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'])

10:48:28 INFO    opendrift:509: OpenDriftSimulation initialised (version 1.13.1 / v1.13.1-25-g5021161)

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))

10:48:28 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
10:48:33 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
10:48:33 INFO    opendrift.models.basemodel.environment:232:    x_sea_water_velocity: 0.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    y_sea_water_velocity: 0.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    sea_surface_height: 0.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    upward_sea_water_velocity: 0.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    x_wind: 0.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    y_wind: 0.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_x_velocity: 0.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_stokes_drift_y_velocity: 0.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_period_at_variance_spectral_density_maximum: 0.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment: 0.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    ocean_vertical_diffusivity: 0.020000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    ocean_mixed_layer_thickness: 50.000000
10:48:33 INFO    opendrift.models.basemodel.environment:232:    sea_floor_depth_below_sea_level: 10000.000000
10:48:33 INFO    opendrift:923: Using existing reader for land_binary_mask
10:48:33 INFO    opendrift:934: All points are in ocean
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10:48:33 INFO    opendrift.readers:61: Opening file with xr.open_dataset
10:48:35 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'X', 'y': 'Y', 'z': 'depth', 'time': 'time'}
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10:51:26 INFO    opendrift:2060: 2025-04-23 12:08:28.233923 - step 153 of 216 - 5312 active elements (0 deactivated)
10:51:27 INFO    opendrift:2060: 2025-04-23 12:18:28.233923 - step 154 of 216 - 5347 active elements (0 deactivated)
10:51:28 INFO    opendrift:2060: 2025-04-23 12:28:28.233923 - step 155 of 216 - 5382 active elements (0 deactivated)
10:51:29 INFO    opendrift:2060: 2025-04-23 12:38:28.233923 - step 156 of 216 - 5417 active elements (0 deactivated)
10:51:30 INFO    opendrift:2060: 2025-04-23 12:48:28.233923 - step 157 of 216 - 5451 active elements (0 deactivated)
10:51:31 INFO    opendrift:2060: 2025-04-23 12:58:28.233923 - step 158 of 216 - 5486 active elements (0 deactivated)
10:51:33 INFO    opendrift:2060: 2025-04-23 13:08:28.233923 - step 159 of 216 - 5521 active elements (0 deactivated)
10:51:34 INFO    opendrift:2060: 2025-04-23 13:18:28.233923 - step 160 of 216 - 5556 active elements (0 deactivated)
10:51:35 INFO    opendrift:2060: 2025-04-23 13:28:28.233923 - step 161 of 216 - 5590 active elements (0 deactivated)
10:51:36 INFO    opendrift:2060: 2025-04-23 13:38:28.233923 - step 162 of 216 - 5625 active elements (0 deactivated)
10:51:37 INFO    opendrift:2060: 2025-04-23 13:48:28.233923 - step 163 of 216 - 5660 active elements (0 deactivated)
10:51:38 INFO    opendrift:2060: 2025-04-23 13:58:28.233923 - step 164 of 216 - 5694 active elements (0 deactivated)
10:51:40 INFO    opendrift:2060: 2025-04-23 14:08:28.233923 - step 165 of 216 - 5729 active elements (0 deactivated)
10:51:41 INFO    opendrift:2060: 2025-04-23 14:18:28.233923 - step 166 of 216 - 5764 active elements (0 deactivated)
10:51:42 INFO    opendrift:2060: 2025-04-23 14:28:28.233923 - step 167 of 216 - 5799 active elements (0 deactivated)
10:51:43 INFO    opendrift:2060: 2025-04-23 14:38:28.233923 - step 168 of 216 - 5833 active elements (0 deactivated)
10:51:44 INFO    opendrift:2060: 2025-04-23 14:48:28.233923 - step 169 of 216 - 5868 active elements (0 deactivated)
10:51:45 INFO    opendrift:2060: 2025-04-23 14:58:28.233923 - step 170 of 216 - 5903 active elements (0 deactivated)
10:51:47 INFO    opendrift:2060: 2025-04-23 15:08:28.233923 - step 171 of 216 - 5937 active elements (0 deactivated)
10:51:48 INFO    opendrift:2060: 2025-04-23 15:18:28.233923 - step 172 of 216 - 5972 active elements (0 deactivated)
10:51:49 INFO    opendrift:2060: 2025-04-23 15:28:28.233923 - step 173 of 216 - 6007 active elements (0 deactivated)
10:51:50 INFO    opendrift:2060: 2025-04-23 15:38:28.233923 - step 174 of 216 - 6042 active elements (0 deactivated)
10:51:51 INFO    opendrift:2060: 2025-04-23 15:48:28.233923 - step 175 of 216 - 6076 active elements (0 deactivated)
10:51:52 INFO    opendrift:2060: 2025-04-23 15:58:28.233923 - step 176 of 216 - 6111 active elements (0 deactivated)
10:51:54 INFO    opendrift:2060: 2025-04-23 16:08:28.233923 - step 177 of 216 - 6146 active elements (0 deactivated)
10:51:55 INFO    opendrift:2060: 2025-04-23 16:18:28.233923 - step 178 of 216 - 6180 active elements (0 deactivated)
10:51:56 INFO    opendrift:2060: 2025-04-23 16:28:28.233923 - step 179 of 216 - 6215 active elements (0 deactivated)
10:51:57 INFO    opendrift:2060: 2025-04-23 16:38:28.233923 - step 180 of 216 - 6250 active elements (0 deactivated)
10:51:58 INFO    opendrift:2060: 2025-04-23 16:48:28.233923 - step 181 of 216 - 6285 active elements (0 deactivated)
10:51:59 INFO    opendrift:2060: 2025-04-23 16:58:28.233923 - step 182 of 216 - 6319 active elements (0 deactivated)
10:52:01 INFO    opendrift:2060: 2025-04-23 17:08:28.233923 - step 183 of 216 - 6354 active elements (0 deactivated)
10:52:02 INFO    opendrift:2060: 2025-04-23 17:18:28.233923 - step 184 of 216 - 6389 active elements (0 deactivated)
10:52:03 INFO    opendrift:2060: 2025-04-23 17:28:28.233923 - step 185 of 216 - 6423 active elements (0 deactivated)
10:52:04 INFO    opendrift:2060: 2025-04-23 17:38:28.233923 - step 186 of 216 - 6458 active elements (0 deactivated)
10:52:05 INFO    opendrift:2060: 2025-04-23 17:48:28.233923 - step 187 of 216 - 6493 active elements (0 deactivated)
10:52:06 INFO    opendrift:2060: 2025-04-23 17:58:28.233923 - step 188 of 216 - 6528 active elements (0 deactivated)
10:52:08 INFO    opendrift:2060: 2025-04-23 18:08:28.233923 - step 189 of 216 - 6562 active elements (0 deactivated)
10:52:09 INFO    opendrift:2060: 2025-04-23 18:18:28.233923 - step 190 of 216 - 6597 active elements (0 deactivated)
10:52:10 INFO    opendrift:2060: 2025-04-23 18:28:28.233923 - step 191 of 216 - 6632 active elements (0 deactivated)
10:52:11 INFO    opendrift:2060: 2025-04-23 18:38:28.233923 - step 192 of 216 - 6667 active elements (0 deactivated)
10:52:12 INFO    opendrift:2060: 2025-04-23 18:48:28.233923 - step 193 of 216 - 6701 active elements (0 deactivated)
10:52:13 INFO    opendrift:2060: 2025-04-23 18:58:28.233923 - step 194 of 216 - 6736 active elements (0 deactivated)
10:52:14 INFO    opendrift:2060: 2025-04-23 19:08:28.233923 - step 195 of 216 - 6771 active elements (0 deactivated)
10:52:16 INFO    opendrift:2060: 2025-04-23 19:18:28.233923 - step 196 of 216 - 6805 active elements (0 deactivated)
10:52:17 INFO    opendrift:2060: 2025-04-23 19:28:28.233923 - step 197 of 216 - 6840 active elements (0 deactivated)
10:52:18 INFO    opendrift:2060: 2025-04-23 19:38:28.233923 - step 198 of 216 - 6875 active elements (0 deactivated)
10:52:19 INFO    opendrift:2060: 2025-04-23 19:48:28.233923 - step 199 of 216 - 6910 active elements (0 deactivated)
10:52:20 INFO    opendrift:2060: 2025-04-23 19:58:28.233923 - step 200 of 216 - 6944 active elements (0 deactivated)
10:52:22 INFO    opendrift:2060: 2025-04-23 20:08:28.233923 - step 201 of 216 - 6979 active elements (0 deactivated)
10:52:23 INFO    opendrift:2060: 2025-04-23 20:18:28.233923 - step 202 of 216 - 7014 active elements (0 deactivated)
10:52:24 INFO    opendrift:2060: 2025-04-23 20:28:28.233923 - step 203 of 216 - 7048 active elements (0 deactivated)
10:52:25 INFO    opendrift:2060: 2025-04-23 20:38:28.233923 - step 204 of 216 - 7083 active elements (0 deactivated)
10:52:26 INFO    opendrift:2060: 2025-04-23 20:48:28.233923 - step 205 of 216 - 7118 active elements (0 deactivated)
10:52:27 INFO    opendrift:2060: 2025-04-23 20:58:28.233923 - step 206 of 216 - 7153 active elements (0 deactivated)
10:52:29 INFO    opendrift:2060: 2025-04-23 21:08:28.233923 - step 207 of 216 - 7187 active elements (0 deactivated)
10:52:30 INFO    opendrift:2060: 2025-04-23 21:18:28.233923 - step 208 of 216 - 7222 active elements (0 deactivated)
10:52:31 INFO    opendrift:2060: 2025-04-23 21:28:28.233923 - step 209 of 216 - 7257 active elements (0 deactivated)
10:52:32 INFO    opendrift:2060: 2025-04-23 21:38:28.233923 - step 210 of 216 - 7291 active elements (0 deactivated)
10:52:33 INFO    opendrift:2060: 2025-04-23 21:48:28.233923 - step 211 of 216 - 7326 active elements (0 deactivated)
10:52:34 INFO    opendrift:2060: 2025-04-23 21:58:28.233923 - step 212 of 216 - 7361 active elements (0 deactivated)
10:52:36 INFO    opendrift:2060: 2025-04-23 22:08:28.233923 - step 213 of 216 - 7396 active elements (0 deactivated)
10:52:37 INFO    opendrift:2060: 2025-04-23 22:18:28.233923 - step 214 of 216 - 7430 active elements (0 deactivated)
10:52:38 INFO    opendrift:2060: 2025-04-23 22:28:28.233923 - step 215 of 216 - 7465 active elements (0 deactivated)
10:52:39 INFO    opendrift:2060: 2025-04-23 22:38:28.233923 - step 216 of 216 - 7500 active elements (0 deactivated)
10:52:39 INFO    opendrift:2192: 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]
    2025-04-22T10:48:28.233923 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2025-04-22T10:48:28.233923000', '2025-04-22T11:18:28.233923000',
           '2025-04-22T11:48:28.233923000', '2025-04-22T12:18:28.233923000',
           '2025-04-22T12:48:28.233923000', '2025-04-22T13:18:28.233923000',
           '2025-04-22T13:48:28.233923000', '2025-04-22T14:18:28.233923000',
           '2025-04-22T14:48:28.233923000', '2025-04-22T15:18:28.233923000',
           '2025-04-22T15:48:28.233923000', '2025-04-22T16:18:28.233923000',
           '2025-04-22T16:48:28.233923000', '2025-04-22T17:18:28.233923000',
           '2025-04-22T17:48:28.233923000', '2025-04-22T18:18:28.233923000',
           '2025-04-22T18:48:28.233923000', '2025-04-22T19:18:28.233923000',
           '2025-04-22T19:48:28.233923000', '2025-04-22T20:18:28.233923000',
           '2025-04-22T20:48:28.233923000', '2025-04-22T21:18:28.233923000',
           '2025-04-22T21:48:28.233923000', '2025-04-22T22:18:28.233923000',
           '2025-04-22T22:48:28.233923000', '2025-04-22T23:18:28.233923000',
           '2025-04-22T23:48:28.233923000', '2025-04-23T00:18:28.233923000',
           '2025-04-23T00:48:28.233923000', '2025-04-23T01:18:28.233923000',
           '2025-04-23T01:48:28.233923000', '2025-04-23T02:18:28.233923000',
           '2025-04-23T02:48:28.233923000', '2025-04-23T03:18:28.233923000',
           '2025-04-23T03:48:28.233923000', '2025-04-23T04:18:28.233923000',
           '2025-04-23T04:48:28.233923000', '2025-04-23T05:18:28.233923000',
           '2025-04-23T05:48:28.233923000', '2025-04-23T06:18:28.233923000',
           '2025-04-23T06:48:28.233923000', '2025-04-23T07:18:28.233923000',
           '2025-04-23T07:48:28.233923000', '2025-04-23T08:18:28.233923000',
           '2025-04-23T08:48:28.233923000', '2025-04-23T09:18:28.233923000',
           '2025-04-23T09:48:28.233923000', '2025-04-23T10:18:28.233923000',
           '2025-04-23T10:48:28.233923000', '2025-04-23T11:18:28.233923000',
           '2025-04-23T11:48:28.233923000', '2025-04-23T12:18:28.233923000',
           '2025-04-23T12:48:28.233923000', '2025-04-23T13:18:28.233923000',
           '2025-04-23T13:48:28.233923000', '2025-04-23T14:18:28.233923000',
           '2025-04-23T14:48:28.233923000', '2025-04-23T15:18:28.233923000',
           '2025-04-23T15:48:28.233923000', '2025-04-23T16:18:28.233923000',
           '2025-04-23T16:48:28.233923000', '2025-04-23T17:18:28.233923000',
           '2025-04-23T17:48:28.233923000', '2025-04-23T18:18:28.233923000',
           '2025-04-23T18:48:28.233923000', '2025-04-23T19:18:28.233923000',
           '2025-04-23T19:48:28.233923000', '2025-04-23T20:18:28.233923000',
           '2025-04-23T20:48:28.233923000', '2025-04-23T21:18:28.233923000',
           '2025-04-23T21:48:28.233923000', '2025-04-23T22:18:28.233923000',
           '2025-04-23T22:48:28.233923000'], 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.,  1.,  1.],
           [ 1.,  1.,  1., ...,  1.,  1.,  1.],
           [ 1.,  1.,  0., ...,  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 :

    10.925449

    maxval :

    11.0376425

    array([[10.96292  , 10.9728775, 10.974221 , ..., 10.977104 , 10.972045 ,
            10.97259  ],
           [10.96292  , 10.977865 , 10.984288 , ..., 11.020218 , 11.023079 ,
            11.02141  ],
           [10.96292  , 10.969334 , 10.972602 , ..., 10.999234 , 11.001085 ,
            11.002262 ],
           ...,
           [       nan,        nan,        nan, ...,        nan,        nan,
            10.96629  ],
           [       nan,        nan,        nan, ...,        nan,        nan,
            10.967517 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
            10.967837 ]], 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 :

    59.10876

    maxval :

    59.188526

    array([[59.169193, 59.168514, 59.168495, ..., 59.159805, 59.15923 ,
            59.156254],
           [59.169193, 59.169743, 59.168613, ..., 59.152843, 59.15072 ,
            59.150303],
           [59.169193, 59.168324, 59.16899 , ..., 59.149773, 59.152275,
            59.15274 ],
           ...,
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.169403],
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.16936 ],
           [      nan,       nan,       nan, ...,       nan,       nan,
            59.16948 ]], dtype=float32)

  • z
    (trajectory, time)
    float32
    0.0 -5.647 -6.576 ... nan -3.647

    dtype :

    <class 'numpy.float32'>

    units :

    m

    standard_name :

    z

    long_name :

    vertical position

    axis :

    Z

    positive :

    up

    minval :

    -14.252508

    maxval :

    0.0

    array([[ 0.       , -5.6468396, -6.5757833, ..., -7.52963  , -7.2918444,
            -6.5017734],
           [ 0.       , -1.8539706, -5.5185738, ..., -1.552219 , -5.9659686,
            -5.9880347],
           [ 0.       , -3.7693653, -6.490991 , ..., -6.9966397, -6.7044563,
            -4.4293704],
           ...,
           [       nan,        nan,        nan, ...,        nan,        nan,
            -3.3155813],
           [       nan,        nan,        nan, ...,        nan,        nan,
            -0.7896019],
           [       nan,        nan,        nan, ...,        nan,        nan,
            -3.6468532]], 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
    0.7925 0.128 -0.3815 ... nan 0.5112

    minval :

    -1.036307

    maxval :

    1.2776885

    array([[ 0.79251784,  0.12803681, -0.38153493, ...,  0.09140937,
            -0.04190741,  0.0390189 ],
           [ 0.5197388 ,  0.23432755,  0.39257625, ...,  0.14496858,
            -0.15918301, -0.22192366],
           [ 0.63545495,  0.19337684,  0.03759148, ...,  0.17774184,
             0.03596044,  0.07626635],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.31080425],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.40507883],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.51122516]], dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    -0.1102 -0.003883 ... nan -0.03805

    minval :

    -1.054789

    maxval :

    0.8908701

    array([[-0.11015346, -0.00388341,  0.21684758, ..., -0.01852833,
            -0.33581012, -0.06333576],
           [ 0.10463488, -0.01167405,  0.22964221, ..., -0.37979996,
            -0.0767254 , -0.59667057],
           [ 0.09905271,  0.14684567,  0.0669758 , ..., -0.03200218,
             0.11403875, -0.02769809],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.04449857],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.02903766],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.03804713]], dtype=float32)

  • sea_surface_height
    (trajectory, time)
    float32
    -0.1429 -0.1472 ... nan -0.1287

    minval :

    -0.5033424

    maxval :

    -0.08431876

    array([[-0.14291795, -0.14715974, -0.16008496, ..., -0.20381948,
            -0.15979658, -0.13318616],
           [-0.14291795, -0.14655979, -0.15925728, ..., -0.20544015,
            -0.16747141, -0.13912697],
           [-0.14291795, -0.14805697, -0.16008969, ..., -0.20116949,
            -0.1523639 , -0.12637953],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.12867202],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.12867202],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -0.12867202]], dtype=float32)

  • upward_sea_water_velocity
    (trajectory, time)
    float32
    -1.04e-05 6.498e-06 ... 9.076e-06

    minval :

    -4.7281424e-05

    maxval :

    0.00078511384

    array([[-1.0404428e-05,  6.4977085e-06,  2.3841014e-05, ...,
             3.0706884e-05,  2.1987844e-05,  1.3327378e-05],
           [-1.0404428e-05,  9.8786204e-06, -8.3343521e-06, ...,
             2.6290189e-05,  8.0997224e-06,  1.0718932e-05],
           [-1.0404428e-05,  4.2210915e-05,  3.2291118e-05, ...,
             3.8708480e-05,  3.9663570e-05,  3.4006633e-05],
           ...,
           [           nan,            nan,            nan, ...,
                       nan,            nan,  9.0764570e-06],
           [           nan,            nan,            nan, ...,
                       nan,            nan,  9.0764570e-06],
           [           nan,            nan,            nan, ...,
                       nan,            nan,  9.0764570e-06]], dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    0.407 -3.341 -1.971 ... nan -2.127

    minval :

    -10.751842

    maxval :

    11.872439

    array([[ 0.4069948 , -3.3412113 , -1.970504  , ...,  1.1205096 ,
            -3.4718354 , -1.9615525 ],
           [-0.7932205 , -3.0009363 , -5.7083955 , ..., -1.6104993 ,
            -2.3614624 , -2.2134397 ],
           [ 1.227615  , -3.4539437 , -0.11972763, ..., -1.312724  ,
            -1.8187529 ,  1.5242194 ],
           ...,
           [        nan,         nan,         nan, ...,         nan,
                    nan,  0.52100307],
           [        nan,         nan,         nan, ...,         nan,
                    nan,  1.6545976 ],
           [        nan,         nan,         nan, ...,         nan,
                    nan, -2.1274648 ]], dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    1.548 -2.611 -2.704 ... nan 4.552

    minval :

    -10.156245

    maxval :

    9.390057

    array([[ 1.5482414, -2.6111877, -2.7036395, ...,  3.3679228,  4.6203346,
             0.8274094],
           [-3.1662388, -4.2812843, -3.3587985, ...,  2.614408 ,  2.1877406,
             1.1430103],
           [-3.8339105, -5.5207467, -0.5530231, ...,  2.5060797, -1.1090629,
             1.4208742],
           ...,
           [       nan,        nan,        nan, ...,        nan,        nan,
             4.175105 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
             3.013755 ],
           [       nan,        nan,        nan, ...,        nan,        nan,
             4.551836 ]], 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
    1.368 3.623 2.859 ... nan nan 4.293

    minval :

    0.0074187345

    maxval :

    10.189628

    array([[1.3678726, 3.623398 , 2.8586547, ..., 3.0328825, 4.938303 ,
            1.8190984],
           [2.7890666, 4.46742  , 5.6593637, ..., 2.6237726, 2.7506409,
            2.1286075],
           [3.439805 , 5.5644584, 0.4834894, ..., 2.417364 , 1.8202196,
            1.7805265],
           ...,
           [      nan,       nan,       nan, ...,       nan,       nan,
            3.5951738],
           [      nan,       nan,       nan, ...,       nan,       nan,
            2.9377408],
           [      nan,       nan,       nan, ...,       nan,       nan,
            4.2932634]], 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 6.802 6.742 ... nan nan 6.592

    minval :

    5.0

    maxval :

    14.983475

    array([[6.59209  , 6.8019505, 6.7417016, ..., 7.8572407, 8.028163 ,
            8.463843 ],
           [6.59209  , 6.610484 , 6.9261   , ..., 5.318414 , 6.1655064,
            6.452329 ],
           [6.59209  , 6.829787 , 6.7013583, ..., 8.191052 , 7.4513836,
            8.309998 ],
           ...,
           [      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(['2025-04-22 10:48:28.233923', '2025-04-22 11:18:28.233923',
                   '2025-04-22 11:48:28.233923', '2025-04-22 12:18:28.233923',
                   '2025-04-22 12:48:28.233923', '2025-04-22 13:18:28.233923',
                   '2025-04-22 13:48:28.233923', '2025-04-22 14:18:28.233923',
                   '2025-04-22 14:48:28.233923', '2025-04-22 15:18:28.233923',
                   '2025-04-22 15:48:28.233923', '2025-04-22 16:18:28.233923',
                   '2025-04-22 16:48:28.233923', '2025-04-22 17:18:28.233923',
                   '2025-04-22 17:48:28.233923', '2025-04-22 18:18:28.233923',
                   '2025-04-22 18:48:28.233923', '2025-04-22 19:18:28.233923',
                   '2025-04-22 19:48:28.233923', '2025-04-22 20:18:28.233923',
                   '2025-04-22 20:48:28.233923', '2025-04-22 21:18:28.233923',
                   '2025-04-22 21:48:28.233923', '2025-04-22 22:18:28.233923',
                   '2025-04-22 22:48:28.233923', '2025-04-22 23:18:28.233923',
                   '2025-04-22 23:48:28.233923', '2025-04-23 00:18:28.233923',
                   '2025-04-23 00:48:28.233923', '2025-04-23 01:18:28.233923',
                   '2025-04-23 01:48:28.233923', '2025-04-23 02:18:28.233923',
                   '2025-04-23 02:48:28.233923', '2025-04-23 03:18:28.233923',
                   '2025-04-23 03:48:28.233923', '2025-04-23 04:18:28.233923',
                   '2025-04-23 04:48:28.233923', '2025-04-23 05:18:28.233923',
                   '2025-04-23 05:48:28.233923', '2025-04-23 06:18:28.233923',
                   '2025-04-23 06:48:28.233923', '2025-04-23 07:18:28.233923',
                   '2025-04-23 07:48:28.233923', '2025-04-23 08:18:28.233923',
                   '2025-04-23 08:48:28.233923', '2025-04-23 09:18:28.233923',
                   '2025-04-23 09:48:28.233923', '2025-04-23 10:18:28.233923',
                   '2025-04-23 10:48:28.233923', '2025-04-23 11:18:28.233923',
                   '2025-04-23 11:48:28.233923', '2025-04-23 12:18:28.233923',
                   '2025-04-23 12:48:28.233923', '2025-04-23 13:18:28.233923',
                   '2025-04-23 13:48:28.233923', '2025-04-23 14:18:28.233923',
                   '2025-04-23 14:48:28.233923', '2025-04-23 15:18:28.233923',
                   '2025-04-23 15:48:28.233923', '2025-04-23 16:18:28.233923',
                   '2025-04-23 16:48:28.233923', '2025-04-23 17:18:28.233923',
                   '2025-04-23 17:48:28.233923', '2025-04-23 18:18:28.233923',
                   '2025-04-23 18:48:28.233923', '2025-04-23 19:18:28.233923',
                   '2025-04-23 19:48:28.233923', '2025-04-23 20:18:28.233923',
                   '2025-04-23 20:48:28.233923', '2025-04-23 21:18:28.233923',
                   '2025-04-23 21:48:28.233923', '2025-04-23 22:18:28.233923',
                   '2025-04-23 22:48:28.233923'],
                  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 2025-04-22 10:48:33.607860

  date_created :

  2025-04-22T10:48:33.607882

  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 :

  2025-04-22 10:48:28.233923

  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 :

  2025-04-22 10:48:33.703180

  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 :

  2025-04-23 22:48:28.233923

  time_coverage_duration :

  P1DT12H0M0S

  time_coverage_resolution :

  P0DT0H10M0S

  performance :

  -------------------- Reader performance: -------------------- global_landmask 0:00:02.9 total 0:00:00.0 preparing 0:00:02.8 reading 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be 0:03:50.7 total 0:00:00.0 preparing 0:03:45.2 reading 0:00:08.3 interpolation 0:00:00.1 interpolation_time 0:00:05.3 rotating vectors 0:00:00.0 masking -------------------- Performance: 4:11.7 total time 5.4 configuration 0.1 preparing main loop 0.0 moving elements to ocean 4:06.1 main loop 4.6 updating elements 3.7 vertical mixing 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  59.10876

  geospatial_lat_max :

  59.188526

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  10.925449

  geospatial_lon_max :

  11.0376425

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:04:11.784203

  geospatial_vertical_min :

  -14.252508

  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'])

10:52:58 INFO    opendrift:4607: Saving animation to /root/project/docs/source/gallery/animations/example_sediments_0.gif...
10:53:45 INFO    opendrift:3043: Time to make animation: 0:00:59.371644