Sediment drift from Glomma river outlet

from datetime import timedelta, datetime
from opendrift.models.sedimentdrift import SedimentDrift

o = SedimentDrift(loglevel=20)  # 0 for debug output

if False:  # Using constant south-westwards current and wind
    o.set_config('environment:fallback:x_sea_water_velocity', -.05)
    o.set_config('environment:fallback:y_sea_water_velocity', -.1)
    o.set_config('environment:fallback:y_wind', -6)
    o.set_config('environment:fallback:x_wind', -2)
    o.set_config('environment:fallback:sea_floor_depth_below_sea_level', 100)  # 100m depth
else:  # Using live data from Thredds
    o.add_readers_from_list([
        'https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be'])

16:11:10 INFO    opendrift:513: OpenDriftSimulation initialised (version 1.14.2 / v1.14.2-82-g86a40e4)

Adding some diffusion

o.set_config('drift:current_uncertainty', .2)
o.set_config('drift:wind_uncertainty', 2)
o.set_config('vertical_mixing:diffusivitymodel', 'windspeed_Large1994')
#o.set_config('vertical_mixing:diffusivitymodel', 'environment')

Source of sediments at Glomma river outlet

lat=59.169194
lon=10.962920
o.seed_elements(lon=lon, lat=lat, number=10000,
                time=[datetime.now(), datetime.now()+timedelta(hours=48)],
                terminal_velocity=-.001)  # 1 mm/s settling speed

o.run(time_step=600, time_step_output=1800, duration=timedelta(hours=36))

16:11:10 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
16:11:14 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
16:11:14 INFO    opendrift.models.basemodel.environment:232:    x_sea_water_velocity: 0.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    y_sea_water_velocity: 0.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    sea_surface_height: 0.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    upward_sea_water_velocity: 0.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    x_wind: 0.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    y_wind: 0.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_period_at_variance_spectral_density_maximum: 0.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    ocean_vertical_diffusivity: 0.020000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    ocean_mixed_layer_thickness: 50.000000
16:11:14 INFO    opendrift.models.basemodel.environment:232:    sea_floor_depth_below_sea_level: 10000.000000
16:11:14 INFO    opendrift:1732: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
16:11:14 INFO    opendrift:1732: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
16:11:14 INFO    opendrift:889: Using existing reader for land_binary_mask
16:11:14 INFO    opendrift:918: All points are in ocean
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16:11:14 INFO    opendrift.readers:61: Opening file with xr.open_dataset
16:11:16 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'X', 'y': 'Y', 'z': 'depth', 'time': 'time'}
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16:12:04 INFO    opendrift:2015: 2025-07-03 18:11:10.169116 - step 157 of 216 - 5451 active elements (0 deactivated)
16:12:04 INFO    opendrift:2015: 2025-07-03 18:21:10.169116 - step 158 of 216 - 5486 active elements (0 deactivated)
16:12:04 INFO    opendrift:2015: 2025-07-03 18:31:10.169116 - step 159 of 216 - 5521 active elements (0 deactivated)
16:12:04 INFO    opendrift:2015: 2025-07-03 18:41:10.169116 - step 160 of 216 - 5556 active elements (0 deactivated)
16:12:04 INFO    opendrift:2015: 2025-07-03 18:51:10.169116 - step 161 of 216 - 5590 active elements (0 deactivated)
16:12:04 INFO    opendrift:2015: 2025-07-03 19:01:10.169116 - step 162 of 216 - 5625 active elements (0 deactivated)
16:12:06 INFO    opendrift:2015: 2025-07-03 19:11:10.169116 - step 163 of 216 - 5660 active elements (0 deactivated)
16:12:06 INFO    opendrift:2015: 2025-07-03 19:21:10.169116 - step 164 of 216 - 5694 active elements (0 deactivated)
16:12:06 INFO    opendrift:2015: 2025-07-03 19:31:10.169116 - step 165 of 216 - 5729 active elements (0 deactivated)
16:12:06 INFO    opendrift:2015: 2025-07-03 19:41:10.169116 - step 166 of 216 - 5764 active elements (0 deactivated)
16:12:06 INFO    opendrift:2015: 2025-07-03 19:51:10.169116 - step 167 of 216 - 5799 active elements (0 deactivated)
16:12:06 INFO    opendrift:2015: 2025-07-03 20:01:10.169116 - step 168 of 216 - 5833 active elements (0 deactivated)
16:12:08 INFO    opendrift:2015: 2025-07-03 20:11:10.169116 - step 169 of 216 - 5868 active elements (0 deactivated)
16:12:08 INFO    opendrift:2015: 2025-07-03 20:21:10.169116 - step 170 of 216 - 5903 active elements (0 deactivated)
16:12:08 INFO    opendrift:2015: 2025-07-03 20:31:10.169116 - step 171 of 216 - 5937 active elements (0 deactivated)
16:12:08 INFO    opendrift:2015: 2025-07-03 20:41:10.169116 - step 172 of 216 - 5972 active elements (0 deactivated)
16:12:09 INFO    opendrift:2015: 2025-07-03 20:51:10.169116 - step 173 of 216 - 6007 active elements (0 deactivated)
16:12:09 INFO    opendrift:2015: 2025-07-03 21:01:10.169116 - step 174 of 216 - 6042 active elements (0 deactivated)
16:12:10 INFO    opendrift:2015: 2025-07-03 21:11:10.169116 - step 175 of 216 - 6076 active elements (0 deactivated)
16:12:10 INFO    opendrift:2015: 2025-07-03 21:21:10.169116 - step 176 of 216 - 6111 active elements (0 deactivated)
16:12:10 INFO    opendrift:2015: 2025-07-03 21:31:10.169116 - step 177 of 216 - 6146 active elements (0 deactivated)
16:12:10 INFO    opendrift:2015: 2025-07-03 21:41:10.169116 - step 178 of 216 - 6180 active elements (0 deactivated)
16:12:11 INFO    opendrift:2015: 2025-07-03 21:51:10.169116 - step 179 of 216 - 6215 active elements (0 deactivated)
16:12:11 INFO    opendrift:2015: 2025-07-03 22:01:10.169116 - step 180 of 216 - 6250 active elements (0 deactivated)
16:12:12 INFO    opendrift:2015: 2025-07-03 22:11:10.169116 - step 181 of 216 - 6285 active elements (0 deactivated)
16:12:12 INFO    opendrift:2015: 2025-07-03 22:21:10.169116 - step 182 of 216 - 6319 active elements (0 deactivated)
16:12:13 INFO    opendrift:2015: 2025-07-03 22:31:10.169116 - step 183 of 216 - 6354 active elements (0 deactivated)
16:12:13 INFO    opendrift:2015: 2025-07-03 22:41:10.169116 - step 184 of 216 - 6389 active elements (0 deactivated)
16:12:13 INFO    opendrift:2015: 2025-07-03 22:51:10.169116 - step 185 of 216 - 6423 active elements (0 deactivated)
16:12:13 INFO    opendrift:2015: 2025-07-03 23:01:10.169116 - step 186 of 216 - 6458 active elements (0 deactivated)
16:12:14 INFO    opendrift:2015: 2025-07-03 23:11:10.169116 - step 187 of 216 - 6493 active elements (0 deactivated)
16:12:15 INFO    opendrift:2015: 2025-07-03 23:21:10.169116 - step 188 of 216 - 6528 active elements (0 deactivated)
16:12:15 INFO    opendrift:2015: 2025-07-03 23:31:10.169116 - step 189 of 216 - 6562 active elements (0 deactivated)
16:12:15 INFO    opendrift:2015: 2025-07-03 23:41:10.169116 - step 190 of 216 - 6597 active elements (0 deactivated)
16:12:15 INFO    opendrift:2015: 2025-07-03 23:51:10.169116 - step 191 of 216 - 6632 active elements (0 deactivated)
16:12:15 INFO    opendrift:2015: 2025-07-04 00:01:10.169116 - step 192 of 216 - 6667 active elements (0 deactivated)
16:12:17 INFO    opendrift:2015: 2025-07-04 00:11:10.169116 - step 193 of 216 - 6701 active elements (0 deactivated)
16:12:17 INFO    opendrift:2015: 2025-07-04 00:21:10.169116 - step 194 of 216 - 6736 active elements (0 deactivated)
16:12:17 INFO    opendrift:2015: 2025-07-04 00:31:10.169116 - step 195 of 216 - 6771 active elements (0 deactivated)
16:12:17 INFO    opendrift:2015: 2025-07-04 00:41:10.169116 - step 196 of 216 - 6805 active elements (0 deactivated)
16:12:17 INFO    opendrift:2015: 2025-07-04 00:51:10.169116 - step 197 of 216 - 6840 active elements (0 deactivated)
16:12:18 INFO    opendrift:2015: 2025-07-04 01:01:10.169116 - step 198 of 216 - 6875 active elements (0 deactivated)
16:12:19 INFO    opendrift:2015: 2025-07-04 01:11:10.169116 - step 199 of 216 - 6910 active elements (0 deactivated)
16:12:19 INFO    opendrift:2015: 2025-07-04 01:21:10.169116 - step 200 of 216 - 6944 active elements (0 deactivated)
16:12:19 INFO    opendrift:2015: 2025-07-04 01:31:10.169116 - step 201 of 216 - 6979 active elements (0 deactivated)
16:12:20 INFO    opendrift:2015: 2025-07-04 01:41:10.169116 - step 202 of 216 - 7014 active elements (0 deactivated)
16:12:20 INFO    opendrift:2015: 2025-07-04 01:51:10.169116 - step 203 of 216 - 7048 active elements (0 deactivated)
16:12:20 INFO    opendrift:2015: 2025-07-04 02:01:10.169116 - step 204 of 216 - 7083 active elements (0 deactivated)
16:12:21 INFO    opendrift:2015: 2025-07-04 02:11:10.169116 - step 205 of 216 - 7118 active elements (0 deactivated)
16:12:22 INFO    opendrift:2015: 2025-07-04 02:21:10.169116 - step 206 of 216 - 7153 active elements (0 deactivated)
16:12:22 INFO    opendrift:2015: 2025-07-04 02:31:10.169116 - step 207 of 216 - 7187 active elements (0 deactivated)
16:12:22 INFO    opendrift:2015: 2025-07-04 02:41:10.169116 - step 208 of 216 - 7222 active elements (0 deactivated)
16:12:22 INFO    opendrift:2015: 2025-07-04 02:51:10.169116 - step 209 of 216 - 7257 active elements (0 deactivated)
16:12:22 INFO    opendrift:2015: 2025-07-04 03:01:10.169116 - step 210 of 216 - 7291 active elements (0 deactivated)
16:12:24 INFO    opendrift:2015: 2025-07-04 03:11:10.169116 - step 211 of 216 - 7326 active elements (0 deactivated)
16:12:24 INFO    opendrift:2015: 2025-07-04 03:21:10.169116 - step 212 of 216 - 7361 active elements (0 deactivated)
16:12:24 INFO    opendrift:2015: 2025-07-04 03:31:10.169116 - step 213 of 216 - 7396 active elements (0 deactivated)
16:12:24 INFO    opendrift:2015: 2025-07-04 03:41:10.169116 - step 214 of 216 - 7430 active elements (0 deactivated)
16:12:24 INFO    opendrift:2015: 2025-07-04 03:51:10.169116 - step 215 of 216 - 7465 active elements (0 deactivated)
16:12:24 INFO    opendrift:2015: 2025-07-04 04:01:10.169116 - step 216 of 216 - 7500 active elements (0 deactivated)
16:12:26 INFO    opendrift:2122: Removing 2500 unseeded elements

<xarray.Dataset> Size: 55MB
Dimensions:                                                                              (
                                                                                          trajectory: 7500,
                                                                                          time: 73)
Coordinates:
  * trajectory                                                                           (trajectory) int64 60kB ...
  * time                                                                                 (time) datetime64[ns] 584B ...
Data variables: (12/25)
    status                                                                               (trajectory, time) float32 2MB ...
    moving                                                                               (trajectory, time) float32 2MB ...
    age_seconds                                                                          (trajectory, time) float32 2MB ...
    origin_marker                                                                        (trajectory, time) float32 2MB ...
    lon                                                                                  (trajectory, time) float32 2MB ...
    lat                                                                                  (trajectory, time) float32 2MB ...
    ...                                                                                   ...
    sea_surface_wave_period_at_variance_spectral_density_maximum                         (trajectory, time) float32 2MB ...
    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment  (trajectory, time) float32 2MB ...
    land_binary_mask                                                                     (trajectory, time) float32 2MB ...
    ocean_vertical_diffusivity                                                           (trajectory, time) float32 2MB ...
    ocean_mixed_layer_thickness                                                          (trajectory, time) float32 2MB ...
    sea_floor_depth_below_sea_level                                                      (trajectory, time) float32 2MB ...
Attributes: (12/124)
    Conventions:                                                             ...
    standard_name_vocabulary:                                                ...
    featureType:                                                             ...
    title:                                                                   ...
    summary:                                                                 ...
    keywords:                                                                ...
    ...                                                                                                               ...
    geospatial_lon_units:                                                    ...
    geospatial_lon_resolution:                                               ...
    runtime:                                                                 ...
    geospatial_vertical_min:                                                 ...
    geospatial_vertical_max:                                                 ...
    geospatial_vertical_positive:                                            ...

xarray.Dataset

• Dimensions:
  • trajectory: 7500
  • time: 73
• Coordinates: (2)
  • trajectory
    (trajectory)
    int64
    0 1 2 3 4 ... 7496 7497 7498 7499

    cf_role :

    trajectory_id

    dtype :

    <class 'numpy.int32'>

    array([   0,    1,    2, ..., 7497, 7498, 7499], shape=(7500,))

  • time
    (time)
    datetime64[ns]
    2025-07-02T16:11:10.169116 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2025-07-02T16:11:10.169116000', '2025-07-02T16:41:10.169116000',
           '2025-07-02T17:11:10.169116000', '2025-07-02T17:41:10.169116000',
           '2025-07-02T18:11:10.169116000', '2025-07-02T18:41:10.169116000',
           '2025-07-02T19:11:10.169116000', '2025-07-02T19:41:10.169116000',
           '2025-07-02T20:11:10.169116000', '2025-07-02T20:41:10.169116000',
           '2025-07-02T21:11:10.169116000', '2025-07-02T21:41:10.169116000',
           '2025-07-02T22:11:10.169116000', '2025-07-02T22:41:10.169116000',
           '2025-07-02T23:11:10.169116000', '2025-07-02T23:41:10.169116000',
           '2025-07-03T00:11:10.169116000', '2025-07-03T00:41:10.169116000',
           '2025-07-03T01:11:10.169116000', '2025-07-03T01:41:10.169116000',
           '2025-07-03T02:11:10.169116000', '2025-07-03T02:41:10.169116000',
           '2025-07-03T03:11:10.169116000', '2025-07-03T03:41:10.169116000',
           '2025-07-03T04:11:10.169116000', '2025-07-03T04:41:10.169116000',
           '2025-07-03T05:11:10.169116000', '2025-07-03T05:41:10.169116000',
           '2025-07-03T06:11:10.169116000', '2025-07-03T06:41:10.169116000',
           '2025-07-03T07:11:10.169116000', '2025-07-03T07:41:10.169116000',
           '2025-07-03T08:11:10.169116000', '2025-07-03T08:41:10.169116000',
           '2025-07-03T09:11:10.169116000', '2025-07-03T09:41:10.169116000',
           '2025-07-03T10:11:10.169116000', '2025-07-03T10:41:10.169116000',
           '2025-07-03T11:11:10.169116000', '2025-07-03T11:41:10.169116000',
           '2025-07-03T12:11:10.169116000', '2025-07-03T12:41:10.169116000',
           '2025-07-03T13:11:10.169116000', '2025-07-03T13:41:10.169116000',
           '2025-07-03T14:11:10.169116000', '2025-07-03T14:41:10.169116000',
           '2025-07-03T15:11:10.169116000', '2025-07-03T15:41:10.169116000',
           '2025-07-03T16:11:10.169116000', '2025-07-03T16:41:10.169116000',
           '2025-07-03T17:11:10.169116000', '2025-07-03T17:41:10.169116000',
           '2025-07-03T18:11:10.169116000', '2025-07-03T18:41:10.169116000',
           '2025-07-03T19:11:10.169116000', '2025-07-03T19:41:10.169116000',
           '2025-07-03T20:11:10.169116000', '2025-07-03T20:41:10.169116000',
           '2025-07-03T21:11:10.169116000', '2025-07-03T21:41:10.169116000',
           '2025-07-03T22:11:10.169116000', '2025-07-03T22:41:10.169116000',
           '2025-07-03T23:11:10.169116000', '2025-07-03T23:41:10.169116000',
           '2025-07-04T00:11:10.169116000', '2025-07-04T00:41:10.169116000',
           '2025-07-04T01:11:10.169116000', '2025-07-04T01:41:10.169116000',
           '2025-07-04T02:11:10.169116000', '2025-07-04T02:41:10.169116000',
           '2025-07-04T03:11:10.169116000', '2025-07-04T03:41:10.169116000',
           '2025-07-04T04:11:10.169116000'], dtype='datetime64[ns]')

• Data variables: (25)
  • status
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... nan nan nan 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.],
           ...,
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.]],
          shape=(7500, 73), dtype=float32)

  • moving
    (trajectory, time)
    float32
    1.0 1.0 1.0 1.0 ... nan nan nan 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.],
           ...,
           [nan, nan, nan, ..., nan, nan,  1.],
           [nan, nan, nan, ..., nan, nan,  1.],
           [nan, nan, nan, ..., nan, nan,  1.]],
          shape=(7500, 73), dtype=float32)

  • age_seconds
    (trajectory, time)
    float32
    0.0 1.8e+03 3.6e+03 ... nan 600.0

    dtype :

    <class 'numpy.float32'>

    units :

    s

    minval :

    0.0

    maxval :

    129600.0

    array([[     0.,   1800.,   3600., ..., 126000., 127800., 129600.],
           [     0.,   1800.,   3600., ..., 126000., 127800., 129600.],
           [     0.,   1800.,   3600., ..., 126000., 127800., 129600.],
           ...,
           [    nan,     nan,     nan, ...,     nan,     nan,    600.],
           [    nan,     nan,     nan, ...,     nan,     nan,    600.],
           [    nan,     nan,     nan, ...,     nan,     nan,    600.]],
          shape=(7500, 73), dtype=float32)

  • origin_marker
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... nan nan nan 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.],
           ...,
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.]],
          shape=(7500, 73), dtype=float32)

  • lon
    (trajectory, time)
    float32
    10.96 10.97 10.98 ... nan nan 10.97

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    10.868587

    maxval :

    11.222743

    array([[10.96292 , 10.9743  , 10.976261, ..., 11.023656, 11.020417,
            11.022403],
           [10.96292 , 10.980344, 10.99186 , ..., 11.016373, 11.020146,
            11.017843],
           [10.96292 , 10.975602, 10.975602, ..., 11.03217 , 11.034031,
            11.034585],
           ...,
           [      nan,       nan,       nan, ...,       nan,       nan,
            10.966384],
           [      nan,       nan,       nan, ...,       nan,       nan,
            10.967611],
           [      nan,       nan,       nan, ...,       nan,       nan,
            10.967931]], shape=(7500, 73), dtype=float32)

  • lat
    (trajectory, time)
    float32
    59.17 59.17 59.17 ... nan nan 59.17

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    58.88173

    maxval :

    59.188717

    array([[59.169193, 59.16896 , 59.169575, ..., 59.14941 , 59.14829 ,
            59.145027],
           [59.169193, 59.170208, 59.16437 , ..., 59.138172, 59.133823,
            59.127037],
           [59.169193, 59.16762 , 59.16762 , ..., 59.13715 , 59.13713 ,
            59.13789 ],
           ...,
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.168934],
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.16889 ],
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.16901 ]], shape=(7500, 73), dtype=float32)

  • z
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... nan nan nan 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.],
           ...,
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.]],
          shape=(7500, 73), dtype=float32)

  • wind_drift_factor
    (trajectory, time)
    float32
    0.02 0.02 0.02 ... nan nan 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],
           ...,
           [ nan,  nan,  nan, ...,  nan,  nan, 0.02],
           [ nan,  nan,  nan, ...,  nan,  nan, 0.02],
           [ nan,  nan,  nan, ...,  nan,  nan, 0.02]],
          shape=(7500, 73), dtype=float32)

  • current_drift_factor
    (trajectory, time)
    float32
    1.0 1.0 1.0 1.0 ... nan nan nan 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.],
           ...,
           [nan, nan, nan, ..., nan, nan,  1.],
           [nan, nan, nan, ..., nan, nan,  1.],
           [nan, nan, nan, ..., nan, nan,  1.]],
          shape=(7500, 73), dtype=float32)

  • terminal_velocity
    (trajectory, time)
    float32
    -0.001 -0.001 -0.001 ... nan -0.001

    dtype :

    <class 'numpy.float32'>

    units :

    m/s

    minval :

    -0.001

    maxval :

    -0.001

    array([[-0.001, -0.001, -0.001, ..., -0.001, -0.001, -0.001],
           [-0.001, -0.001, -0.001, ..., -0.001, -0.001, -0.001],
           [-0.001, -0.001, -0.001, ..., -0.001, -0.001, -0.001],
           ...,
           [   nan,    nan,    nan, ...,    nan,    nan, -0.001],
           [   nan,    nan,    nan, ...,    nan,    nan, -0.001],
           [   nan,    nan,    nan, ...,    nan,    nan, -0.001]],
          shape=(7500, 73), dtype=float32)

  • settled
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... nan nan nan 0.0

    dtype :

    <class 'numpy.uint8'>

    units :

    1

    minval :

    0

    maxval :

    0

    array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],
           [ 0.,  0.,  0., ...,  0.,  0.,  0.],
           [ 0.,  0.,  0., ...,  0.,  0.,  0.],
           ...,
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.]],
          shape=(7500, 73), dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    0.7395 0.5677 ... nan 0.4706

    minval :

    -1.0359321

    maxval :

    1.4409522

    array([[ 0.73953766,  0.56769574,  0.0852454 , ...,  0.11937428,
             0.01604868,  0.08482413],
           [ 0.46675867,  0.41452292,  0.7568981 , ...,  0.18328658,
            -0.11462101, -0.17256515],
           [ 0.5824748 ,  0.68238664,  0.48700443, ...,  0.2270974 ,
             0.09878089,  0.13481317],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.2701399 ],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.36441448],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.47056085]], shape=(7500, 73), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    -0.08335 -0.2888 ... nan -0.06031

    minval :

    -1.3921337

    maxval :

    0.961064

    array([[-0.08335048, -0.28881544, -0.00380983, ..., -0.03948632,
            -0.36265552, -0.06907835],
           [ 0.13143785, -0.12284886, -0.06119114, ..., -0.4561669 ,
            -0.17567776, -0.7001754 ],
           [ 0.1258557 , -0.21205926, -0.25941566, ..., -0.07333618,
             0.12715182, -0.01560301],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.06676447],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.05130355],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.06031302]], shape=(7500, 73), dtype=float32)

  • sea_surface_height
    (trajectory, time)
    float32
    -0.1851 -0.1691 ... nan -0.2474

    minval :

    -0.30135483

    maxval :

    0.100581214

    array([[-0.18505928, -0.16905612, -0.14645098, ..., -0.23312713,
            -0.25009286, -0.2673109 ],
           [-0.18505928, -0.16882217, -0.14495364, ..., -0.2348555 ,
            -0.25340545, -0.2654658 ],
           [-0.18505928, -0.16968521, -0.14663592, ..., -0.23496704,
            -0.2542626 , -0.26664463],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.24739684],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.24739684],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.24739684]], shape=(7500, 73), dtype=float32)

  • upward_sea_water_velocity
    (trajectory, time)
    float32
    8.233e-06 1.281e-05 ... -2.191e-05

    minval :

    -3.3313492e-05

    maxval :

    2.7805314e-05

    array([[ 8.23277696e-06,  1.28088996e-05,  8.63234254e-06, ...,
            -1.28871588e-05, -9.34176478e-06, -7.29382555e-06],
           [ 8.23277696e-06,  1.23108639e-05,  1.04350065e-05, ...,
            -1.28509946e-05, -9.67857795e-06, -7.93183881e-06],
           [ 8.23277696e-06,  1.27989679e-05,  9.97292864e-06, ...,
            -1.28589436e-05, -9.33806768e-06, -7.28513714e-06],
           ...,
           [            nan,             nan,             nan, ...,
                        nan,             nan, -2.19129179e-05],
           [            nan,             nan,             nan, ...,
                        nan,             nan, -2.19129179e-05],
           [            nan,             nan,             nan, ...,
                        nan,             nan, -2.19129179e-05]],
          shape=(7500, 73), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    2.64 -1.046 0.5927 ... nan 0.3547

    minval :

    -9.335823

    maxval :

    16.604181

    array([[ 2.6398234 , -1.045661  ,  0.5926718 , ...,  4.402335  ,
            -0.9266496 ,  0.2720506 ],
           [ 1.4396081 , -0.71228623, -3.1726875 , ...,  2.3952856 ,
             1.1020446 ,  0.96924436],
           [ 3.4604437 , -1.1228274 ,  2.4554462 , ...,  2.3158379 ,
             0.9557241 ,  4.018397  ],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan,  3.0031981 ],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  4.1367927 ],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.3547302 ]], shape=(7500, 73), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    4.965 0.2803 -0.07145 ... nan 1.32

    minval :

    -16.215118

    maxval :

    14.903978

    array([[ 4.964635  ,  0.28033468, -0.07144523, ..., -0.19481489,
             1.1352898 , -2.646274  ],
           [ 0.2501546 , -1.3597717 , -0.8570381 , ..., -1.2513784 ,
            -1.6500304 , -2.7905033 ],
           [-0.41751704, -2.6284719 ,  1.9812775 , ..., -1.151747  ,
            -4.4065447 , -1.889585  ],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.94329774],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.21805237],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  1.3200285 ]], shape=(7500, 73), dtype=float32)

  • sea_surface_wave_stokes_drift_x_velocity
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... nan nan nan 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.],
           ...,
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.]],
          shape=(7500, 73), dtype=float32)

  • sea_surface_wave_stokes_drift_y_velocity
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... nan nan nan 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.],
           ...,
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.]],
          shape=(7500, 73), dtype=float32)

  • sea_surface_wave_period_at_variance_spectral_density_maximum
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... nan nan nan 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.],
           ...,
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.]],
          shape=(7500, 73), dtype=float32)

  • sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
    (trajectory, time)
    float32
    4.805 0.925 0.5101 ... nan 1.168

    minval :

    0.0039774557

    maxval :

    15.429704

    array([[4.804547  , 0.92503864, 0.51008695, ..., 3.7653475 , 1.2521893 ,
            2.273081  ],
           [1.2485359 , 1.3116418 , 2.8081372 , ..., 2.3091807 , 1.695452  ,
            2.5241387 ],
           [2.9782913 , 2.4422925 , 2.6959429 , ..., 2.2100294 , 3.8528044 ,
            3.7942767 ],
           ...,
           [       nan,        nan,        nan, ...,        nan,        nan,
            2.689752  ],
           [       nan,        nan,        nan, ...,        nan,        nan,
            3.539675  ],
           [       nan,        nan,        nan, ...,        nan,        nan,
            1.1679425 ]], shape=(7500, 73), dtype=float32)

  • land_binary_mask
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... nan nan nan 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.],
           ...,
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.],
           [nan, nan, nan, ..., nan, nan,  0.]],
          shape=(7500, 73), dtype=float32)

  • ocean_vertical_diffusivity
    (trajectory, time)
    float32
    0.02 0.02 0.02 ... nan nan 0.02

    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],
           ...,
           [ nan,  nan,  nan, ...,  nan,  nan, 0.02],
           [ nan,  nan,  nan, ...,  nan,  nan, 0.02],
           [ nan,  nan,  nan, ...,  nan,  nan, 0.02]],
          shape=(7500, 73), dtype=float32)

  • ocean_mixed_layer_thickness
    (trajectory, time)
    float32
    50.0 50.0 50.0 ... nan nan 50.0

    minval :

    50.0

    maxval :

    50.0

    array([[50., 50., 50., ..., 50., 50., 50.],
           [50., 50., 50., ..., 50., 50., 50.],
           [50., 50., 50., ..., 50., 50., 50.],
           ...,
           [nan, nan, nan, ..., nan, nan, 50.],
           [nan, nan, nan, ..., nan, nan, 50.],
           [nan, nan, nan, ..., nan, nan, 50.]],
          shape=(7500, 73), dtype=float32)

  • sea_floor_depth_below_sea_level
    (trajectory, time)
    float32
    6.592 6.797 6.634 ... nan nan 6.592

    minval :

    5.0

    maxval :

    77.683044

    array([[ 6.59209  ,  6.796583 ,  6.634422 , ...,  7.0028167,  7.7644596,
            10.132347 ],
           [ 6.59209  ,  6.5511637,  7.009266 , ..., 11.196093 , 11.73864  ,
            12.232362 ],
           [ 6.59209  ,  6.9228745,  7.023348 , ...,  9.216057 ,  7.7654085,
             9.511481 ],
           ...,
           [       nan,        nan,        nan, ...,        nan,        nan,
             6.592038 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
             6.592038 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
             6.592038 ]], shape=(7500, 73), dtype=float32)

• Indexes: (2)
  • trajectory
    PandasIndex

    PandasIndex(Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,
           ...
           7490, 7491, 7492, 7493, 7494, 7495, 7496, 7497, 7498, 7499],
          dtype='int64', name='trajectory', length=7500))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2025-07-02 16:11:10.169116', '2025-07-02 16:41:10.169116',
                   '2025-07-02 17:11:10.169116', '2025-07-02 17:41:10.169116',
                   '2025-07-02 18:11:10.169116', '2025-07-02 18:41:10.169116',
                   '2025-07-02 19:11:10.169116', '2025-07-02 19:41:10.169116',
                   '2025-07-02 20:11:10.169116', '2025-07-02 20:41:10.169116',
                   '2025-07-02 21:11:10.169116', '2025-07-02 21:41:10.169116',
                   '2025-07-02 22:11:10.169116', '2025-07-02 22:41:10.169116',
                   '2025-07-02 23:11:10.169116', '2025-07-02 23:41:10.169116',
                   '2025-07-03 00:11:10.169116', '2025-07-03 00:41:10.169116',
                   '2025-07-03 01:11:10.169116', '2025-07-03 01:41:10.169116',
                   '2025-07-03 02:11:10.169116', '2025-07-03 02:41:10.169116',
                   '2025-07-03 03:11:10.169116', '2025-07-03 03:41:10.169116',
                   '2025-07-03 04:11:10.169116', '2025-07-03 04:41:10.169116',
                   '2025-07-03 05:11:10.169116', '2025-07-03 05:41:10.169116',
                   '2025-07-03 06:11:10.169116', '2025-07-03 06:41:10.169116',
                   '2025-07-03 07:11:10.169116', '2025-07-03 07:41:10.169116',
                   '2025-07-03 08:11:10.169116', '2025-07-03 08:41:10.169116',
                   '2025-07-03 09:11:10.169116', '2025-07-03 09:41:10.169116',
                   '2025-07-03 10:11:10.169116', '2025-07-03 10:41:10.169116',
                   '2025-07-03 11:11:10.169116', '2025-07-03 11:41:10.169116',
                   '2025-07-03 12:11:10.169116', '2025-07-03 12:41:10.169116',
                   '2025-07-03 13:11:10.169116', '2025-07-03 13:41:10.169116',
                   '2025-07-03 14:11:10.169116', '2025-07-03 14:41:10.169116',
                   '2025-07-03 15:11:10.169116', '2025-07-03 15:41:10.169116',
                   '2025-07-03 16:11:10.169116', '2025-07-03 16:41:10.169116',
                   '2025-07-03 17:11:10.169116', '2025-07-03 17:41:10.169116',
                   '2025-07-03 18:11:10.169116', '2025-07-03 18:41:10.169116',
                   '2025-07-03 19:11:10.169116', '2025-07-03 19:41:10.169116',
                   '2025-07-03 20:11:10.169116', '2025-07-03 20:41:10.169116',
                   '2025-07-03 21:11:10.169116', '2025-07-03 21:41:10.169116',
                   '2025-07-03 22:11:10.169116', '2025-07-03 22:41:10.169116',
                   '2025-07-03 23:11:10.169116', '2025-07-03 23:41:10.169116',
                   '2025-07-04 00:11:10.169116', '2025-07-04 00:41:10.169116',
                   '2025-07-04 01:11:10.169116', '2025-07-04 01:41:10.169116',
                   '2025-07-04 02:11:10.169116', '2025-07-04 02:41:10.169116',
                   '2025-07-04 03:11:10.169116', '2025-07-04 03:41:10.169116',
                   '2025-07-04 04:11:10.169116'],
                  dtype='datetime64[ns]', name='time', freq='30min'))

• Attributes: (124)

  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 2025-07-02 16:11:14.464312

  date_created :

  2025-07-02T16:11:14.464330

  source :

  Output from simulation with OpenDrift

  model_url :

  https://github.com/OpenDrift/opendrift

  opendrift_class :

  SedimentDrift

  opendrift_module :

  opendrift.models.sedimentdrift

  readers :

  odict_keys(['LazyReader: https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be', 'global_landmask'])

  time_coverage_start :

  2025-07-02 16:11:10.169116

  time_step_calculation :

  0:10:00

  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:upward_sea_water_velocity :

  None

  config_environment:fallback:upward_sea_water_velocity :

  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:sea_surface_wave_stokes_drift_x_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_x_velocity :

  0

  config_environment:constant:sea_surface_wave_stokes_drift_y_velocity :

  None

  config_environment:fallback:sea_surface_wave_stokes_drift_y_velocity :

  0

  config_environment:constant:sea_surface_wave_period_at_variance_spectral_density_maximum :

  None

  config_environment:fallback:sea_surface_wave_period_at_variance_spectral_density_maximum :

  0

  config_environment:constant:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  None

  config_environment:fallback:sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  0

  config_environment:constant:land_binary_mask :

  None

  config_environment:fallback:land_binary_mask :

  None

  config_environment:constant:ocean_vertical_diffusivity :

  None

  config_environment:fallback:ocean_vertical_diffusivity :

  0.02

  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_general:use_auto_landmask :

  True

  config_drift:current_uncertainty :

  0.2

  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 :

  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 :

  2.0

  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 :

  -0.001

  config_seed:settled :

  0

  config_drift:vertical_advection :

  True

  config_drift:vertical_advection_at_surface :

  False

  config_drift:vertical_mixing :

  True

  config_drift:vertical_mixing_at_surface :

  False

  config_vertical_mixing:timestep :

  60

  config_vertical_mixing:diffusivitymodel :

  windspeed_Large1994

  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

  config_vertical_mixing:resuspension_threshold :

  0.2

  opendrift_version :

  1.14.2

  seed_geojson :

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

  simulation_time :

  2025-07-02 16:11:14.535629

  reader_x_sea_water_velocity :

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

  reader_y_sea_water_velocity :

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

  reader_sea_surface_height :

  ['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_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_sea_surface_wave_stokes_drift_x_velocity :

  0

  reader_sea_surface_wave_stokes_drift_y_velocity :

  0

  reader_sea_surface_wave_period_at_variance_spectral_density_maximum :

  0

  reader_sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment :

  0

  reader_land_binary_mask :

  ['global_landmask']

  reader_ocean_vertical_diffusivity :

  0.02

  reader_ocean_mixed_layer_thickness :

  50

  reader_sea_floor_depth_below_sea_level :

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

  time_coverage_end :

  2025-07-04 04:11:10.169116

  time_coverage_duration :

  P1DT12H0M0S

  time_coverage_resolution :

  P0DT0H10M0S

  performance :

  -------------------- Reader performance: -------------------- global_landmask 0:00:05.3 total 0:00:00.0 preparing 0:00:05.2 reading 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be 0:00:54.7 total 0:00:00.0 preparing 0:00:51.7 reading 0:00:02.6 interpolation 0:00:00.1 interpolation_time 0:00:02.9 rotating vectors 0:00:00.0 masking -------------------- Performance: 1:16.2 total time 4.2 configuration 0.1 preparing main loop 0.0 moving elements to ocean 1:11.8 main loop 4.7 updating elements 3.7 vertical mixing 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  58.88173

  geospatial_lat_max :

  59.188717

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  10.868587

  geospatial_lon_max :

  11.222743

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:01:16.234432

  geospatial_vertical_min :

  0.0

  geospatial_vertical_max :

  0.0

  geospatial_vertical_positive :

  up

Plotting the depth vs time

o.plot_property('z')

Animate sediment particles colored by their depth

o.animation(color='z', fast=False, buffer=.01)
#o.animation(color='moving', fast=False, buffer=.01, colorbar=False, legend=['Sedimented', 'Moving'])

16:12:40 INFO    opendrift:4533: Saving animation to /root/project/docs/source/gallery/animations/example_sediments_0.gif...
16:13:32 INFO    opendrift:2974: Time to make animation: 0:01:02.515873