated)
17:17:11 INFO    opendrift:2035: 2023-01-01 09:15:00 - step 38 of 64 - 2500 active elements (0 deactivated)
17:17:13 INFO    opendrift:2035: 2023-01-01 09:30:00 - step 39 of 64 - 2500 active elements (0 deactivated)
17:17:14 INFO    opendrift:2035: 2023-01-01 09:45:00 - step 40 of 64 - 2500 active elements (0 deactivated)
17:17:15 INFO    opendrift:2035: 2023-01-01 10:00:00 - step 41 of 64 - 2500 active elements (0 deactivated)
17:17:15 INFO    opendrift:2035: 2023-01-01 10:15:00 - step 42 of 64 - 2500 active elements (0 deactivated)
17:17:18 INFO    opendrift:2035: 2023-01-01 10:30:00 - step 43 of 64 - 2500 active elements (0 deactivated)
17:17:18 INFO    opendrift:2035: 2023-01-01 10:45:00 - step 44 of 64 - 2500 active elements (0 deactivated)
17:17:19 INFO    opendrift:2035: 2023-01-01 11:00:00 - step 45 of 64 - 2500 active elements (0 deactivated)
17:17:20 INFO    opendrift:2035: 2023-01-01 11:15:00 - step 46 of 64 - 2500 active elements (0 deactivated)
17:17:22 INFO    opendrift:2035: 2023-01-01 11:30:00 - step 47 of 64 - 2500 active elements (0 deactivated)
17:17:22 INFO    opendrift:2035: 2023-01-01 11:45:00 - step 48 of 64 - 2500 active elements (0 deactivated)
17:17:23 INFO    opendrift:2035: 2023-01-01 12:00:00 - step 49 of 64 - 2500 active elements (0 deactivated)
17:17:24 INFO    opendrift:2035: 2023-01-01 12:15:00 - step 50 of 64 - 2500 active elements (0 deactivated)
17:17:27 INFO    opendrift:2035: 2023-01-01 12:30:00 - step 51 of 64 - 2500 active elements (0 deactivated)
17:17:27 INFO    opendrift:2035: 2023-01-01 12:45:00 - step 52 of 64 - 2500 active elements (0 deactivated)
17:17:28 INFO    opendrift:2035: 2023-01-01 13:00:00 - step 53 of 64 - 2500 active elements (0 deactivated)
17:17:29 INFO    opendrift:2035: 2023-01-01 13:15:00 - step 54 of 64 - 2500 active elements (0 deactivated)
17:17:31 INFO    opendrift:2035: 2023-01-01 13:30:00 - step 55 of 64 - 2500 active elements (0 deactivated)
17:17:32 INFO    opendrift:2035: 2023-01-01 13:45:00 - step 56 of 64 - 2500 active elements (0 deactivated)
17:17:32 INFO    opendrift:2035: 2023-01-01 14:00:00 - step 57 of 64 - 2500 active elements (0 deactivated)
17:17:33 INFO    opendrift:2035: 2023-01-01 14:15:00 - step 58 of 64 - 2500 active elements (0 deactivated)
17:17:35 INFO    opendrift:2035: 2023-01-01 14:30:00 - step 59 of 64 - 2500 active elements (0 deactivated)
17:17:36 INFO    opendrift:2035: 2023-01-01 14:45:00 - step 60 of 64 - 2500 active elements (0 deactivated)
17:17:37 INFO    opendrift:2035: 2023-01-01 15:00:00 - step 61 of 64 - 2500 active elements (0 deactivated)
17:17:37 INFO    opendrift:2035: 2023-01-01 15:15:00 - step 62 of 64 - 2500 active elements (0 deactivated)
17:17:40 INFO    opendrift:2035: 2023-01-01 15:30:00 - step 63 of 64 - 2500 active elements (0 deactivated)
17:17:41 INFO    opendrift:2035: 2023-01-01 15:45:00 - 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 2023...
Data variables: (12/21)
    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 ...
    ...                                        ...
    upward_sea_water_velocity                 (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: (12/119)
    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]
    2023-01-01 ... 2023-01-01T16:00:00

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2023-01-01T00:00:00.000000000', '2023-01-01T00:30:00.000000000',
           '2023-01-01T01:00:00.000000000', '2023-01-01T01:30:00.000000000',
           '2023-01-01T02:00:00.000000000', '2023-01-01T02:30:00.000000000',
           '2023-01-01T03:00:00.000000000', '2023-01-01T03:30:00.000000000',
           '2023-01-01T04:00:00.000000000', '2023-01-01T04:30:00.000000000',
           '2023-01-01T05:00:00.000000000', '2023-01-01T05:30:00.000000000',
           '2023-01-01T06:00:00.000000000', '2023-01-01T06:30:00.000000000',
           '2023-01-01T07:00:00.000000000', '2023-01-01T07:30:00.000000000',
           '2023-01-01T08:00:00.000000000', '2023-01-01T08:30:00.000000000',
           '2023-01-01T09:00:00.000000000', '2023-01-01T09:30:00.000000000',
           '2023-01-01T10:00:00.000000000', '2023-01-01T10:30:00.000000000',
           '2023-01-01T11:00:00.000000000', '2023-01-01T11:30:00.000000000',
           '2023-01-01T12:00:00.000000000', '2023-01-01T12:30:00.000000000',
           '2023-01-01T13:00:00.000000000', '2023-01-01T13:30:00.000000000',
           '2023-01-01T14:00:00.000000000', '2023-01-01T14:30:00.000000000',
           '2023-01-01T15:00:00.000000000', '2023-01-01T15:30:00.000000000',
           '2023-01-01T16:00:00.000000000'], dtype='datetime64[ns]')

• Data variables: (21)
  • 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
    10.2 10.22 10.24 ... 12.81 12.81

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    10.2

    maxval :

    13.091973

    array([[10.2      , 10.218525 , 10.237876 , ..., 10.467282 , 10.460944 ,
            10.452177 ],
           [10.240816 , 10.260304 , 10.280287 , ..., 10.517744 , 10.511491 ,
            10.502817 ],
           [10.281632 , 10.301856 , 10.322128 , ..., 10.569458 , 10.564138 ,
            10.556259 ],
           ...,
           [12.118367 , 12.126342 , 12.138069 , ..., 12.76848  , 12.779327 ,
            12.789845 ],
           [12.1591835, 12.167105 , 12.178949 , ..., 12.784947 , 12.794078 ,
            12.803002 ],
           [12.2      , 12.208063 , 12.220088 , ..., 12.798654 , 12.80614  ,
            12.813357 ]], shape=(2500, 33), dtype=float32)

  • lat
    (trajectory, time)
    float32
    69.8 69.8 69.8 ... 70.77 70.77

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    69.717896

    maxval :

    70.89516

    array([[69.8     , 69.8011  , 69.80156 , ..., 69.76242 , 69.763084,
            69.76411 ],
           [69.8     , 69.800674, 69.80059 , ..., 69.756424, 69.75766 ,
            69.759254],
           [69.8     , 69.80005 , 69.79928 , ..., 69.75672 , 69.75862 ,
            69.7608  ],
           ...,
           [70.8     , 70.80496 , 70.80982 , ..., 70.80402 , 70.80058 ,
            70.79753 ],
           [70.8     , 70.80472 , 70.80928 , ..., 70.788734, 70.78517 ,
            70.781975],
           [70.8     , 70.80437 , 70.8085  , ..., 70.7735  , 70.76984 ,
            70.76654 ]], 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
    0.1508 0.1694 ... 0.03577 0.03948

    minval :

    -0.3653251

    maxval :

    0.6282285

    array([[ 0.1508468 ,  0.16937989,  0.18395689, ..., -0.06200969,
            -0.0913118 , -0.10577182],
           [ 0.16984282,  0.18301564,  0.19120601, ..., -0.06365902,
            -0.09209113, -0.10697623],
           [ 0.18362503,  0.18998086,  0.19163287, ..., -0.0487317 ,
            -0.07867802, -0.09456115],
           ...,
           [-0.00406694,  0.03863363,  0.07994751, ...,  0.09638151,
             0.10204943,  0.10615217],
           [ 0.00049907,  0.04224612,  0.08350854, ...,  0.06109729,
             0.06950085,  0.07438668],
           [ 0.00524969,  0.04601391,  0.08582487, ...,  0.02833329,
             0.03576539,  0.03947533]], shape=(2500, 33), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    0.09247 0.04716 ... -0.2675 -0.2656

    minval :

    -0.5568988

    maxval :

    0.51733863

    array([[ 0.0924696 ,  0.04716127, -0.00404848, ..., -0.1475011 ,
            -0.13116768, -0.12363526],
           [ 0.0708096 ,  0.01635837, -0.04173061, ..., -0.11262627,
            -0.09470789, -0.0864872 ],
           [ 0.03575769, -0.0245007 , -0.08704081, ..., -0.07129022,
            -0.0562574 , -0.04900027],
           ...,
           [ 0.28007287,  0.2870139 ,  0.29011324, ..., -0.2565261 ,
            -0.25024074, -0.247474  ],
           [ 0.26347846,  0.2685886 ,  0.26917946, ..., -0.2648394 ,
            -0.2600432 , -0.2574585 ],
           [ 0.24081926,  0.24294229,  0.24096689, ..., -0.27179486,
            -0.26748738, -0.26557094]], shape=(2500, 33), dtype=float32)

  • sea_surface_height
    (trajectory, time)
    float32
    -0.8835 -0.9414 ... -0.4513 -0.3859

    minval :

    -1.0293646

    maxval :

    0.17818588

    array([[-0.8834985 , -0.94137883, -0.999368  , ..., -0.59958214,
            -0.45498455, -0.38259372],
           [-0.8813948 , -0.93969166, -0.99930507, ..., -0.6034424 ,
            -0.45953178, -0.38762543],
           [-0.87944543, -0.9388499 , -0.99894404, ..., -0.60622054,
            -0.46227852, -0.3903258 ],
           ...,
           [-0.78084356, -0.8482051 , -0.915197  , ..., -0.5790119 ,
            -0.44814277, -0.3826064 ],
           [-0.77600086, -0.8440045 , -0.91117555, ..., -0.58016   ,
            -0.4491178 , -0.38358802],
           [-0.7718407 , -0.8396784 , -0.9071907 , ..., -0.5822763 ,
            -0.4512848 , -0.38591766]], shape=(2500, 33), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    12.05 12.06 12.02 ... 5.652 5.332

    minval :

    -4.76403

    maxval :

    14.205892

    array([[12.046592 , 12.060548 , 12.016486 , ..., -3.048309 , -4.1922765,
            -4.76403  ],
           [12.192654 , 12.159228 , 12.000943 , ..., -2.8907146, -4.040566 ,
            -4.620782 ],
           [12.418686 , 12.245587 , 11.96399  , ..., -2.6028574, -3.816587 ,
            -4.4294868],
           ...,
           [ 7.3927183,  9.054044 , 10.900345 , ...,  6.3582907,  5.6842937,
             5.363099 ],
           [ 7.0642347,  8.949439 , 10.951578 , ...,  6.3320518,  5.672694 ,
             5.3552027],
           [ 6.9538794,  8.9463625, 11.016491 , ...,  6.300161 ,  5.6516647,
             5.3322606]], shape=(2500, 33), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    -0.7557 -0.4097 ... 2.876 3.344

    minval :

    -2.3135846

    maxval :

    9.767339

    array([[-7.5570089e-01, -4.0970048e-01,  1.1601480e-06, ...,
             9.1229935e+00,  9.4601374e+00,  9.6375275e+00],
           [-8.9776689e-01, -4.7762707e-01,  5.4054595e-07, ...,
             9.1772108e+00,  9.4046059e+00,  9.5342512e+00],
           [-1.0185230e+00, -5.2432811e-01,  5.9368199e-07, ...,
             9.2119341e+00,  9.3544655e+00,  9.4452267e+00],
           ...,
           [ 1.4178244e+00,  8.2702041e-01,  1.7052831e-01, ...,
             1.8468108e+00,  2.7581508e+00,  3.2152274e+00],
           [ 1.5421191e+00,  8.5273612e-01,  1.3571195e-01, ...,
             1.9086848e+00,  2.8232441e+00,  3.2813883e+00],
           [ 1.6208452e+00,  8.7952000e-01,  1.2762508e-01, ...,
             1.9493971e+00,  2.8758116e+00,  3.3442075e+00]],
          shape=(2500, 33), dtype=float32)

  • upward_sea_water_velocity
    (trajectory, time)
    float32
    4.024e-07 -4.216e-06 ... 7.476e-05

    minval :

    -0.00052312494

    maxval :

    0.0007168661

    array([[ 4.0239186e-07, -4.2159904e-06, -6.4648011e-06, ...,
             7.5176358e-05,  8.6917629e-05,  9.2633367e-05],
           [ 3.4095666e-07, -1.6698150e-06, -3.5794367e-06, ...,
             5.7124256e-05,  6.5975793e-05,  7.0551658e-05],
           [ 2.2735834e-07, -3.0694378e-06, -9.3345407e-06, ...,
             6.3257008e-05,  6.9454924e-05,  7.2212468e-05],
           ...,
           [-2.1482394e-07, -8.0566851e-06, -1.6065291e-05, ...,
             6.2781241e-05,  7.0755545e-05,  7.4636824e-05],
           [-1.8747035e-07, -8.1394128e-06, -1.5906027e-05, ...,
             6.1363462e-05,  6.9536123e-05,  7.3823001e-05],
           [-1.2054919e-07, -8.1393873e-06, -1.5986132e-05, ...,
             6.1193852e-05,  7.0206443e-05,  7.4758616e-05]],
          shape=(2500, 33), dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    3.584 3.582 3.552 ... 0.9892 0.9746

    minval :

    0.0

    maxval :

    4.9857564

    array([[3.5840104 , 3.582367  , 3.55214   , ..., 2.2760217 , 2.6339068 ,
            2.8432167 ],
           [3.6768823 , 3.6426442 , 3.5429568 , ..., 2.2774048 , 2.5774105 ,
            2.7614377 ],
           [3.8194234 , 3.6956413 , 3.5211713 , ..., 2.254211  , 2.51098   ,
            2.6772833 ],
           ...,
           [1.3938978 , 2.0334275 , 2.9236264 , ..., 1.0784286 , 0.9819973 ,
            0.9618727 ],
           [1.286126  , 1.9881625 , 2.9509048 , ..., 1.0759536 , 0.987694  ,
            0.97036433],
           [1.2541959 , 1.9879495 , 2.985932  , ..., 1.0699074 , 0.98920554,
            0.9745714 ]], 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
    2.92e+03 2.919e+03 ... 2.459e+03

    minval :

    2397.992

    maxval :

    2932.8926

    array([[2919.9211, 2918.9316, 2918.1375, ..., 2924.6523, 2924.1492,
            2923.8367],
           [2918.3804, 2917.587 , 2917.0415, ..., 2928.71  , 2928.1528,
            2927.8   ],
           [2917.099 , 2916.658 , 2916.4844, ..., 2931.1873, 2930.6946,
            2930.3992],
           ...,
           [2486.0542, 2481.291 , 2477.7607, ..., 2417.057 , 2419.6904,
            2420.9392],
           [2488.389 , 2484.983 , 2483.9897, ..., 2435.157 , 2438.7778,
            2440.4863],
           [2495.363 , 2494.0251, 2495.569 , ..., 2453.5906, 2457.4429,
            2459.1968]], 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(['2023-01-01 00:00:00', '2023-01-01 00:30:00',
                   '2023-01-01 01:00:00', '2023-01-01 01:30:00',
                   '2023-01-01 02:00:00', '2023-01-01 02:30:00',
                   '2023-01-01 03:00:00', '2023-01-01 03:30:00',
                   '2023-01-01 04:00:00', '2023-01-01 04:30:00',
                   '2023-01-01 05:00:00', '2023-01-01 05:30:00',
                   '2023-01-01 06:00:00', '2023-01-01 06:30:00',
                   '2023-01-01 07:00:00', '2023-01-01 07:30:00',
                   '2023-01-01 08:00:00', '2023-01-01 08:30:00',
                   '2023-01-01 09:00:00', '2023-01-01 09:30:00',
                   '2023-01-01 10:00:00', '2023-01-01 10:30:00',
                   '2023-01-01 11:00:00', '2023-01-01 11:30:00',
                   '2023-01-01 12:00:00', '2023-01-01 12:30:00',
                   '2023-01-01 13:00:00', '2023-01-01 13:30:00',
                   '2023-01-01 14:00:00', '2023-01-01 14:30:00',
                   '2023-01-01 15:00:00', '2023-01-01 15:30:00',
                   '2023-01-01 16:00:00'],
                  dtype='datetime64[ns]', name='time', freq='30min'))

• Attributes: (119)

  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 2025-07-11 17:16:30.131260

  date_created :

  2025-07-11T17:16:30.131276

  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/sea/norkyst800m/1h/aggregate_be', 'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'global_landmask'])

  time_coverage_start :

  2023-01-01 00:00:00

  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: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:horizontal_diffusivity :

  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: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 :

  1.14.2

  seed_geojson :

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

  simulation_time :

  2025-07-11 17:16:30.138518

  reader_x_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_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/sea/norkyst800m/1h/aggregate_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/sea/norkyst800m/1h/aggregate_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/sea/norkyst800m/1h/aggregate_be']

  reader_y_wind :

  ['https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be']

  reader_upward_sea_water_velocity :

  ['https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be']

  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/sea/norkyst800m/1h/aggregate_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 :

  2023-01-01 16:00:00

  time_coverage_duration :

  P0DT16H0M0S

  time_coverage_resolution :

  P0DT0H15M0S

  performance :

  -------------------- Reader performance: -------------------- https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be 0:00:28.4 total 0:00:00.0 preparing 0:00:27.8 reading 0:00:00.5 interpolation 0:00:00.0 interpolation_time 0:00:00.5 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml 0:00:40.8 total 0:00:00.0 preparing 0:00:40.7 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: 1:19.6 total time 8.1 configuration 0.0 preparing main loop 0.0 moving elements to ocean 1:11.4 main loop 0.2 updating elements 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  69.717896

  geospatial_lat_max :

  70.89516

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  10.2

  geospatial_lon_max :

  13.091973

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:01:19.624118

  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/sea/norkyst800m/1h/aggregate_be
 0:00:28.4  total
 0:00:00.0  preparing
 0:00:27.8  reading
 0:00:00.5  interpolation
 0:00:00.0  interpolation_time
 0:00:00.5  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
 0:00:40.8  total
 0:00:00.0  preparing
 0:00:40.7  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:
 1:19.6 total time
    8.1 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
 1:11.4 main loop
      0.2 updating elements
    0.0 cleaning up
--------------------
===========================
Model:  OceanDrift     (OpenDrift version 1.14.2)
        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/sea/norkyst800m/1h/aggregate_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/sea/norkyst800m/1h/aggregate_be
  -----
  land_binary_mask
     1) global_landmask
  -----
Readers not added for the following variables:
  sea_surface_wave_significant_height
  sea_surface_wave_stokes_drift_x_velocity
  sea_surface_wave_stokes_drift_y_velocity

Discarded readers:

Time:
        Start: 2023-01-01 00:00:00 UTC
        Present: 2023-01-01 16:00:00 UTC
        Calculation steps: 64 * 0:15:00 - total time: 16:00:00
        Output steps: 33 * 0:30:00
===========================

17:17:41 WARNING opendrift:2391: Plotting fast. This will make your plots less accurate.
17:17:43 INFO    opendrift:4553: Saving animation to /root/project/docs/source/gallery/animations/example_reader_boundary_0.gif...
17:18:09 INFO    opendrift:2994: Time to make animation: 0:00:27.774197

o.plot(fast=True)

17:18:09 WARNING opendrift:2391: Plotting fast. This will make your plots less accurate.

(<GeoAxes: title={'center': 'OpenDrift - OceanDrift\n2023-01-01 00:00 to 2023-01-01 16:00 UTC (33 steps)'}>, <Figure size 867.688x1100 with 1 Axes>)