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/fou-hi/norkystv3_800m_m00_be'])

16:15:04 INFO    opendrift:576: OpenDriftSimulation initialised (version 1.14.6 / v1.14.6-23-g72ef044)

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))

16:15:04 INFO    opendrift.models.basemodel.environment:203: Adding a global landmask from GSHHG
16:15:08 INFO    opendrift.models.basemodel.environment:227: Fallback values will be used for the following variables which have no readers:
16:15:08 INFO    opendrift.models.basemodel.environment:230:    x_sea_water_velocity: 0.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    y_sea_water_velocity: 0.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    sea_surface_height: 0.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    upward_sea_water_velocity: 0.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    x_wind: 0.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    y_wind: 0.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_period_at_variance_spectral_density_maximum: 0.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    ocean_vertical_diffusivity: 0.020000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    ocean_mixed_layer_thickness: 50.000000
16:15:08 INFO    opendrift.models.basemodel.environment:230:    sea_floor_depth_below_sea_level: 10000.000000
16:15:08 INFO    opendrift:1814: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
16:15:08 INFO    opendrift:1814: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
16:15:08 INFO    opendrift:952: Using existing reader for land_binary_mask to move elements to ocean
16:15:08 INFO    opendrift:982: All points are in ocean
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16:15:08 INFO    opendrift.readers:63: Opening file with xr.open_dataset
16:15:11 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'X', 'y': 'Y', 'z': 'depth', 'time': 'time'}
16:15:11 INFO    opendrift.readers.basereader:176: Variable x_sea_water_velocity will be rotated from eastward_sea_water_velocity
16:15:11 INFO    opendrift.readers.basereader:176: Variable y_sea_water_velocity will be rotated from northward_sea_water_velocity
16:15:11 INFO    opendrift.readers.basereader:176: Variable x_wind will be rotated from eastward_wind
16:15:11 INFO    opendrift.readers.basereader:176: Variable y_wind will be rotated from northward_wind
16:15:14 INFO    opendrift:2111: 2025-11-27 16:25:04.150182 - step 2 of 216 - 70 active elements (0 deactivated)
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16:16:26 INFO    opendrift:2111: 2025-11-28 16:25:04.150182 - step 146 of 216 - 5069 active elements (0 deactivated)
16:16:27 INFO    opendrift:2111: 2025-11-28 16:35:04.150182 - step 147 of 216 - 5104 active elements (0 deactivated)
16:16:27 INFO    opendrift:2111: 2025-11-28 16:45:04.150182 - step 148 of 216 - 5139 active elements (0 deactivated)
16:16:28 INFO    opendrift:2111: 2025-11-28 16:55:04.150182 - step 149 of 216 - 5174 active elements (0 deactivated)
16:16:28 INFO    opendrift:2111: 2025-11-28 17:05:04.150182 - step 150 of 216 - 5208 active elements (0 deactivated)
16:16:30 INFO    opendrift:2111: 2025-11-28 17:15:04.150182 - step 151 of 216 - 5243 active elements (0 deactivated)
16:16:31 INFO    opendrift:2111: 2025-11-28 17:25:04.150182 - step 152 of 216 - 5278 active elements (0 deactivated)
16:16:31 INFO    opendrift:2111: 2025-11-28 17:35:04.150182 - step 153 of 216 - 5312 active elements (0 deactivated)
16:16:31 INFO    opendrift:2111: 2025-11-28 17:45:04.150182 - step 154 of 216 - 5347 active elements (0 deactivated)
16:16:32 INFO    opendrift:2111: 2025-11-28 17:55:04.150182 - step 155 of 216 - 5382 active elements (0 deactivated)
16:16:32 INFO    opendrift:2111: 2025-11-28 18:05:04.150182 - step 156 of 216 - 5417 active elements (0 deactivated)
16:16:34 INFO    opendrift:2111: 2025-11-28 18:15:04.150182 - step 157 of 216 - 5451 active elements (0 deactivated)
16:16:35 INFO    opendrift:2111: 2025-11-28 18:25:04.150182 - step 158 of 216 - 5486 active elements (0 deactivated)
16:16:35 INFO    opendrift:2111: 2025-11-28 18:35:04.150182 - step 159 of 216 - 5521 active elements (0 deactivated)
16:16:36 INFO    opendrift:2111: 2025-11-28 18:45:04.150182 - step 160 of 216 - 5556 active elements (0 deactivated)
16:16:36 INFO    opendrift:2111: 2025-11-28 18:55:04.150182 - step 161 of 216 - 5590 active elements (0 deactivated)
16:16:36 INFO    opendrift:2111: 2025-11-28 19:05:04.150182 - step 162 of 216 - 5625 active elements (0 deactivated)
16:16:38 INFO    opendrift:2111: 2025-11-28 19:15:04.150182 - step 163 of 216 - 5660 active elements (0 deactivated)
16:16:39 INFO    opendrift:2111: 2025-11-28 19:25:04.150182 - step 164 of 216 - 5694 active elements (0 deactivated)
16:16:39 INFO    opendrift:2111: 2025-11-28 19:35:04.150182 - step 165 of 216 - 5729 active elements (0 deactivated)
16:16:40 INFO    opendrift:2111: 2025-11-28 19:45:04.150182 - step 166 of 216 - 5764 active elements (0 deactivated)
16:16:40 INFO    opendrift:2111: 2025-11-28 19:55:04.150182 - step 167 of 216 - 5799 active elements (0 deactivated)
16:16:41 INFO    opendrift:2111: 2025-11-28 20:05:04.150182 - step 168 of 216 - 5833 active elements (0 deactivated)
16:16:43 INFO    opendrift:2111: 2025-11-28 20:15:04.150182 - step 169 of 216 - 5868 active elements (0 deactivated)
16:16:43 INFO    opendrift:2111: 2025-11-28 20:25:04.150182 - step 170 of 216 - 5903 active elements (0 deactivated)
16:16:44 INFO    opendrift:2111: 2025-11-28 20:35:04.150182 - step 171 of 216 - 5937 active elements (0 deactivated)
16:16:44 INFO    opendrift:2111: 2025-11-28 20:45:04.150182 - step 172 of 216 - 5972 active elements (0 deactivated)
16:16:45 INFO    opendrift:2111: 2025-11-28 20:55:04.150182 - step 173 of 216 - 6007 active elements (0 deactivated)
16:16:45 INFO    opendrift:2111: 2025-11-28 21:05:04.150182 - step 174 of 216 - 6042 active elements (0 deactivated)
16:16:47 INFO    opendrift:2111: 2025-11-28 21:15:04.150182 - step 175 of 216 - 6076 active elements (0 deactivated)
16:16:48 INFO    opendrift:2111: 2025-11-28 21:25:04.150182 - step 176 of 216 - 6111 active elements (0 deactivated)
16:16:48 INFO    opendrift:2111: 2025-11-28 21:35:04.150182 - step 177 of 216 - 6146 active elements (0 deactivated)
16:16:49 INFO    opendrift:2111: 2025-11-28 21:45:04.150182 - step 178 of 216 - 6180 active elements (0 deactivated)
16:16:49 INFO    opendrift:2111: 2025-11-28 21:55:04.150182 - step 179 of 216 - 6215 active elements (0 deactivated)
16:16:50 INFO    opendrift:2111: 2025-11-28 22:05:04.150182 - step 180 of 216 - 6250 active elements (0 deactivated)
16:16:52 INFO    opendrift:2111: 2025-11-28 22:15:04.150182 - step 181 of 216 - 6285 active elements (0 deactivated)
16:16:53 INFO    opendrift:2111: 2025-11-28 22:25:04.150182 - step 182 of 216 - 6319 active elements (0 deactivated)
16:16:53 INFO    opendrift:2111: 2025-11-28 22:35:04.150182 - step 183 of 216 - 6354 active elements (0 deactivated)
16:16:54 INFO    opendrift:2111: 2025-11-28 22:45:04.150182 - step 184 of 216 - 6389 active elements (0 deactivated)
16:16:54 INFO    opendrift:2111: 2025-11-28 22:55:04.150182 - step 185 of 216 - 6423 active elements (0 deactivated)
16:16:55 INFO    opendrift:2111: 2025-11-28 23:05:04.150182 - step 186 of 216 - 6458 active elements (0 deactivated)
16:16:58 INFO    opendrift:2111: 2025-11-28 23:15:04.150182 - step 187 of 216 - 6493 active elements (0 deactivated)
16:16:58 INFO    opendrift:2111: 2025-11-28 23:25:04.150182 - step 188 of 216 - 6528 active elements (0 deactivated)
16:16:59 INFO    opendrift:2111: 2025-11-28 23:35:04.150182 - step 189 of 216 - 6562 active elements (0 deactivated)
16:16:59 INFO    opendrift:2111: 2025-11-28 23:45:04.150182 - step 190 of 216 - 6597 active elements (0 deactivated)
16:17:00 INFO    opendrift:2111: 2025-11-28 23:55:04.150182 - step 191 of 216 - 6632 active elements (0 deactivated)
16:17:01 INFO    opendrift:2111: 2025-11-29 00:05:04.150182 - step 192 of 216 - 6667 active elements (0 deactivated)
16:17:03 INFO    opendrift:2111: 2025-11-29 00:15:04.150182 - step 193 of 216 - 6701 active elements (0 deactivated)
16:17:03 INFO    opendrift:2111: 2025-11-29 00:25:04.150182 - step 194 of 216 - 6736 active elements (0 deactivated)
16:17:04 INFO    opendrift:2111: 2025-11-29 00:35:04.150182 - step 195 of 216 - 6771 active elements (0 deactivated)
16:17:04 INFO    opendrift:2111: 2025-11-29 00:45:04.150182 - step 196 of 216 - 6805 active elements (0 deactivated)
16:17:05 INFO    opendrift:2111: 2025-11-29 00:55:04.150182 - step 197 of 216 - 6840 active elements (0 deactivated)
16:17:06 INFO    opendrift:2111: 2025-11-29 01:05:04.150182 - step 198 of 216 - 6875 active elements (0 deactivated)
16:17:08 INFO    opendrift:2111: 2025-11-29 01:15:04.150182 - step 199 of 216 - 6910 active elements (0 deactivated)
16:17:09 INFO    opendrift:2111: 2025-11-29 01:25:04.150182 - step 200 of 216 - 6944 active elements (0 deactivated)
16:17:10 INFO    opendrift:2111: 2025-11-29 01:35:04.150182 - step 201 of 216 - 6979 active elements (0 deactivated)
16:17:10 INFO    opendrift:2111: 2025-11-29 01:45:04.150182 - step 202 of 216 - 7014 active elements (0 deactivated)
16:17:11 INFO    opendrift:2111: 2025-11-29 01:55:04.150182 - step 203 of 216 - 7048 active elements (0 deactivated)
16:17:11 INFO    opendrift:2111: 2025-11-29 02:05:04.150182 - step 204 of 216 - 7083 active elements (0 deactivated)
16:17:13 INFO    opendrift:2111: 2025-11-29 02:15:04.150182 - step 205 of 216 - 7118 active elements (0 deactivated)
16:17:14 INFO    opendrift:2111: 2025-11-29 02:25:04.150182 - step 206 of 216 - 7153 active elements (0 deactivated)
16:17:14 INFO    opendrift:2111: 2025-11-29 02:35:04.150182 - step 207 of 216 - 7187 active elements (0 deactivated)
16:17:15 INFO    opendrift:2111: 2025-11-29 02:45:04.150182 - step 208 of 216 - 7222 active elements (0 deactivated)
16:17:15 INFO    opendrift:2111: 2025-11-29 02:55:04.150182 - step 209 of 216 - 7257 active elements (0 deactivated)
16:17:16 INFO    opendrift:2111: 2025-11-29 03:05:04.150182 - step 210 of 216 - 7291 active elements (0 deactivated)
16:17:18 INFO    opendrift:2111: 2025-11-29 03:15:04.150182 - step 211 of 216 - 7326 active elements (0 deactivated)
16:17:19 INFO    opendrift:2111: 2025-11-29 03:25:04.150182 - step 212 of 216 - 7361 active elements (0 deactivated)
16:17:19 INFO    opendrift:2111: 2025-11-29 03:35:04.150182 - step 213 of 216 - 7396 active elements (0 deactivated)
16:17:20 INFO    opendrift:2111: 2025-11-29 03:45:04.150182 - step 214 of 216 - 7430 active elements (0 deactivated)
16:17:20 INFO    opendrift:2111: 2025-11-29 03:55:04.150182 - step 215 of 216 - 7465 active elements (0 deactivated)
16:17:21 INFO    opendrift:2111: 2025-11-29 04:05:04.150182 - step 216 of 216 - 7500 active elements (0 deactivated)
16:17:24 INFO    opendrift:2220: 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: (12/126)
    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]
    2025-11-27T16:15:04.150182 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2025-11-27T16:15:04.150182000', '2025-11-27T16:45:04.150182000',
           '2025-11-27T17:15:04.150182000', '2025-11-27T17:45:04.150182000',
           '2025-11-27T18:15:04.150182000', '2025-11-27T18:45:04.150182000',
           '2025-11-27T19:15:04.150182000', '2025-11-27T19:45:04.150182000',
           '2025-11-27T20:15:04.150182000', '2025-11-27T20:45:04.150182000',
           '2025-11-27T21:15:04.150182000', '2025-11-27T21:45:04.150182000',
           '2025-11-27T22:15:04.150182000', '2025-11-27T22:45:04.150182000',
           '2025-11-27T23:15:04.150182000', '2025-11-27T23:45:04.150182000',
           '2025-11-28T00:15:04.150182000', '2025-11-28T00:45:04.150182000',
           '2025-11-28T01:15:04.150182000', '2025-11-28T01:45:04.150182000',
           '2025-11-28T02:15:04.150182000', '2025-11-28T02:45:04.150182000',
           '2025-11-28T03:15:04.150182000', '2025-11-28T03:45:04.150182000',
           '2025-11-28T04:15:04.150182000', '2025-11-28T04:45:04.150182000',
           '2025-11-28T05:15:04.150182000', '2025-11-28T05:45:04.150182000',
           '2025-11-28T06:15:04.150182000', '2025-11-28T06:45:04.150182000',
           '2025-11-28T07:15:04.150182000', '2025-11-28T07:45:04.150182000',
           '2025-11-28T08:15:04.150182000', '2025-11-28T08:45:04.150182000',
           '2025-11-28T09:15:04.150182000', '2025-11-28T09:45:04.150182000',
           '2025-11-28T10:15:04.150182000', '2025-11-28T10:45:04.150182000',
           '2025-11-28T11:15:04.150182000', '2025-11-28T11:45:04.150182000',
           '2025-11-28T12:15:04.150182000', '2025-11-28T12:45:04.150182000',
           '2025-11-28T13:15:04.150182000', '2025-11-28T13:45:04.150182000',
           '2025-11-28T14:15:04.150182000', '2025-11-28T14:45:04.150182000',
           '2025-11-28T15:15:04.150182000', '2025-11-28T15:45:04.150182000',
           '2025-11-28T16:15:04.150182000', '2025-11-28T16:45:04.150182000',
           '2025-11-28T17:15:04.150182000', '2025-11-28T17:45:04.150182000',
           '2025-11-28T18:15:04.150182000', '2025-11-28T18:45:04.150182000',
           '2025-11-28T19:15:04.150182000', '2025-11-28T19:45:04.150182000',
           '2025-11-28T20:15:04.150182000', '2025-11-28T20:45:04.150182000',
           '2025-11-28T21:15:04.150182000', '2025-11-28T21:45:04.150182000',
           '2025-11-28T22:15:04.150182000', '2025-11-28T22:45:04.150182000',
           '2025-11-28T23:15:04.150182000', '2025-11-28T23:45:04.150182000',
           '2025-11-29T00:15:04.150182000', '2025-11-29T00:45:04.150182000',
           '2025-11-29T01:15:04.150182000', '2025-11-29T01:45:04.150182000',
           '2025-11-29T02:15:04.150182000', '2025-11-29T02:45:04.150182000',
           '2025-11-29T03:15:04.150182000', '2025-11-29T03:45:04.150182000',
           '2025-11-29T04:15:04.150182000'], 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 10.98 10.98 ... nan nan 10.97

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    10.936935

    maxval :

    11.070777

    array([[10.96292  , 10.979346 , 10.979417 , ..., 10.992064 , 10.992064 ,
            10.992427 ],
           [10.96292  , 10.976709 , 10.983314 , ..., 11.012666 , 11.012666 ,
            11.011419 ],
           [10.96292  , 10.976511 , 10.976511 , ..., 11.0177145, 11.0210905,
            11.0210905],
           ...,
           [       nan,        nan,        nan, ...,        nan,        nan,
            10.965466 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
            10.966692 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
            10.967012 ]], 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 :

    59.094795

    maxval :

    59.21164

    array([[59.169193, 59.167637, 59.169052, ..., 59.188465, 59.188465,
            59.187965],
           [59.169193, 59.170353, 59.169483, ..., 59.186863, 59.186863,
            59.184395],
           [59.169193, 59.16668 , 59.16668 , ..., 59.18394 , 59.184734,
            59.184734],
           ...,
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.169376],
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.169334],
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.169453]], 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
    0.6314 0.4175 ... nan 0.3449

    minval :

    -1.0311029

    maxval :

    1.1837004

    array([[ 0.6313926 ,  0.4175397 , -0.15111837, ...,  0.15214819,
             0.01381856,  0.0866994 ],
           [ 0.35861358,  0.2579396 ,  0.6258914 , ...,  0.16734296,
            -0.13259387, -0.19379956],
           [ 0.4743297 ,  0.4767401 ,  0.30095172, ...,  0.23904276,
             0.08466468,  0.1110061 ],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.14444016],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.23871472],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.3448611 ]], shape=(7500, 73), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    -0.2164 -0.2496 ... nan -0.178

    minval :

    -1.2249473

    maxval :

    0.9380325

    array([[-0.2163507 , -0.24961072,  0.01859964, ...,  0.04122011,
            -0.30508062, -0.04016677],
           [-0.00156236, -0.09249903,  0.01698   , ..., -0.34189376,
            -0.08294851, -0.6097615 ],
           [-0.00714452, -0.14640868, -0.2284675 , ..., -0.01775606,
             0.12915553,  0.00164322],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.18441996],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.16895905],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.17796853]], shape=(7500, 73), dtype=float32)

  • sea_surface_height
    (trajectory, time)
    float32
    -0.3258 -0.3159 ... nan -0.0004959

    minval :

    -0.32575077

    maxval :

    0.44502768

    array([[-0.32575077, -0.31592464, -0.2899992 , ...,  0.05267968,
             0.02217968,  0.00294466],
           [-0.32575077, -0.3154452 , -0.29103103, ...,  0.05258776,
             0.0220643 ,  0.00275604],
           [-0.32575077, -0.31582987, -0.29049748, ...,  0.05250252,
             0.0220091 ,  0.00278225],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.00049589],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.00049589],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.00049589]], shape=(7500, 73), dtype=float32)

  • upward_sea_water_velocity
    (trajectory, time)
    float32
    -2.159e-05 1.074e-05 ... -1.674e-05

    minval :

    -0.000121659585

    maxval :

    6.497694e-05

    array([[-2.1585995e-05,  1.0742503e-05,  1.6627835e-05, ...,
            -2.4976944e-05, -1.4976943e-05, -9.1551383e-06],
           [-2.1585995e-05,  1.1240570e-05,  1.8200515e-05, ...,
            -2.4976944e-05, -1.4976943e-05, -9.1551383e-06],
           [-2.1585995e-05,  1.0550461e-05,  1.6206968e-05, ...,
            -2.4976944e-05, -1.4976943e-05, -9.1551383e-06],
           ...,
           [           nan,            nan,            nan, ...,
                       nan,            nan, -1.6736707e-05],
           [           nan,            nan,            nan, ...,
                       nan,            nan, -1.6736707e-05],
           [           nan,            nan,            nan, ...,
                       nan,            nan, -1.6736707e-05]],
          shape=(7500, 73), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    5.047 1.762 3.437 ... nan nan 2.26

    minval :

    -8.878816

    maxval :

    14.079745

    array([[ 5.046952  ,  1.762284  ,  3.436513  , ...,  6.377918  ,
             1.0346227 ,  2.3494978 ],
           [ 3.8467364 ,  2.089655  , -0.35909486, ...,  3.8812664 ,
             2.4427965 ,  2.3724022 ],
           [ 5.867572  ,  1.7219235 ,  5.336712  , ...,  4.129396  ,
             2.897936  ,  5.993579  ],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan,  4.9087124 ],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  6.042307  ],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  2.2602444 ]], shape=(7500, 73), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    9.06 4.736 4.268 ... nan nan 11.29

    minval :

    -3.8664997

    maxval :

    22.357504

    array([[ 9.059972 ,  4.7359653,  4.26797  , ...,  9.098552 , 10.60381  ,
             7.18997  ],
           [ 4.345491 ,  2.9871585,  3.6389918, ...,  8.456315 ,  8.365586 ,
             7.6421895],
           [ 3.6778195,  1.8542597,  6.459357 , ...,  8.236795 ,  4.938981 ,
             7.888091 ],
           ...,
           [       nan,        nan,        nan, ...,        nan,        nan,
            10.916705 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
             9.755355 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
            11.293436 ]], 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
    8.862 4.318 4.682 ... nan nan 9.841

    minval :

    0.0969339

    maxval :

    19.103842

    array([[ 8.861598 ,  4.3178263,  4.6820927, ...,  9.494298 ,  9.103671 ,
             6.463312 ],
           [ 4.9589243,  3.114985 ,  3.124514 , ...,  7.950411 ,  7.446665 ,
             6.837439 ],
           [ 5.9171557,  2.162216 ,  7.159413 , ...,  7.8730407,  4.893034 ,
             8.465082 ],
           ...,
           [       nan,        nan,        nan, ...,        nan,        nan,
            10.22762  ],
           [       nan,        nan,        nan, ...,        nan,        nan,
             9.80508  ],
           [       nan,        nan,        nan, ...,        nan,        nan,
             9.841277 ]], 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
    1e-06 1e-06 1e-06 ... nan 6.415e-05

    minval :

    1e-06

    maxval :

    0.009119885

    array([[1.0000000e-06, 1.0000000e-06, 1.0000000e-06, ..., 6.2220020e-04,
            2.5937235e-04, 7.2222385e-05],
           [1.0000000e-06, 1.0000000e-06, 1.0000000e-06, ..., 6.2206789e-04,
            2.5887569e-04, 7.1309856e-05],
           [1.0000000e-06, 1.0000000e-06, 1.0000000e-06, ..., 6.2194519e-04,
            2.5863809e-04, 7.1436640e-05],
           ...,
           [          nan,           nan,           nan, ...,           nan,
                      nan, 6.4147258e-05],
           [          nan,           nan,           nan, ...,           nan,
                      nan, 6.4147258e-05],
           [          nan,           nan,           nan, ...,           nan,
                      nan, 6.4147258e-05]], 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
    14.0 13.89 13.9 ... nan nan 14.0

    minval :

    10.0

    maxval :

    17.929571

    array([[14.000173, 13.88664 , 13.90155 , ..., 10.      , 10.      ,
            10.      ],
           [14.000173, 14.011665, 13.670421, ..., 10.      , 10.      ,
            10.      ],
           [14.000173, 13.982422, 13.865794, ..., 10.      , 10.      ,
            10.      ],
           ...,
           [      nan,       nan,       nan, ...,       nan,       nan,
            14.000064],
           [      nan,       nan,       nan, ...,       nan,       nan,
            14.000064],
           [      nan,       nan,       nan, ...,       nan,       nan,
            14.000064]], 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(['2025-11-27 16:15:04.150182', '2025-11-27 16:45:04.150182',
                   '2025-11-27 17:15:04.150182', '2025-11-27 17:45:04.150182',
                   '2025-11-27 18:15:04.150182', '2025-11-27 18:45:04.150182',
                   '2025-11-27 19:15:04.150182', '2025-11-27 19:45:04.150182',
                   '2025-11-27 20:15:04.150182', '2025-11-27 20:45:04.150182',
                   '2025-11-27 21:15:04.150182', '2025-11-27 21:45:04.150182',
                   '2025-11-27 22:15:04.150182', '2025-11-27 22:45:04.150182',
                   '2025-11-27 23:15:04.150182', '2025-11-27 23:45:04.150182',
                   '2025-11-28 00:15:04.150182', '2025-11-28 00:45:04.150182',
                   '2025-11-28 01:15:04.150182', '2025-11-28 01:45:04.150182',
                   '2025-11-28 02:15:04.150182', '2025-11-28 02:45:04.150182',
                   '2025-11-28 03:15:04.150182', '2025-11-28 03:45:04.150182',
                   '2025-11-28 04:15:04.150182', '2025-11-28 04:45:04.150182',
                   '2025-11-28 05:15:04.150182', '2025-11-28 05:45:04.150182',
                   '2025-11-28 06:15:04.150182', '2025-11-28 06:45:04.150182',
                   '2025-11-28 07:15:04.150182', '2025-11-28 07:45:04.150182',
                   '2025-11-28 08:15:04.150182', '2025-11-28 08:45:04.150182',
                   '2025-11-28 09:15:04.150182', '2025-11-28 09:45:04.150182',
                   '2025-11-28 10:15:04.150182', '2025-11-28 10:45:04.150182',
                   '2025-11-28 11:15:04.150182', '2025-11-28 11:45:04.150182',
                   '2025-11-28 12:15:04.150182', '2025-11-28 12:45:04.150182',
                   '2025-11-28 13:15:04.150182', '2025-11-28 13:45:04.150182',
                   '2025-11-28 14:15:04.150182', '2025-11-28 14:45:04.150182',
                   '2025-11-28 15:15:04.150182', '2025-11-28 15:45:04.150182',
                   '2025-11-28 16:15:04.150182', '2025-11-28 16:45:04.150182',
                   '2025-11-28 17:15:04.150182', '2025-11-28 17:45:04.150182',
                   '2025-11-28 18:15:04.150182', '2025-11-28 18:45:04.150182',
                   '2025-11-28 19:15:04.150182', '2025-11-28 19:45:04.150182',
                   '2025-11-28 20:15:04.150182', '2025-11-28 20:45:04.150182',
                   '2025-11-28 21:15:04.150182', '2025-11-28 21:45:04.150182',
                   '2025-11-28 22:15:04.150182', '2025-11-28 22:45:04.150182',
                   '2025-11-28 23:15:04.150182', '2025-11-28 23:45:04.150182',
                   '2025-11-29 00:15:04.150182', '2025-11-29 00:45:04.150182',
                   '2025-11-29 01:15:04.150182', '2025-11-29 01:45:04.150182',
                   '2025-11-29 02:15:04.150182', '2025-11-29 02:45:04.150182',
                   '2025-11-29 03:15:04.150182', '2025-11-29 03:45:04.150182',
                   '2025-11-29 04:15:04.150182'],
                  dtype='datetime64[ns]', name='time', freq='30min'))

• Attributes: (126)

  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 2025-11-27 16:15:08.240881

  date_created :

  2025-11-27T16:15:08.240897

  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/fou-hi/norkystv3_800m_m00_be', 'global_landmask'])

  time_coverage_start :

  2025-11-27 16:15:04.150182

  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:water_column_stretching :

  False

  config_drift:vertical_advection_correction :

  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 :

  1.14.6

  seed_geojson :

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

  simulation_time :

  2025-11-27 16:15:08.249594

  reader_x_sea_water_velocity :

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

  reader_y_sea_water_velocity :

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

  reader_sea_surface_height :

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

  reader_upward_sea_water_velocity :

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

  reader_x_wind :

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

  reader_y_wind :

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

  reader_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 :

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

  reader_ocean_mixed_layer_thickness :

  50

  reader_sea_floor_depth_below_sea_level :

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

  time_coverage_end :

  2025-11-29 04:15:04.150182

  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/fou-hi/norkystv3_800m_m00_be 0:01:17.1 total 0:00:00.0 preparing 0:01:14.4 reading 0:00:07.6 interpolation 0:00:00.2 interpolation_time 0:00:02.6 rotating vectors 0:00:00.0 masking -------------------- Performance: 2:20.4 total time 4.0 configuration 0.0 preparing main loop 0.0 moving elements to ocean 2:16.0 main loop 4.2 updating elements 3.3 vertical mixing 0.3 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  59.094795

  geospatial_lat_max :

  59.21164

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  10.936935

  geospatial_lon_max :

  11.070777

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:02:20.495268

  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'])

16:17:36 INFO    opendrift:4651: Saving animation to /root/project/docs/source/gallery/animations/example_sediments_0.gif...
16:18:22 INFO    opendrift:3086: Time to make animation: 0:00:54.781128