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'])

15:23:09 INFO    opendrift:509: OpenDriftSimulation initialised (version 1.13.1 / v1.13.1-12-gca7f755)

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.utcnow(), datetime.utcnow()+timedelta(hours=48)],
                terminal_velocity=-.001)  # 1 mm/s settling speed

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

15:23:09 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
15:23:13 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
15:23:13 INFO    opendrift.models.basemodel.environment:232:    x_sea_water_velocity: 0.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    y_sea_water_velocity: 0.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    sea_surface_height: 0.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    upward_sea_water_velocity: 0.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    x_wind: 0.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    y_wind: 0.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_period_at_variance_spectral_density_maximum: 0.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    ocean_vertical_diffusivity: 0.020000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    ocean_mixed_layer_thickness: 50.000000
15:23:13 INFO    opendrift.models.basemodel.environment:232:    sea_floor_depth_below_sea_level: 10000.000000
15:23:13 INFO    opendrift:919: Using existing reader for land_binary_mask
15:23:13 INFO    opendrift:930: All points are in ocean
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15:23:13 INFO    opendrift.readers:61: Opening file with xr.open_dataset
15:23:15 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'X', 'y': 'Y', 'z': 'depth', 'time': 'time'}
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15:26:04 INFO    opendrift:2056: 2025-04-04 16:43:09.506565 - step 153 of 216 - 5312 active elements (0 deactivated)
15:26:05 INFO    opendrift:2056: 2025-04-04 16:53:09.506565 - step 154 of 216 - 5347 active elements (0 deactivated)
15:26:06 INFO    opendrift:2056: 2025-04-04 17:03:09.506565 - step 155 of 216 - 5382 active elements (0 deactivated)
15:26:07 INFO    opendrift:2056: 2025-04-04 17:13:09.506565 - step 156 of 216 - 5417 active elements (0 deactivated)
15:26:09 INFO    opendrift:2056: 2025-04-04 17:23:09.506565 - step 157 of 216 - 5451 active elements (0 deactivated)
15:26:10 INFO    opendrift:2056: 2025-04-04 17:33:09.506565 - step 158 of 216 - 5486 active elements (0 deactivated)
15:26:11 INFO    opendrift:2056: 2025-04-04 17:43:09.506565 - step 159 of 216 - 5521 active elements (0 deactivated)
15:26:12 INFO    opendrift:2056: 2025-04-04 17:53:09.506565 - step 160 of 216 - 5556 active elements (0 deactivated)
15:26:13 INFO    opendrift:2056: 2025-04-04 18:03:09.506565 - step 161 of 216 - 5590 active elements (0 deactivated)
15:26:14 INFO    opendrift:2056: 2025-04-04 18:13:09.506565 - step 162 of 216 - 5625 active elements (0 deactivated)
15:26:15 INFO    opendrift:2056: 2025-04-04 18:23:09.506565 - step 163 of 216 - 5660 active elements (0 deactivated)
15:26:17 INFO    opendrift:2056: 2025-04-04 18:33:09.506565 - step 164 of 216 - 5694 active elements (0 deactivated)
15:26:18 INFO    opendrift:2056: 2025-04-04 18:43:09.506565 - step 165 of 216 - 5729 active elements (0 deactivated)
15:26:19 INFO    opendrift:2056: 2025-04-04 18:53:09.506565 - step 166 of 216 - 5764 active elements (0 deactivated)
15:26:20 INFO    opendrift:2056: 2025-04-04 19:03:09.506565 - step 167 of 216 - 5799 active elements (0 deactivated)
15:26:21 INFO    opendrift:2056: 2025-04-04 19:13:09.506565 - step 168 of 216 - 5833 active elements (0 deactivated)
15:26:22 INFO    opendrift:2056: 2025-04-04 19:23:09.506565 - step 169 of 216 - 5868 active elements (0 deactivated)
15:26:24 INFO    opendrift:2056: 2025-04-04 19:33:09.506565 - step 170 of 216 - 5903 active elements (0 deactivated)
15:26:25 INFO    opendrift:2056: 2025-04-04 19:43:09.506565 - step 171 of 216 - 5937 active elements (0 deactivated)
15:26:26 INFO    opendrift:2056: 2025-04-04 19:53:09.506565 - step 172 of 216 - 5972 active elements (0 deactivated)
15:26:28 INFO    opendrift:2056: 2025-04-04 20:03:09.506565 - step 173 of 216 - 6007 active elements (0 deactivated)
15:26:29 INFO    opendrift:2056: 2025-04-04 20:13:09.506565 - step 174 of 216 - 6042 active elements (0 deactivated)
15:26:30 INFO    opendrift:2056: 2025-04-04 20:23:09.506565 - step 175 of 216 - 6076 active elements (0 deactivated)
15:26:31 INFO    opendrift:2056: 2025-04-04 20:33:09.506565 - step 176 of 216 - 6111 active elements (0 deactivated)
15:26:32 INFO    opendrift:2056: 2025-04-04 20:43:09.506565 - step 177 of 216 - 6146 active elements (0 deactivated)
15:26:33 INFO    opendrift:2056: 2025-04-04 20:53:09.506565 - step 178 of 216 - 6180 active elements (0 deactivated)
15:26:35 INFO    opendrift:2056: 2025-04-04 21:03:09.506565 - step 179 of 216 - 6215 active elements (0 deactivated)
15:26:36 INFO    opendrift:2056: 2025-04-04 21:13:09.506565 - step 180 of 216 - 6250 active elements (0 deactivated)
15:26:37 INFO    opendrift:2056: 2025-04-04 21:23:09.506565 - step 181 of 216 - 6285 active elements (0 deactivated)
15:26:38 INFO    opendrift:2056: 2025-04-04 21:33:09.506565 - step 182 of 216 - 6319 active elements (0 deactivated)
15:26:39 INFO    opendrift:2056: 2025-04-04 21:43:09.506565 - step 183 of 216 - 6354 active elements (0 deactivated)
15:26:40 INFO    opendrift:2056: 2025-04-04 21:53:09.506565 - step 184 of 216 - 6389 active elements (0 deactivated)
15:26:42 INFO    opendrift:2056: 2025-04-04 22:03:09.506565 - step 185 of 216 - 6423 active elements (0 deactivated)
15:26:43 INFO    opendrift:2056: 2025-04-04 22:13:09.506565 - step 186 of 216 - 6458 active elements (0 deactivated)
15:26:44 INFO    opendrift:2056: 2025-04-04 22:23:09.506565 - step 187 of 216 - 6493 active elements (0 deactivated)
15:26:45 INFO    opendrift:2056: 2025-04-04 22:33:09.506565 - step 188 of 216 - 6528 active elements (0 deactivated)
15:26:46 INFO    opendrift:2056: 2025-04-04 22:43:09.506565 - step 189 of 216 - 6562 active elements (0 deactivated)
15:26:47 INFO    opendrift:2056: 2025-04-04 22:53:09.506565 - step 190 of 216 - 6597 active elements (0 deactivated)
15:26:49 INFO    opendrift:2056: 2025-04-04 23:03:09.506565 - step 191 of 216 - 6632 active elements (0 deactivated)
15:26:50 INFO    opendrift:2056: 2025-04-04 23:13:09.506565 - step 192 of 216 - 6667 active elements (0 deactivated)
15:26:51 INFO    opendrift:2056: 2025-04-04 23:23:09.506565 - step 193 of 216 - 6701 active elements (0 deactivated)
15:26:52 INFO    opendrift:2056: 2025-04-04 23:33:09.506565 - step 194 of 216 - 6736 active elements (0 deactivated)
15:26:53 INFO    opendrift:2056: 2025-04-04 23:43:09.506565 - step 195 of 216 - 6771 active elements (0 deactivated)
15:26:54 INFO    opendrift:2056: 2025-04-04 23:53:09.506565 - step 196 of 216 - 6805 active elements (0 deactivated)
15:26:56 INFO    opendrift:2056: 2025-04-05 00:03:09.506565 - step 197 of 216 - 6840 active elements (0 deactivated)
15:26:57 INFO    opendrift:2056: 2025-04-05 00:13:09.506565 - step 198 of 216 - 6875 active elements (0 deactivated)
15:26:58 INFO    opendrift:2056: 2025-04-05 00:23:09.506565 - step 199 of 216 - 6910 active elements (0 deactivated)
15:26:59 INFO    opendrift:2056: 2025-04-05 00:33:09.506565 - step 200 of 216 - 6944 active elements (0 deactivated)
15:27:00 INFO    opendrift:2056: 2025-04-05 00:43:09.506565 - step 201 of 216 - 6979 active elements (0 deactivated)
15:27:02 INFO    opendrift:2056: 2025-04-05 00:53:09.506565 - step 202 of 216 - 7014 active elements (0 deactivated)
15:27:03 INFO    opendrift:2056: 2025-04-05 01:03:09.506565 - step 203 of 216 - 7048 active elements (0 deactivated)
15:27:04 INFO    opendrift:2056: 2025-04-05 01:13:09.506565 - step 204 of 216 - 7083 active elements (0 deactivated)
15:27:05 INFO    opendrift:2056: 2025-04-05 01:23:09.506565 - step 205 of 216 - 7118 active elements (0 deactivated)
15:27:07 INFO    opendrift:2056: 2025-04-05 01:33:09.506565 - step 206 of 216 - 7153 active elements (0 deactivated)
15:27:08 INFO    opendrift:2056: 2025-04-05 01:43:09.506565 - step 207 of 216 - 7187 active elements (0 deactivated)
15:27:09 INFO    opendrift:2056: 2025-04-05 01:53:09.506565 - step 208 of 216 - 7222 active elements (0 deactivated)
15:27:10 INFO    opendrift:2056: 2025-04-05 02:03:09.506565 - step 209 of 216 - 7257 active elements (0 deactivated)
15:27:12 INFO    opendrift:2056: 2025-04-05 02:13:09.506565 - step 210 of 216 - 7291 active elements (0 deactivated)
15:27:13 INFO    opendrift:2056: 2025-04-05 02:23:09.506565 - step 211 of 216 - 7326 active elements (0 deactivated)
15:27:14 INFO    opendrift:2056: 2025-04-05 02:33:09.506565 - step 212 of 216 - 7361 active elements (0 deactivated)
15:27:15 INFO    opendrift:2056: 2025-04-05 02:43:09.506565 - step 213 of 216 - 7396 active elements (0 deactivated)
15:27:16 INFO    opendrift:2056: 2025-04-05 02:53:09.506565 - step 214 of 216 - 7430 active elements (0 deactivated)
15:27:18 INFO    opendrift:2056: 2025-04-05 03:03:09.506565 - step 215 of 216 - 7465 active elements (0 deactivated)
15:27:19 INFO    opendrift:2056: 2025-04-05 03:13:09.506565 - step 216 of 216 - 7500 active elements (0 deactivated)
15:27:19 INFO    opendrift:2185: 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: (12/122)
    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])

  • time
    (time)
    datetime64[ns]
    2025-04-03T15:23:09.506565 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2025-04-03T15:23:09.506565000', '2025-04-03T15:53:09.506565000',
           '2025-04-03T16:23:09.506565000', '2025-04-03T16:53:09.506565000',
           '2025-04-03T17:23:09.506565000', '2025-04-03T17:53:09.506565000',
           '2025-04-03T18:23:09.506565000', '2025-04-03T18:53:09.506565000',
           '2025-04-03T19:23:09.506565000', '2025-04-03T19:53:09.506565000',
           '2025-04-03T20:23:09.506565000', '2025-04-03T20:53:09.506565000',
           '2025-04-03T21:23:09.506565000', '2025-04-03T21:53:09.506565000',
           '2025-04-03T22:23:09.506565000', '2025-04-03T22:53:09.506565000',
           '2025-04-03T23:23:09.506565000', '2025-04-03T23:53:09.506565000',
           '2025-04-04T00:23:09.506565000', '2025-04-04T00:53:09.506565000',
           '2025-04-04T01:23:09.506565000', '2025-04-04T01:53:09.506565000',
           '2025-04-04T02:23:09.506565000', '2025-04-04T02:53:09.506565000',
           '2025-04-04T03:23:09.506565000', '2025-04-04T03:53:09.506565000',
           '2025-04-04T04:23:09.506565000', '2025-04-04T04:53:09.506565000',
           '2025-04-04T05:23:09.506565000', '2025-04-04T05:53:09.506565000',
           '2025-04-04T06:23:09.506565000', '2025-04-04T06:53:09.506565000',
           '2025-04-04T07:23:09.506565000', '2025-04-04T07:53:09.506565000',
           '2025-04-04T08:23:09.506565000', '2025-04-04T08:53:09.506565000',
           '2025-04-04T09:23:09.506565000', '2025-04-04T09:53:09.506565000',
           '2025-04-04T10:23:09.506565000', '2025-04-04T10:53:09.506565000',
           '2025-04-04T11:23:09.506565000', '2025-04-04T11:53:09.506565000',
           '2025-04-04T12:23:09.506565000', '2025-04-04T12:53:09.506565000',
           '2025-04-04T13:23:09.506565000', '2025-04-04T13:53:09.506565000',
           '2025-04-04T14:23:09.506565000', '2025-04-04T14:53:09.506565000',
           '2025-04-04T15:23:09.506565000', '2025-04-04T15:53:09.506565000',
           '2025-04-04T16:23:09.506565000', '2025-04-04T16:53:09.506565000',
           '2025-04-04T17:23:09.506565000', '2025-04-04T17:53:09.506565000',
           '2025-04-04T18:23:09.506565000', '2025-04-04T18:53:09.506565000',
           '2025-04-04T19:23:09.506565000', '2025-04-04T19:53:09.506565000',
           '2025-04-04T20:23:09.506565000', '2025-04-04T20:53:09.506565000',
           '2025-04-04T21:23:09.506565000', '2025-04-04T21:53:09.506565000',
           '2025-04-04T22:23:09.506565000', '2025-04-04T22:53:09.506565000',
           '2025-04-04T23:23:09.506565000', '2025-04-04T23:53:09.506565000',
           '2025-04-05T00:23:09.506565000', '2025-04-05T00:53:09.506565000',
           '2025-04-05T01:23:09.506565000', '2025-04-05T01:53:09.506565000',
           '2025-04-05T02:23:09.506565000', '2025-04-05T02:53:09.506565000',
           '2025-04-05T03:23:09.506565000'], 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.]], dtype=float32)

  • moving
    (trajectory, time)
    float32
    1.0 1.0 1.0 1.0 ... nan nan nan 1.0

    dtype :

    <class 'numpy.int32'>

    minval :

    0

    maxval :

    1

    array([[ 1.,  1.,  1., ...,  1.,  0.,  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.]], 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.]],
          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.]], dtype=float32)

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

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    10.891997

    maxval :

    11.038944

    array([[10.96292 , 10.971396, 10.969377, ..., 11.002099, 10.99692 ,
            10.998692],
           [10.96292 , 10.974141, 10.979134, ..., 11.008911, 11.009994,
            11.007447],
           [10.96292 , 10.970396, 10.974122, ..., 10.992525, 10.996748,
            10.994308],
           ...,
           [      nan,       nan,       nan, ...,       nan,       nan,
            10.965611],
           [      nan,       nan,       nan, ...,       nan,       nan,
            10.966839],
           [      nan,       nan,       nan, ...,       nan,       nan,
            10.967158]], 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 :

    59.111835

    maxval :

    59.18872

    array([[59.169193, 59.17031 , 59.171856, ..., 59.16688 , 59.166534,
            59.16539 ],
           [59.169193, 59.171642, 59.16862 , ..., 59.157276, 59.15408 ,
            59.15006 ],
           [59.169193, 59.169113, 59.169964, ..., 59.145332, 59.14668 ,
            59.14805 ],
           ...,
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.169033],
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.16899 ],
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.16911 ]], dtype=float32)

  • z
    (trajectory, time)
    float32
    0.0 -5.015 -5.26 ... nan -0.5569

    dtype :

    <class 'numpy.float32'>

    units :

    m

    standard_name :

    z

    long_name :

    vertical position

    axis :

    Z

    positive :

    up

    minval :

    -14.039592

    maxval :

    0.0

    array([[ 0.        , -5.015098  , -5.2599645 , ..., -6.268532  ,
            -6.348414  , -4.4871755 ],
           [ 0.        , -1.8484185 , -4.9462495 , ..., -1.7406856 ,
            -3.907423  , -5.3687468 ],
           [ 0.        , -2.9045959 , -6.062164  , ..., -9.553843  ,
            -9.192858  , -6.3878202 ],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan, -2.6573706 ],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.83270323],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.5569198 ]], 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]], 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.]], 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]],
          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.]], dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    0.6728 0.1589 ... nan 0.4024

    minval :

    -0.9828836

    maxval :

    1.1555463

    array([[ 0.67276   ,  0.15887205, -0.35725886, ...,  0.13089034,
             0.00112782,  0.07408949],
           [ 0.399981  ,  0.17886303,  0.42344967, ...,  0.18893383,
            -0.17016545, -0.21321426],
           [ 0.5156971 ,  0.21796064,  0.04903601, ...,  0.18217227,
             0.04445992,  0.06170564],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.20201571],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.29629028],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.40243664]], dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    -0.0406 0.01558 ... nan -0.02189

    minval :

    -1.0457287

    maxval :

    0.8738461

    array([[-0.04060438,  0.01557565,  0.23921765, ..., -0.00322268,
            -0.33199015, -0.06151645],
           [ 0.17418396,  0.04681681,  0.24860816, ..., -0.46283898,
            -0.10897753, -0.6461862 ],
           [ 0.1686018 ,  0.14732645,  0.08602185, ..., -0.06756669,
             0.11360215, -0.03064712],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.02834259],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.01288167],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.02189115]], dtype=float32)

  • sea_surface_height
    (trajectory, time)
    float32
    -0.3652 -0.3129 ... nan -0.4297

    minval :

    -0.47543418

    maxval :

    -0.09308821

    array([[-0.3652424 , -0.31289393, -0.26496154, ..., -0.4131834 ,
            -0.4310132 , -0.4302318 ],
           [-0.3652424 , -0.31236786, -0.26484048, ..., -0.41150913,
            -0.42900914, -0.4283946 ],
           [-0.3652424 , -0.31317133, -0.26519305, ..., -0.41623744,
            -0.43342924, -0.43099016],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.42966592],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.42966592],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.42966592]], dtype=float32)

  • upward_sea_water_velocity
    (trajectory, time)
    float32
    1.109e-05 2.417e-05 ... -1.82e-05

    minval :

    -9.7690274e-05

    maxval :

    0.00058250857

    array([[ 1.1088310e-05,  2.4173547e-05,  6.3843232e-05, ...,
             1.6583246e-05,  8.6270747e-06,  1.3904950e-05],
           [ 1.1088310e-05,  2.3125596e-05,  1.7489472e-05, ...,
             1.3036927e-05,  4.1102812e-05,  4.3794807e-05],
           [ 1.1088310e-05,  2.3136894e-05,  2.3968658e-05, ...,
             4.3413133e-05,  4.2252264e-05,  4.4512766e-05],
           ...,
           [           nan,            nan,            nan, ...,
                       nan,            nan, -1.8202418e-05],
           [           nan,            nan,            nan, ...,
                       nan,            nan, -1.8202418e-05],
           [           nan,            nan,            nan, ...,
                       nan,            nan, -1.8202418e-05]], dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    1.13 -2.627 -1.157 ... nan 0.07852

    minval :

    -11.041305

    maxval :

    8.522754

    array([[ 1.1299776 , -2.6271098 , -1.1573968 , ...,  3.0337522 ,
            -1.6567258 , -0.22203268],
           [-0.07023774, -2.2620456 , -4.8360415 , ...,  0.485288  ,
            -0.41102478, -0.343343  ],
           [ 1.9505978 , -2.6998198 ,  0.7466708 , ...,  1.0411977 ,
             0.3198278 ,  3.5674913 ],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan,  2.7269921 ],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  3.8605866 ],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.0785243 ]], dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    7.343 3.026 2.736 ... nan nan 0.318

    minval :

    -13.429169

    maxval :

    10.617111

    array([[ 7.342727  ,  3.026281  ,  2.7357647 , ..., -0.6243098 ,
             0.43132025, -3.443685  ],
           [ 2.6282468 ,  1.3021005 ,  2.063596  , ..., -1.3762594 ,
            -1.8671119 , -3.05045   ],
           [ 1.960575  ,  0.15000252,  4.898412  , ..., -2.1607308 ,
            -5.7099943 , -3.1948783 ],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.05868529],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -1.2200354 ],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.3180455 ]], 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.]], 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.]], 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.]], dtype=float32)

  • sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment
    (trajectory, time)
    float32
    6.348 3.424 2.538 ... nan 0.2799

    minval :

    0.0043307566

    maxval :

    11.722181

    array([[6.348003 , 3.424294 , 2.5382202, ..., 2.646572 , 1.4628122,
            2.9486375],
           [2.2465615, 2.2302036, 4.4927382, ..., 1.24694  , 1.6335922,
            2.6229784],
           [2.3631458, 2.3104749, 4.233896 , ..., 2.0494564, 4.88667  ,
            4.092035 ],
           ...,
           [      nan,       nan,       nan, ...,       nan,       nan,
            2.3306744],
           [      nan,       nan,       nan, ...,       nan,       nan,
            3.4595633],
           [      nan,       nan,       nan, ...,       nan,       nan,
            0.279921 ]], 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.]], 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]], 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.]], dtype=float32)

  • sea_floor_depth_below_sea_level
    (trajectory, time)
    float32
    6.592 6.588 6.457 ... nan nan 6.592

    minval :

    5.0

    maxval :

    14.7399025

    array([[ 6.5920897,  6.588453 ,  6.4574056, ...,  6.681715 ,  6.779427 ,
             6.833904 ],
           [ 6.5920897,  6.463019 ,  6.7069273, ...,  6.409444 ,  5.8359737,
             5.807142 ],
           [ 6.5920897,  6.7085195,  6.6095133, ..., 10.443814 ,  9.6262865,
             9.555397 ],
           ...,
           [       nan,        nan,        nan, ...,        nan,        nan,
             6.592038 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
             6.592038 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
             6.592038 ]], 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(['2025-04-03 15:23:09.506565', '2025-04-03 15:53:09.506565',
                   '2025-04-03 16:23:09.506565', '2025-04-03 16:53:09.506565',
                   '2025-04-03 17:23:09.506565', '2025-04-03 17:53:09.506565',
                   '2025-04-03 18:23:09.506565', '2025-04-03 18:53:09.506565',
                   '2025-04-03 19:23:09.506565', '2025-04-03 19:53:09.506565',
                   '2025-04-03 20:23:09.506565', '2025-04-03 20:53:09.506565',
                   '2025-04-03 21:23:09.506565', '2025-04-03 21:53:09.506565',
                   '2025-04-03 22:23:09.506565', '2025-04-03 22:53:09.506565',
                   '2025-04-03 23:23:09.506565', '2025-04-03 23:53:09.506565',
                   '2025-04-04 00:23:09.506565', '2025-04-04 00:53:09.506565',
                   '2025-04-04 01:23:09.506565', '2025-04-04 01:53:09.506565',
                   '2025-04-04 02:23:09.506565', '2025-04-04 02:53:09.506565',
                   '2025-04-04 03:23:09.506565', '2025-04-04 03:53:09.506565',
                   '2025-04-04 04:23:09.506565', '2025-04-04 04:53:09.506565',
                   '2025-04-04 05:23:09.506565', '2025-04-04 05:53:09.506565',
                   '2025-04-04 06:23:09.506565', '2025-04-04 06:53:09.506565',
                   '2025-04-04 07:23:09.506565', '2025-04-04 07:53:09.506565',
                   '2025-04-04 08:23:09.506565', '2025-04-04 08:53:09.506565',
                   '2025-04-04 09:23:09.506565', '2025-04-04 09:53:09.506565',
                   '2025-04-04 10:23:09.506565', '2025-04-04 10:53:09.506565',
                   '2025-04-04 11:23:09.506565', '2025-04-04 11:53:09.506565',
                   '2025-04-04 12:23:09.506565', '2025-04-04 12:53:09.506565',
                   '2025-04-04 13:23:09.506565', '2025-04-04 13:53:09.506565',
                   '2025-04-04 14:23:09.506565', '2025-04-04 14:53:09.506565',
                   '2025-04-04 15:23:09.506565', '2025-04-04 15:53:09.506565',
                   '2025-04-04 16:23:09.506565', '2025-04-04 16:53:09.506565',
                   '2025-04-04 17:23:09.506565', '2025-04-04 17:53:09.506565',
                   '2025-04-04 18:23:09.506565', '2025-04-04 18:53:09.506565',
                   '2025-04-04 19:23:09.506565', '2025-04-04 19:53:09.506565',
                   '2025-04-04 20:23:09.506565', '2025-04-04 20:53:09.506565',
                   '2025-04-04 21:23:09.506565', '2025-04-04 21:53:09.506565',
                   '2025-04-04 22:23:09.506565', '2025-04-04 22:53:09.506565',
                   '2025-04-04 23:23:09.506565', '2025-04-04 23:53:09.506565',
                   '2025-04-05 00:23:09.506565', '2025-04-05 00:53:09.506565',
                   '2025-04-05 01:23:09.506565', '2025-04-05 01:53:09.506565',
                   '2025-04-05 02:23:09.506565', '2025-04-05 02:53:09.506565',
                   '2025-04-05 03:23:09.506565'],
                  dtype='datetime64[ns]', name='time', freq='30min'))

• Attributes: (122)

  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 2025-04-03 15:23:13.601458

  date_created :

  2025-04-03T15:23:13.601477

  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 :

  2025-04-03 15:23:09.506565

  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_mixing :

  True

  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 :

  1.13.1

  seed_geojson :

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

  simulation_time :

  2025-04-03 15:23:13.661047

  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 :

  2025-04-05 03:23:09.506565

  time_coverage_duration :

  P1DT12H0M0S

  time_coverage_resolution :

  P0DT0H10M0S

  performance :

  -------------------- Reader performance: -------------------- global_landmask 0:00:02.8 total 0:00:00.0 preparing 0:00:02.7 reading 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be 0:03:51.2 total 0:00:00.0 preparing 0:03:45.6 reading 0:00:05.7 interpolation 0:00:00.1 interpolation_time 0:00:05.5 rotating vectors 0:00:00.0 masking -------------------- Performance: 4:10.0 total time 4.0 configuration 0.1 preparing main loop 0.0 moving elements to ocean 4:05.8 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 :

  59.111835

  geospatial_lat_max :

  59.18872

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  10.891997

  geospatial_lon_max :

  11.038944

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:04:10.024443

  geospatial_vertical_min :

  -14.039592

  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'])

15:27:34 INFO    opendrift:4600: Saving animation to /root/project/docs/source/gallery/animations/example_sediments_0.gif...
15:28:18 INFO    opendrift:3036: Time to make animation: 0:00:53.582480