No stranding

import numpy as np
from opendrift import test_data_folder as tdf
from opendrift.readers import reader_netCDF_CF_generic
from opendrift.readers import reader_ROMS_native
from opendrift.models.oceandrift import OceanDrift

o = OceanDrift(loglevel=20)  # Set loglevel to 0 for debug information
o.set_config('drift:max_speed', 3)

# This example works better using hourly input from Thredds than the daily data from test folder
reader_current = reader_netCDF_CF_generic.Reader('https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml')
#reader_current = reader_ROMS_native.Reader(tdf +
#    '2Feb2016_Nordic_sigma_3d/Nordic-4km_SLEVELS_avg_00_subset2Feb2016.nc')

o.add_reader([reader_current])
o.set_config('general:coastline_action', 'previous')

07:31:16 INFO    opendrift:513: OpenDriftSimulation initialised (version 1.14.2 / v1.14.2-90-g1dd1995)
07:31:16 INFO    opendrift.readers:61: Opening file with xr.open_dataset
07:31:19 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}

Seeding elements on a grid

lons = np.linspace(12, 14.5, 30)
lats = np.linspace(67.5, 68.5, 30)
lons, lats = np.meshgrid(lons, lats)
lon = lons.ravel()
lat = lats.ravel()

time = reader_current.start_time
o.seed_elements(lon, lat, radius=0, number=30*30, time=time)

o.run(steps=24*2, time_step=3600)

07:31:19 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
07:31:23 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
07:31:23 INFO    opendrift.models.basemodel.environment:232:    x_wind: 0.000000
07:31:23 INFO    opendrift.models.basemodel.environment:232:    y_wind: 0.000000
07:31:23 INFO    opendrift.models.basemodel.environment:232:    upward_sea_water_velocity: 0.000000
07:31:23 INFO    opendrift.models.basemodel.environment:232:    ocean_vertical_diffusivity: 0.000000
07:31:23 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_significant_height: 0.000000
07:31:23 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
07:31:23 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
07:31:23 INFO    opendrift.models.basemodel.environment:232:    ocean_mixed_layer_thickness: 50.000000
07:31:23 INFO    opendrift:1732: Skipping environment variable ocean_vertical_diffusivity because of condition ['drift:vertical_mixing', 'is', False]
07:31:23 INFO    opendrift:1732: Skipping environment variable ocean_mixed_layer_thickness because of condition ['drift:vertical_mixing', 'is', False]
07:31:23 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']))
07:31:23 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']))
07:31:23 INFO    opendrift:1751: Storing previous values of environment variable sea_surface_height because of condition ['drift:vertical_advection', 'is', True]
07:31:23 INFO    opendrift:899: Using existing reader for land_binary_mask
07:31:25 INFO    opendrift:930: Moving 81 out of 900 points from land to water
07:31:25 INFO    opendrift:2035: 2023-01-01 00:00:00 - step 1 of 48 - 900 active elements (0 deactivated)
07:31:26 INFO    opendrift:2035: 2023-01-01 01:00:00 - step 2 of 48 - 900 active elements (0 deactivated)
07:31:26 INFO    opendrift:2035: 2023-01-01 02:00:00 - step 3 of 48 - 900 active elements (0 deactivated)
07:31:27 INFO    opendrift:2035: 2023-01-01 03:00:00 - step 4 of 48 - 900 active elements (0 deactivated)
07:31:27 INFO    opendrift:2035: 2023-01-01 04:00:00 - step 5 of 48 - 900 active elements (0 deactivated)
07:31:28 INFO    opendrift:2035: 2023-01-01 05:00:00 - step 6 of 48 - 900 active elements (0 deactivated)
07:31:29 INFO    opendrift:2035: 2023-01-01 06:00:00 - step 7 of 48 - 900 active elements (0 deactivated)
07:31:29 INFO    opendrift:2035: 2023-01-01 07:00:00 - step 8 of 48 - 900 active elements (0 deactivated)
07:31:30 INFO    opendrift:2035: 2023-01-01 08:00:00 - step 9 of 48 - 900 active elements (0 deactivated)
07:31:31 INFO    opendrift:2035: 2023-01-01 09:00:00 - step 10 of 48 - 900 active elements (0 deactivated)
07:31:31 INFO    opendrift:2035: 2023-01-01 10:00:00 - step 11 of 48 - 900 active elements (0 deactivated)
07:31:32 INFO    opendrift:2035: 2023-01-01 11:00:00 - step 12 of 48 - 900 active elements (0 deactivated)
07:31:32 INFO    opendrift:2035: 2023-01-01 12:00:00 - step 13 of 48 - 900 active elements (0 deactivated)
07:31:33 INFO    opendrift:2035: 2023-01-01 13:00:00 - step 14 of 48 - 900 active elements (0 deactivated)
07:31:34 INFO    opendrift:2035: 2023-01-01 14:00:00 - step 15 of 48 - 900 active elements (0 deactivated)
07:31:34 INFO    opendrift:2035: 2023-01-01 15:00:00 - step 16 of 48 - 900 active elements (0 deactivated)
07:31:35 INFO    opendrift:2035: 2023-01-01 16:00:00 - step 17 of 48 - 900 active elements (0 deactivated)
07:31:36 INFO    opendrift:2035: 2023-01-01 17:00:00 - step 18 of 48 - 900 active elements (0 deactivated)
07:31:36 INFO    opendrift:2035: 2023-01-01 18:00:00 - step 19 of 48 - 900 active elements (0 deactivated)
07:31:37 INFO    opendrift:2035: 2023-01-01 19:00:00 - step 20 of 48 - 900 active elements (0 deactivated)
07:31:37 INFO    opendrift:2035: 2023-01-01 20:00:00 - step 21 of 48 - 900 active elements (0 deactivated)
07:31:38 INFO    opendrift:2035: 2023-01-01 21:00:00 - step 22 of 48 - 900 active elements (0 deactivated)
07:31:39 INFO    opendrift:2035: 2023-01-01 22:00:00 - step 23 of 48 - 900 active elements (0 deactivated)
07:31:39 INFO    opendrift:2035: 2023-01-01 23:00:00 - step 24 of 48 - 900 active elements (0 deactivated)
07:31:40 INFO    opendrift:2035: 2023-01-02 00:00:00 - step 25 of 48 - 900 active elements (0 deactivated)
07:31:41 INFO    opendrift:2035: 2023-01-02 01:00:00 - step 26 of 48 - 900 active elements (0 deactivated)
07:31:42 INFO    opendrift:2035: 2023-01-02 02:00:00 - step 27 of 48 - 900 active elements (0 deactivated)
07:31:42 INFO    opendrift:2035: 2023-01-02 03:00:00 - step 28 of 48 - 900 active elements (0 deactivated)
07:31:43 INFO    opendrift:2035: 2023-01-02 04:00:00 - step 29 of 48 - 900 active elements (0 deactivated)
07:31:43 INFO    opendrift:2035: 2023-01-02 05:00:00 - step 30 of 48 - 900 active elements (0 deactivated)
07:31:44 INFO    opendrift:2035: 2023-01-02 06:00:00 - step 31 of 48 - 900 active elements (0 deactivated)
07:31:45 INFO    opendrift:2035: 2023-01-02 07:00:00 - step 32 of 48 - 900 active elements (0 deactivated)
07:31:45 INFO    opendrift:2035: 2023-01-02 08:00:00 - step 33 of 48 - 900 active elements (0 deactivated)
07:31:46 INFO    opendrift:2035: 2023-01-02 09:00:00 - step 34 of 48 - 900 active elements (0 deactivated)
07:31:46 INFO    opendrift:2035: 2023-01-02 10:00:00 - step 35 of 48 - 900 active elements (0 deactivated)
07:31:47 INFO    opendrift:2035: 2023-01-02 11:00:00 - step 36 of 48 - 900 active elements (0 deactivated)
07:31:48 INFO    opendrift:2035: 2023-01-02 12:00:00 - step 37 of 48 - 900 active elements (0 deactivated)
07:31:48 INFO    opendrift:2035: 2023-01-02 13:00:00 - step 38 of 48 - 900 active elements (0 deactivated)
07:31:49 INFO    opendrift:2035: 2023-01-02 14:00:00 - step 39 of 48 - 900 active elements (0 deactivated)
07:31:49 INFO    opendrift:2035: 2023-01-02 15:00:00 - step 40 of 48 - 900 active elements (0 deactivated)
07:31:50 INFO    opendrift:2035: 2023-01-02 16:00:00 - step 41 of 48 - 900 active elements (0 deactivated)
07:31:51 INFO    opendrift:2035: 2023-01-02 17:00:00 - step 42 of 48 - 900 active elements (0 deactivated)
07:31:51 INFO    opendrift:2035: 2023-01-02 18:00:00 - step 43 of 48 - 900 active elements (0 deactivated)
07:31:52 INFO    opendrift:2035: 2023-01-02 19:00:00 - step 44 of 48 - 900 active elements (0 deactivated)
07:31:52 INFO    opendrift:2035: 2023-01-02 20:00:00 - step 45 of 48 - 900 active elements (0 deactivated)
07:31:53 INFO    opendrift:2035: 2023-01-02 21:00:00 - step 46 of 48 - 900 active elements (0 deactivated)
07:31:54 INFO    opendrift:2035: 2023-01-02 22:00:00 - step 47 of 48 - 900 active elements (0 deactivated)
07:31:54 INFO    opendrift:2035: 2023-01-02 23:00:00 - step 48 of 48 - 900 active elements (0 deactivated)

<xarray.Dataset> Size: 4MB
Dimensions:                                   (trajectory: 900, time: 49)
Coordinates:
  * trajectory                                (trajectory) int64 7kB 0 1 ... 899
  * time                                      (time) datetime64[ns] 392B 2023...
Data variables: (12/21)
    status                                    (trajectory, time) float32 176kB ...
    moving                                    (trajectory, time) float32 176kB ...
    age_seconds                               (trajectory, time) float32 176kB ...
    origin_marker                             (trajectory, time) float32 176kB ...
    lon                                       (trajectory, time) float32 176kB ...
    lat                                       (trajectory, time) float32 176kB ...
    ...                                        ...
    upward_sea_water_velocity                 (trajectory, time) float32 176kB ...
    sea_surface_wave_significant_height       (trajectory, time) float32 176kB ...
    sea_surface_wave_stokes_drift_x_velocity  (trajectory, time) float32 176kB ...
    sea_surface_wave_stokes_drift_y_velocity  (trajectory, time) float32 176kB ...
    sea_floor_depth_below_sea_level           (trajectory, time) float32 176kB ...
    land_binary_mask                          (trajectory, time) float32 176kB ...
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: 900
  • time: 49
• Coordinates: (2)
  • trajectory
    (trajectory)
    int64
    0 1 2 3 4 5 ... 895 896 897 898 899

    cf_role :

    trajectory_id

    dtype :

    <class 'numpy.int32'>

    array([  0,   1,   2, ..., 897, 898, 899], shape=(900,))

  • time
    (time)
    datetime64[ns]
    2023-01-01 ... 2023-01-03

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2023-01-01T00:00:00.000000000', '2023-01-01T01:00:00.000000000',
           '2023-01-01T02:00:00.000000000', '2023-01-01T03:00:00.000000000',
           '2023-01-01T04:00:00.000000000', '2023-01-01T05:00:00.000000000',
           '2023-01-01T06:00:00.000000000', '2023-01-01T07:00:00.000000000',
           '2023-01-01T08:00:00.000000000', '2023-01-01T09:00:00.000000000',
           '2023-01-01T10:00:00.000000000', '2023-01-01T11:00:00.000000000',
           '2023-01-01T12:00:00.000000000', '2023-01-01T13:00:00.000000000',
           '2023-01-01T14:00:00.000000000', '2023-01-01T15:00:00.000000000',
           '2023-01-01T16:00:00.000000000', '2023-01-01T17:00:00.000000000',
           '2023-01-01T18:00:00.000000000', '2023-01-01T19:00:00.000000000',
           '2023-01-01T20:00:00.000000000', '2023-01-01T21:00:00.000000000',
           '2023-01-01T22:00:00.000000000', '2023-01-01T23:00:00.000000000',
           '2023-01-02T00:00:00.000000000', '2023-01-02T01:00:00.000000000',
           '2023-01-02T02:00:00.000000000', '2023-01-02T03:00:00.000000000',
           '2023-01-02T04:00:00.000000000', '2023-01-02T05:00:00.000000000',
           '2023-01-02T06:00:00.000000000', '2023-01-02T07:00:00.000000000',
           '2023-01-02T08:00:00.000000000', '2023-01-02T09:00:00.000000000',
           '2023-01-02T10:00:00.000000000', '2023-01-02T11:00:00.000000000',
           '2023-01-02T12:00:00.000000000', '2023-01-02T13:00:00.000000000',
           '2023-01-02T14:00:00.000000000', '2023-01-02T15:00:00.000000000',
           '2023-01-02T16:00:00.000000000', '2023-01-02T17:00:00.000000000',
           '2023-01-02T18:00:00.000000000', '2023-01-02T19:00:00.000000000',
           '2023-01-02T20:00:00.000000000', '2023-01-02T21:00:00.000000000',
           '2023-01-02T22:00:00.000000000', '2023-01-02T23:00:00.000000000',
           '2023-01-03T00:00:00.000000000'], 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=(900, 49), 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=(900, 49), dtype=float32)

  • age_seconds
    (trajectory, time)
    float32
    0.0 3.6e+03 ... 1.692e+05 1.728e+05

    dtype :

    <class 'numpy.float32'>

    units :

    s

    minval :

    0.0

    maxval :

    172800.0

    array([[     0.,   3600.,   7200., ..., 165600., 169200., 172800.],
           [     0.,   3600.,   7200., ..., 165600., 169200., 172800.],
           [     0.,   3600.,   7200., ..., 165600., 169200., 172800.],
           ...,
           [     0.,   3600.,   7200., ..., 165600., 169200., 172800.],
           [     0.,   3600.,   7200., ..., 165600., 169200., 172800.],
           [     0.,   3600.,   7200., ..., 165600., 169200., 172800.]],
          shape=(900, 49), 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=(900, 49), dtype=float32)

  • lon
    (trajectory, time)
    float32
    12.0 12.03 12.05 ... 14.7 14.7

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    12.0

    maxval :

    15.03666

    array([[12.       , 12.0303545, 12.052847 , ..., 12.482344 , 12.470093 ,
            12.457545 ],
           [12.086206 , 12.118613 , 12.149753 , ..., 12.606239 , 12.592639 ,
            12.578894 ],
           [12.172414 , 12.202872 , 12.232885 , ..., 12.684913 , 12.6708975,
            12.656663 ],
           ...,
           [14.327586 , 14.341576 , 14.356925 , ..., 14.687427 , 14.682342 ,
            14.676968 ],
           [14.413794 , 14.425592 , 14.438937 , ..., 14.704156 , 14.699092 ,
            14.693747 ],
           [14.5      , 14.509222 , 14.520284 , ..., 14.708705 , 14.702928 ,
            14.696759 ]], shape=(900, 49), dtype=float32)

  • lat
    (trajectory, time)
    float32
    67.5 67.5 67.49 ... 68.5 68.5 68.5

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    67.41997

    maxval :

    68.75942

    array([[67.5     , 67.496376, 67.492165, ..., 67.458916, 67.45654 ,
            67.45368 ],
           [67.5     , 67.497665, 67.48978 , ..., 67.43649 , 67.43382 ,
            67.43082 ],
           [67.5     , 67.49723 , 67.49089 , ..., 67.43685 , 67.433685,
            67.43034 ],
           ...,
           [68.5     , 68.50105 , 68.50127 , ..., 68.50948 , 68.50975 ,
            68.51036 ],
           [68.5     , 68.50193 , 68.50308 , ..., 68.51386 , 68.51398 ,
            68.514435],
           [68.5     , 68.50218 , 68.50367 , ..., 68.49854 , 68.4988  ,
            68.49952 ]], shape=(900, 49), 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=(900, 49), 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=(900, 49), 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=(900, 49), 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=(900, 49), dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    0.3603 0.267 ... -0.07011 -0.07011

    minval :

    -0.5585474

    maxval :

    0.6893235

    array([[ 0.36027595,  0.26701906,  0.20259352, ..., -0.14564475,
            -0.14919741, -0.14919741],
           [ 0.3846205 ,  0.36970308,  0.30899823, ..., -0.16184784,
            -0.16359709, -0.16359709],
           [ 0.361504  ,  0.35630798,  0.31103233, ..., -0.1667942 ,
            -0.16941494, -0.16941494],
           ...,
           [ 0.1589977 ,  0.17444433,  0.1793775 , ..., -0.05777307,
            -0.06105062, -0.06105062],
           [ 0.13409449,  0.15164994,  0.16059501, ..., -0.05752146,
            -0.06072373, -0.06072373],
           [ 0.10480703,  0.12570198,  0.139096  , ..., -0.06567191,
            -0.07011269, -0.07011269]], shape=(900, 49), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    -0.1122 -0.1305 ... 0.02218 0.02218

    minval :

    -0.60228515

    maxval :

    0.5603876

    array([[-0.11217061, -0.13048893, -0.19458356, ..., -0.07355474,
            -0.08847616, -0.08847616],
           [-0.07227591, -0.24423034, -0.28095156, ..., -0.08269477,
            -0.09319704, -0.09319704],
           [-0.08576874, -0.19634315, -0.24997956, ..., -0.09825044,
            -0.10343478, -0.10343478],
           ...,
           [ 0.03263704,  0.00667581, -0.01834369, ...,  0.0083685 ,
             0.01883854,  0.01883854],
           [ 0.05976202,  0.03586343,  0.01175819, ...,  0.00369112,
             0.01419422,  0.01419422],
           [ 0.06756789,  0.0460512 ,  0.02240106, ...,  0.00814261,
             0.02218349,  0.02218349]], shape=(900, 49), dtype=float32)

  • sea_surface_height
    (trajectory, time)
    float32
    -0.8262 -0.8473 ... -0.1973 -0.1973

    minval :

    -0.9396711

    maxval :

    0.6970283

    array([[-0.8261687 , -0.8472681 , -0.7013644 , ...,  0.00215531,
            -0.29847494, -0.29847494],
           [-0.8366683 , -0.84892887, -0.70252186, ...,  0.00370781,
            -0.30031618, -0.30031618],
           [-0.83916926, -0.85350937, -0.7057294 , ...,  0.0059844 ,
            -0.30010414, -0.30010414],
           ...,
           [-0.67553747, -0.7366561 , -0.6580994 , ...,  0.05239202,
            -0.19719076, -0.19719076],
           [-0.6755518 , -0.73687756, -0.6581909 , ...,  0.05303105,
            -0.19713588, -0.19713588],
           [-0.67404515, -0.73604405, -0.65786594, ...,  0.0517599 ,
            -0.19731703, -0.19731703]], shape=(900, 49), dtype=float32)

  • x_wind
    (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=(900, 49), dtype=float32)

  • y_wind
    (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=(900, 49), dtype=float32)

  • upward_sea_water_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=(900, 49), dtype=float32)

  • sea_surface_wave_significant_height
    (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=(900, 49), 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=(900, 49), 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=(900, 49), dtype=float32)

  • sea_floor_depth_below_sea_level
    (trajectory, time)
    float32
    37.83 34.16 37.26 ... 104.7 104.7

    minval :

    13.001983

    maxval :

    403.03845

    array([[ 37.83103 ,  34.158607,  37.256203, ..., 191.62172 , 190.19409 ,
            190.19409 ],
           [ 35.498   ,  49.81222 ,  71.82157 , ..., 223.342   , 221.96979 ,
            221.96979 ],
           [ 65.07617 ,  78.388374, 100.82862 , ..., 237.95695 , 236.74721 ,
            236.74721 ],
           ...,
           [ 79.739395,  82.83348 ,  85.09755 , ..., 106.31921 , 106.40693 ,
            106.40693 ],
           [ 79.532364,  80.13223 ,  81.102455, ..., 105.89615 , 106.01266 ,
            106.01266 ],
           [ 87.423256,  88.78412 ,  90.753784, ..., 103.68075 , 104.7123  ,
            104.7123  ]], shape=(900, 49), 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=(900, 49), dtype=float32)

• Indexes: (2)
  • trajectory
    PandasIndex

    PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,
           ...
           890, 891, 892, 893, 894, 895, 896, 897, 898, 899],
          dtype='int64', name='trajectory', length=900))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2023-01-01 00:00:00', '2023-01-01 01:00:00',
                   '2023-01-01 02:00:00', '2023-01-01 03:00:00',
                   '2023-01-01 04:00:00', '2023-01-01 05:00:00',
                   '2023-01-01 06:00:00', '2023-01-01 07:00:00',
                   '2023-01-01 08:00:00', '2023-01-01 09:00:00',
                   '2023-01-01 10:00:00', '2023-01-01 11:00:00',
                   '2023-01-01 12:00:00', '2023-01-01 13:00:00',
                   '2023-01-01 14:00:00', '2023-01-01 15:00:00',
                   '2023-01-01 16:00:00', '2023-01-01 17:00:00',
                   '2023-01-01 18:00:00', '2023-01-01 19:00:00',
                   '2023-01-01 20:00:00', '2023-01-01 21:00:00',
                   '2023-01-01 22:00:00', '2023-01-01 23:00:00',
                   '2023-01-02 00:00:00', '2023-01-02 01:00:00',
                   '2023-01-02 02:00:00', '2023-01-02 03:00:00',
                   '2023-01-02 04:00:00', '2023-01-02 05:00:00',
                   '2023-01-02 06:00:00', '2023-01-02 07:00:00',
                   '2023-01-02 08:00:00', '2023-01-02 09:00:00',
                   '2023-01-02 10:00:00', '2023-01-02 11:00:00',
                   '2023-01-02 12:00:00', '2023-01-02 13:00:00',
                   '2023-01-02 14:00:00', '2023-01-02 15:00:00',
                   '2023-01-02 16:00:00', '2023-01-02 17:00:00',
                   '2023-01-02 18:00:00', '2023-01-02 19:00:00',
                   '2023-01-02 20:00:00', '2023-01-02 21:00:00',
                   '2023-01-02 22:00:00', '2023-01-02 23:00:00',
                   '2023-01-03 00:00:00'],
                  dtype='datetime64[ns]', name='time', freq='h'))

• 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 2025-07-17 07:31:23.723078

  date_created :

  2025-07-17T07:31:23.723091

  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/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'global_landmask'])

  time_coverage_start :

  2023-01-01 00:00:00

  time_step_calculation :

  1:00:00

  time_step_output :

  1:00:00

  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 :

  None

  config_general:use_auto_landmask :

  True

  config_drift:current_uncertainty :

  0

  config_drift:current_uncertainty_uniform :

  0

  config_drift:max_speed :

  3.0

  config_readers:max_number_of_fails :

  1

  config_general:simulation_name :

  config_general:coastline_action :

  previous

  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 :

  2025-07-17 07:31:25.322332

  reader_x_sea_water_velocity :

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

  reader_y_sea_water_velocity :

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

  reader_sea_surface_height :

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

  reader_x_wind :

  0

  reader_y_wind :

  0

  reader_upward_sea_water_velocity :

  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/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml']

  reader_land_binary_mask :

  ['global_landmask']

  time_coverage_end :

  2023-01-03 00:00:00

  time_coverage_duration :

  P2DT0H0M0S

  time_coverage_resolution :

  P0DT1H0M0S

  performance :

  -------------------- Reader performance: -------------------- https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml 0:00:28.7 total 0:00:00.0 preparing 0:00:28.6 reading 0:00:00.1 interpolation 0:00:00.0 interpolation_time 0:00:00.0 rotating vectors 0:00:00.0 masking -------------------- global_landmask 0:00:01.6 total 0:00:00.0 preparing 0:00:01.6 reading 0:00:00.0 masking -------------------- Performance: 38.8 total time 7.0 configuration 1.6 preparing main loop 1.5 moving elements to ocean 30.1 main loop 0.0 updating elements 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  67.41997

  geospatial_lat_max :

  68.75942

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  12.0

  geospatial_lon_max :

  15.03666

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:00:38.871308

  geospatial_vertical_min :

  0.0

  geospatial_vertical_max :

  0.0

  geospatial_vertical_positive :

  up

Print and plot results

print(o)
o.plot()
#o.plot(background=['x_sea_water_velocity', 'y_sea_water_velocity'])
o.animation()

===========================
--------------------
Reader performance:
--------------------
https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
 0:00:28.7  total
 0:00:00.0  preparing
 0:00:28.6  reading
 0:00:00.1  interpolation
 0:00:00.0  interpolation_time
 0:00:00.0  rotating vectors
 0:00:00.0  masking
--------------------
global_landmask
 0:00:01.6  total
 0:00:00.0  preparing
 0:00:01.6  reading
 0:00:00.0  masking
--------------------
Performance:
   38.8 total time
    7.0 configuration
    1.6 preparing main loop
      1.5 moving elements to ocean
   30.1 main loop
      0.0 updating elements
    0.0 cleaning up
--------------------
===========================
Model:  OceanDrift     (OpenDrift version 1.14.2)
        900 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/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
  -----
  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
  upward_sea_water_velocity
  x_wind
  y_wind

Discarded readers:

Time:
        Start: 2023-01-01 00:00:00 UTC
        Present: 2023-01-03 00:00:00 UTC
        Calculation steps: 48 * 1:00:00 - total time: 2 days, 0:00:00
        Output steps: 49 * 1:00:00
===========================

07:32:10 INFO    opendrift:4553: Saving animation to /root/project/docs/source/gallery/animations/example_coastline_0.gif...
07:32:43 INFO    opendrift:2994: Time to make animation: 0:00:33.685528