Cod egg

from opendrift.readers import reader_netCDF_CF_generic
from opendrift.models.pelagicegg import PelagicEggDrift
from datetime import datetime, timedelta

o = PelagicEggDrift(loglevel=20)  # Set loglevel to 0 for debug information

# Forcing with Topaz ocean model and MEPS atmospheric model
o.add_readers_from_list([
    'https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml',
    'https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc'])

14:21:54 INFO    opendrift:569: OpenDriftSimulation initialised (version 1.14.3 / v1.14.3-25-gcd89af5)

Adjusting some configuration

o.set_config('drift:vertical_mixing', True)
o.set_config('vertical_mixing:diffusivitymodel', 'windspeed_Sundby1983') # windspeed parameterization for eddy diffusivity

Vertical mixing requires fast time step

o.set_config('vertical_mixing:timestep', 60.) # seconds

spawn NEA cod eggs at defined position and time

time = datetime.now()
o.seed_elements(14. , 68.1, z=-40, radius=2000, number=500,
                time=time, diameter=0.0014, neutral_buoyancy_salinity=31.25)
o.seed_elements(12.5, 68., z=-40, radius=2000, number=500,
                time=time, diameter=0.0014, neutral_buoyancy_salinity=31.25)
o.seed_elements(13.5, 68., z=-40, radius=2000, number=500,
                time=time, diameter=0.0014, neutral_buoyancy_salinity=31.25)
o.seed_elements(13., 67.8, z=-40, radius=2000, number=500,
                time=time, diameter=0.0014, neutral_buoyancy_salinity=31.25)

14:21:54 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
14:21:58 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
14:21:58 INFO    opendrift.models.basemodel.environment:232:    x_sea_water_velocity: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    y_sea_water_velocity: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    sea_surface_height: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_significant_height: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    sea_ice_area_fraction: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    x_wind: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    y_wind: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    sea_floor_depth_below_sea_level: 100.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    ocean_vertical_diffusivity: 0.020000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    ocean_mixed_layer_thickness: 50.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    sea_water_temperature: 10.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    sea_water_salinity: 34.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    surface_downward_x_stress: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    surface_downward_y_stress: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    turbulent_kinetic_energy: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    turbulent_generic_length_scale: 0.000000
14:21:58 INFO    opendrift.models.basemodel.environment:232:    upward_sea_water_velocity: 0.000000

Running model

o.run(duration=timedelta(hours=48), time_step=3600)

14:21:58 INFO    opendrift:1790: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
14:21:58 INFO    opendrift:1790: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
14:21:58 INFO    opendrift:945: Using existing reader for land_binary_mask to move elements to ocean
14:21:58 INFO    opendrift:975: All points are in ocean
14:21:58 INFO    opendrift:2086: 2025-10-03 14:21:54.450134 - step 1 of 48 - 2000 active elements (0 deactivated)
14:21:58 INFO    opendrift.readers:63: Opening file with xr.open_dataset
14:22:00 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}
14:22:00 INFO    opendrift.readers:63: Opening file with xr.open_dataset
14:22:01 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'time': 'time', 'x': 'x', 'y': 'y'}
14:22:03 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:03 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:03 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:03 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:03 INFO    opendrift:2086: 2025-10-03 15:21:54.450134 - step 2 of 48 - 2000 active elements (0 deactivated)
14:22:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:05 INFO    opendrift:2086: 2025-10-03 16:21:54.450134 - step 3 of 48 - 2000 active elements (0 deactivated)
14:22:07 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:07 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:07 INFO    opendrift:2086: 2025-10-03 17:21:54.450134 - step 4 of 48 - 2000 active elements (0 deactivated)
14:22:11 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:11 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:11 INFO    opendrift:2086: 2025-10-03 18:21:54.450134 - step 5 of 48 - 2000 active elements (0 deactivated)
14:22:13 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:13 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:14 INFO    opendrift:2086: 2025-10-03 19:21:54.450134 - step 6 of 48 - 2000 active elements (0 deactivated)
14:22:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:16 INFO    opendrift:2086: 2025-10-03 20:21:54.450134 - step 7 of 48 - 2000 active elements (0 deactivated)
14:22:18 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:18 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:18 INFO    opendrift:2086: 2025-10-03 21:21:54.450134 - step 8 of 48 - 2000 active elements (0 deactivated)
14:22:20 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:20 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:20 INFO    opendrift:2086: 2025-10-03 22:21:54.450134 - step 9 of 48 - 2000 active elements (0 deactivated)
14:22:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:22 INFO    opendrift:2086: 2025-10-03 23:21:54.450134 - step 10 of 48 - 2000 active elements (0 deactivated)
14:22:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:24 INFO    opendrift:2086: 2025-10-04 00:21:54.450134 - step 11 of 48 - 2000 active elements (0 deactivated)
14:22:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:26 INFO    opendrift:2086: 2025-10-04 01:21:54.450134 - step 12 of 48 - 2000 active elements (0 deactivated)
14:22:28 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:28 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:28 INFO    opendrift:2086: 2025-10-04 02:21:54.450134 - step 13 of 48 - 2000 active elements (0 deactivated)
14:22:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:30 INFO    opendrift:2086: 2025-10-04 03:21:54.450134 - step 14 of 48 - 2000 active elements (0 deactivated)
14:22:32 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:32 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:32 INFO    opendrift:2086: 2025-10-04 04:21:54.450134 - step 15 of 48 - 2000 active elements (0 deactivated)
14:22:34 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:34 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:34 INFO    opendrift:2086: 2025-10-04 05:21:54.450134 - step 16 of 48 - 2000 active elements (0 deactivated)
14:22:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:36 INFO    opendrift:2086: 2025-10-04 06:21:54.450134 - step 17 of 48 - 2000 active elements (0 deactivated)
14:22:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:38 INFO    opendrift:2086: 2025-10-04 07:21:54.450134 - step 18 of 48 - 2000 active elements (0 deactivated)
14:22:39 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:39 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:40 INFO    opendrift:2086: 2025-10-04 08:21:54.450134 - step 19 of 48 - 2000 active elements (0 deactivated)
14:22:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:42 INFO    opendrift:2086: 2025-10-04 09:21:54.450134 - step 20 of 48 - 2000 active elements (0 deactivated)
14:22:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:44 INFO    opendrift:2086: 2025-10-04 10:21:54.450134 - step 21 of 48 - 2000 active elements (0 deactivated)
14:22:46 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:46 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:46 INFO    opendrift:2086: 2025-10-04 11:21:54.450134 - step 22 of 48 - 2000 active elements (0 deactivated)
14:22:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:48 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:48 INFO    opendrift:2086: 2025-10-04 12:21:54.450134 - step 23 of 48 - 2000 active elements (0 deactivated)
14:22:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:50 INFO    opendrift:2086: 2025-10-04 13:21:54.450134 - step 24 of 48 - 2000 active elements (0 deactivated)
14:22:52 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:52 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:52 INFO    opendrift:2086: 2025-10-04 14:21:54.450134 - step 25 of 48 - 2000 active elements (0 deactivated)
14:22:55 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:55 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:55 INFO    opendrift:2086: 2025-10-04 15:21:54.450134 - step 26 of 48 - 2000 active elements (0 deactivated)
14:22:57 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:57 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:57 INFO    opendrift:2086: 2025-10-04 16:21:54.450134 - step 27 of 48 - 2000 active elements (0 deactivated)
14:22:59 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:59 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:22:59 INFO    opendrift:2086: 2025-10-04 17:21:54.450134 - step 28 of 48 - 2000 active elements (0 deactivated)
14:23:02 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:02 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:02 INFO    opendrift:2086: 2025-10-04 18:21:54.450134 - step 29 of 48 - 2000 active elements (0 deactivated)
14:23:04 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:04 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:04 INFO    opendrift:2086: 2025-10-04 19:21:54.450134 - step 30 of 48 - 2000 active elements (0 deactivated)
14:23:06 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:06 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:06 INFO    opendrift:2086: 2025-10-04 20:21:54.450134 - step 31 of 48 - 2000 active elements (0 deactivated)
14:23:08 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:08 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:08 INFO    opendrift:2086: 2025-10-04 21:21:54.450134 - step 32 of 48 - 2000 active elements (0 deactivated)
14:23:10 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:10 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:10 INFO    opendrift:2086: 2025-10-04 22:21:54.450134 - step 33 of 48 - 2000 active elements (0 deactivated)
14:23:12 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:12 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:12 INFO    opendrift:2086: 2025-10-04 23:21:54.450134 - step 34 of 48 - 2000 active elements (0 deactivated)
14:23:14 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:14 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:15 INFO    opendrift:2086: 2025-10-05 00:21:54.450134 - step 35 of 48 - 2000 active elements (0 deactivated)
14:23:17 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:17 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:17 INFO    opendrift:2086: 2025-10-05 01:21:54.450134 - step 36 of 48 - 2000 active elements (0 deactivated)
14:23:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:19 INFO    opendrift:2086: 2025-10-05 02:21:54.450134 - step 37 of 48 - 2000 active elements (0 deactivated)
14:23:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:22 INFO    opendrift:2086: 2025-10-05 03:21:54.450134 - step 38 of 48 - 2000 active elements (0 deactivated)
14:23:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:24 INFO    opendrift:2086: 2025-10-05 04:21:54.450134 - step 39 of 48 - 2000 active elements (0 deactivated)
14:23:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:26 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:27 INFO    opendrift:2086: 2025-10-05 05:21:54.450134 - step 40 of 48 - 2000 active elements (0 deactivated)
14:23:28 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:28 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:29 INFO    opendrift:2086: 2025-10-05 06:21:54.450134 - step 41 of 48 - 2000 active elements (0 deactivated)
14:23:31 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:31 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:31 INFO    opendrift:2086: 2025-10-05 07:21:54.450134 - step 42 of 48 - 2000 active elements (0 deactivated)
14:23:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:33 INFO    opendrift:2086: 2025-10-05 08:21:54.450134 - step 43 of 48 - 2000 active elements (0 deactivated)
14:23:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:35 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:35 INFO    opendrift:2086: 2025-10-05 09:21:54.450134 - step 44 of 48 - 2000 active elements (0 deactivated)
14:23:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:37 INFO    opendrift:2086: 2025-10-05 10:21:54.450134 - step 45 of 48 - 2000 active elements (0 deactivated)
14:23:39 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:39 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:39 INFO    opendrift:2086: 2025-10-05 11:21:54.450134 - step 46 of 48 - 2000 active elements (0 deactivated)
14:23:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:41 INFO    opendrift:2086: 2025-10-05 12:21:54.450134 - step 47 of 48 - 2000 active elements (0 deactivated)
14:23:43 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:43 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:43 INFO    opendrift:2086: 2025-10-05 13:21:54.450134 - step 48 of 48 - 2000 active elements (0 deactivated)
14:23:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
14:23:45 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor

<xarray.Dataset> Size: 13MB
Dimensions:                              (trajectory: 2000, time: 49)
Coordinates:
  * trajectory                           (trajectory) int64 16kB 0 1 ... 1999
  * time                                 (time) datetime64[ns] 392B 2025-10-0...
Data variables: (12/32)
    status                               (trajectory, time) float32 392kB 0.0...
    moving                               (trajectory, time) float32 392kB 1.0...
    age_seconds                          (trajectory, time) float32 392kB 0.0...
    origin_marker                        (trajectory, time) float32 392kB 0.0...
    lon                                  (trajectory, time) float32 392kB 14....
    lat                                  (trajectory, time) float32 392kB 68....
    ...                                   ...
    sea_water_salinity                   (trajectory, time) float32 392kB 34....
    surface_downward_x_stress            (trajectory, time) float32 392kB 0.0...
    surface_downward_y_stress            (trajectory, time) float32 392kB 0.0...
    turbulent_kinetic_energy             (trajectory, time) float32 392kB 0.0...
    turbulent_generic_length_scale       (trajectory, time) float32 392kB 0.0...
    upward_sea_water_velocity            (trajectory, time) float32 392kB 0.0...
Attributes: (12/140)
    Conventions:                                                      CF-1.11...
    standard_name_vocabulary:                                         CF Stan...
    featureType:                                                      trajectory
    title:                                                            OpenDri...
    summary:                                                          Output ...
    keywords:                                                         traject...
    ...                                                               ...
    geospatial_lon_units:                                             degrees...
    geospatial_lon_resolution:                                        point
    runtime:                                                          0:01:51...
    geospatial_vertical_min:                                          -53.267063
    geospatial_vertical_max:                                          0.0
    geospatial_vertical_positive:                                     up

xarray.Dataset

• Dimensions:
  • trajectory: 2000
  • time: 49
• Coordinates: (2)
  • trajectory
    (trajectory)
    int64
    0 1 2 3 4 ... 1996 1997 1998 1999

    cf_role :

    trajectory_id

    dtype :

    <class 'numpy.int32'>

    array([   0,    1,    2, ..., 1997, 1998, 1999], shape=(2000,))

  • time
    (time)
    datetime64[ns]
    2025-10-03T14:21:54.450134 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2025-10-03T14:21:54.450134000', '2025-10-03T15:21:54.450134000',
           '2025-10-03T16:21:54.450134000', '2025-10-03T17:21:54.450134000',
           '2025-10-03T18:21:54.450134000', '2025-10-03T19:21:54.450134000',
           '2025-10-03T20:21:54.450134000', '2025-10-03T21:21:54.450134000',
           '2025-10-03T22:21:54.450134000', '2025-10-03T23:21:54.450134000',
           '2025-10-04T00:21:54.450134000', '2025-10-04T01:21:54.450134000',
           '2025-10-04T02:21:54.450134000', '2025-10-04T03:21:54.450134000',
           '2025-10-04T04:21:54.450134000', '2025-10-04T05:21:54.450134000',
           '2025-10-04T06:21:54.450134000', '2025-10-04T07:21:54.450134000',
           '2025-10-04T08:21:54.450134000', '2025-10-04T09:21:54.450134000',
           '2025-10-04T10:21:54.450134000', '2025-10-04T11:21:54.450134000',
           '2025-10-04T12:21:54.450134000', '2025-10-04T13:21:54.450134000',
           '2025-10-04T14:21:54.450134000', '2025-10-04T15:21:54.450134000',
           '2025-10-04T16:21:54.450134000', '2025-10-04T17:21:54.450134000',
           '2025-10-04T18:21:54.450134000', '2025-10-04T19:21:54.450134000',
           '2025-10-04T20:21:54.450134000', '2025-10-04T21:21:54.450134000',
           '2025-10-04T22:21:54.450134000', '2025-10-04T23:21:54.450134000',
           '2025-10-05T00:21:54.450134000', '2025-10-05T01:21:54.450134000',
           '2025-10-05T02:21:54.450134000', '2025-10-05T03:21:54.450134000',
           '2025-10-05T04:21:54.450134000', '2025-10-05T05:21:54.450134000',
           '2025-10-05T06:21:54.450134000', '2025-10-05T07:21:54.450134000',
           '2025-10-05T08:21:54.450134000', '2025-10-05T09:21:54.450134000',
           '2025-10-05T10:21:54.450134000', '2025-10-05T11:21:54.450134000',
           '2025-10-05T12:21:54.450134000', '2025-10-05T13:21:54.450134000',
           '2025-10-05T14:21:54.450134000'], dtype='datetime64[ns]')

• Data variables: (32)
  • status
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.int32'>

    valid_range :

    [0 0]

    flag_values :

    [0]

    flag_meanings :

    active

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(2000, 49), dtype=float32)

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

    dtype :

    <class 'numpy.int32'>

    minval :

    1

    maxval :

    1

    array([[1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(2000, 49), dtype=float32)

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

    dtype :

    <class 'numpy.float32'>

    units :

    s

    minval :

    0.0

    maxval :

    172800.0

    array([[     0.,   3600.,   7200., ..., 165600., 169200., 172800.],
           [     0.,   3600.,   7200., ..., 165600., 169200., 172800.],
           [     0.,   3600.,   7200., ..., 165600., 169200., 172800.],
           ...,
           [     0.,   3600.,   7200., ..., 165600., 169200., 172800.],
           [     0.,   3600.,   7200., ..., 165600., 169200., 172800.],
           [     0.,   3600.,   7200., ..., 165600., 169200., 172800.]],
          shape=(2000, 49), dtype=float32)

  • origin_marker
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 3.0 3.0 3.0 3.0

    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 1 2 3]

    flag_meanings :

    Seed_0 Seed_1 Seed_2 Seed_3

    minval :

    0

    maxval :

    3

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [3., 3., 3., ..., 3., 3., 3.],
           [3., 3., 3., ..., 3., 3., 3.],
           [3., 3., 3., ..., 3., 3., 3.]], shape=(2000, 49), dtype=float32)

  • lon
    (trajectory, time)
    float32
    14.08 14.09 14.09 ... 12.52 12.49

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    12.314689

    maxval :

    14.16527

    array([[14.084752 , 14.087102 , 14.090194 , ..., 13.990854 , 13.99416  ,
            13.997019 ],
           [14.019218 , 14.022503 , 14.026568 , ..., 13.941078 , 13.93935  ,
            13.937635 ],
           [14.047049 , 14.05003  , 14.0536995, ..., 13.989718 , 13.991634 ,
            13.991634 ],
           ...,
           [13.055853 , 13.056958 , 13.064766 , ..., 12.554111 , 12.526219 ,
            12.506009 ],
           [13.005157 , 13.009913 , 13.02102  , ..., 12.5462885, 12.545316 ,
            12.547042 ],
           [13.002091 , 13.00546  , 13.015725 , ..., 12.54773  , 12.51508  ,
            12.490213 ]], shape=(2000, 49), dtype=float32)

  • lat
    (trajectory, time)
    float32
    68.11 68.11 68.11 ... 67.93 67.95

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    67.732445

    maxval :

    68.398926

    array([[68.10684 , 68.107445, 68.10895 , ..., 68.19957 , 68.20115 ,
            68.20115 ],
           [68.09939 , 68.10027 , 68.101944, ..., 68.17332 , 68.17565 ,
            68.17763 ],
           [68.11965 , 68.12033 , 68.12174 , ..., 68.19485 , 68.19902 ,
            68.20074 ],
           ...,
           [67.79944 , 67.80291 , 67.80581 , ..., 67.93397 , 67.952774,
            67.97238 ],
           [67.82828 , 67.83078 , 67.83229 , ..., 68.05922 , 68.07328 ,
            68.08797 ],
           [67.78542 , 67.78852 , 67.79045 , ..., 67.91479 , 67.933235,
            67.95235 ]], shape=(2000, 49), dtype=float32)

  • z
    (trajectory, time)
    float32
    -40.0 -46.2 ... -32.28 -39.11

    dtype :

    <class 'numpy.float32'>

    units :

    m

    standard_name :

    z

    long_name :

    vertical position

    axis :

    Z

    positive :

    up

    minval :

    -53.267063

    maxval :

    0.0

    array([[-40.        , -46.20146   , -43.37372   , ...,  -3.7991493 ,
             -1.6706394 ,  -0.63777953],
           [-40.        , -46.28473   , -47.148888  , ..., -13.729342  ,
            -12.662469  , -43.316986  ],
           [-40.        , -27.074774  ,  -9.055048  , ..., -11.126631  ,
             -3.6710615 , -11.814697  ],
           ...,
           [-40.        , -37.481068  , -34.532734  , ..., -34.335617  ,
            -36.150887  , -40.548668  ],
           [-40.        , -29.104267  , -13.034151  , ..., -29.040327  ,
             -4.476101  ,  -9.688441  ],
           [-40.        , -40.288982  , -27.053722  , ..., -48.403553  ,
            -32.277668  , -39.10886   ]], shape=(2000, 49), dtype=float32)

  • wind_drift_factor
    (trajectory, time)
    float32
    0.02 0.02 0.02 ... 0.02 0.02 0.02

    dtype :

    <class 'numpy.float32'>

    units :

    1

    description :

    Elements at surface are moved with this fraction of the vind vector, in addition to currents and Stokes drift

    minval :

    0.02

    maxval :

    0.02

    array([[0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           ...,
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02]],
          shape=(2000, 49), dtype=float32)

  • current_drift_factor
    (trajectory, time)
    float32
    1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0

    dtype :

    <class 'numpy.float32'>

    units :

    1

    description :

    Elements are moved with this fraction of the current vector, in addition to currents and Stokes drift

    minval :

    1.0

    maxval :

    1.0

    array([[1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           ...,
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.],
           [1., 1., 1., ..., 1., 1., 1.]], shape=(2000, 49), dtype=float32)

  • terminal_velocity
    (trajectory, time)
    float32
    0.0 0.001324 ... 0.001324 0.001324

    dtype :

    <class 'numpy.float32'>

    units :

    m/s

    description :

    Terminal rise/sinking velocity (buoyancy) in the ocean column

    minval :

    0.0

    maxval :

    0.0013238009

    array([[0.       , 0.0013238, 0.0013238, ..., 0.0013238, 0.0013238,
            0.0013238],
           [0.       , 0.0013238, 0.0013238, ..., 0.0013238, 0.0013238,
            0.0013238],
           [0.       , 0.0013238, 0.0013238, ..., 0.0013238, 0.0013238,
            0.0013238],
           ...,
           [0.       , 0.0013238, 0.0013238, ..., 0.0013238, 0.0013238,
            0.0013238],
           [0.       , 0.0013238, 0.0013238, ..., 0.0013238, 0.0013238,
            0.0013238],
           [0.       , 0.0013238, 0.0013238, ..., 0.0013238, 0.0013238,
            0.0013238]], shape=(2000, 49), dtype=float32)

  • diameter
    (trajectory, time)
    float32
    0.0014 0.0014 ... 0.0014 0.0014

    dtype :

    <class 'numpy.float32'>

    units :

    m

    minval :

    0.0014

    maxval :

    0.0014

    array([[0.0014, 0.0014, 0.0014, ..., 0.0014, 0.0014, 0.0014],
           [0.0014, 0.0014, 0.0014, ..., 0.0014, 0.0014, 0.0014],
           [0.0014, 0.0014, 0.0014, ..., 0.0014, 0.0014, 0.0014],
           ...,
           [0.0014, 0.0014, 0.0014, ..., 0.0014, 0.0014, 0.0014],
           [0.0014, 0.0014, 0.0014, ..., 0.0014, 0.0014, 0.0014],
           [0.0014, 0.0014, 0.0014, ..., 0.0014, 0.0014, 0.0014]],
          shape=(2000, 49), dtype=float32)

  • neutral_buoyancy_salinity
    (trajectory, time)
    float32
    31.25 31.25 31.25 ... 31.25 31.25

    dtype :

    <class 'numpy.float32'>

    units :

    []

    minval :

    31.25

    maxval :

    31.25

    array([[31.25, 31.25, 31.25, ..., 31.25, 31.25, 31.25],
           [31.25, 31.25, 31.25, ..., 31.25, 31.25, 31.25],
           [31.25, 31.25, 31.25, ..., 31.25, 31.25, 31.25],
           ...,
           [31.25, 31.25, 31.25, ..., 31.25, 31.25, 31.25],
           [31.25, 31.25, 31.25, ..., 31.25, 31.25, 31.25],
           [31.25, 31.25, 31.25, ..., 31.25, 31.25, 31.25]],
          shape=(2000, 49), dtype=float32)

  • density
    (trajectory, time)
    float32
    1.028e+03 1.028e+03 ... 1.028e+03

    dtype :

    <class 'numpy.float32'>

    units :

    kg/m^3

    minval :

    1028.0

    maxval :

    1028.0

    array([[1028., 1028., 1028., ..., 1028., 1028., 1028.],
           [1028., 1028., 1028., ..., 1028., 1028., 1028.],
           [1028., 1028., 1028., ..., 1028., 1028., 1028.],
           ...,
           [1028., 1028., 1028., ..., 1028., 1028., 1028.],
           [1028., 1028., 1028., ..., 1028., 1028., 1028.],
           [1028., 1028., 1028., ..., 1028., 1028., 1028.]],
          shape=(2000, 49), dtype=float32)

  • hatched
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    dtype :

    <class 'numpy.float32'>

    units :

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(2000, 49), dtype=float32)

  • x_sea_water_velocity
    (trajectory, time)
    float32
    0.02717 0.03575 ... -0.2895 -0.2895

    minval :

    -1.0469831

    maxval :

    0.41365573

    array([[ 0.0271669 ,  0.03575149,  0.04721687, ...,  0.03806308,
             0.03292501,  0.03292501],
           [ 0.03798839,  0.04702887,  0.05498756, ..., -0.01991482,
            -0.01977331, -0.01977331],
           [ 0.03445357,  0.04241017,  0.05052367, ...,  0.02206211,
             0.02106068,  0.02106068],
           ...,
           [ 0.0129548 ,  0.09145837,  0.12832241, ..., -0.32467327,
            -0.23506308, -0.23506308],
           [ 0.05565307,  0.12996183,  0.14476071, ..., -0.01126514,
             0.01998415,  0.01998415],
           [ 0.03948576,  0.12032755,  0.15146007, ..., -0.38039762,
            -0.2894733 , -0.2894733 ]], shape=(2000, 49), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    0.01862 0.04664 ... 0.5923 0.5923

    minval :

    -0.36069945

    maxval :

    0.85245454

    array([[0.01862488, 0.04664277, 0.06830394, ..., 0.14686368, 0.12013856,
            0.12013856],
           [0.02735886, 0.05192188, 0.06981795, ..., 0.0723309 , 0.06131261,
            0.06131261],
           [0.02102427, 0.04385224, 0.06236692, ..., 0.1294066 , 0.10634476,
            0.10634476],
           ...,
           [0.10757612, 0.08979751, 0.06342435, ..., 0.58260196, 0.6075628 ,
            0.6075628 ],
           [0.07749098, 0.04678395, 0.0212591 , ..., 0.43554512, 0.45510784,
            0.45510784],
           [0.09589824, 0.05981634, 0.02166138, ..., 0.5716411 , 0.5922996 ,
            0.5922996 ]], shape=(2000, 49), dtype=float32)

  • sea_surface_height
    (trajectory, time)
    float32
    -0.9122 -0.83 ... -0.1529 -0.1529

    minval :

    -1.2112589

    maxval :

    0.8177675

    array([[-0.9122329 , -0.83001626, -0.5940466 , ...,  0.2701205 ,
            -0.14930055, -0.14930055],
           [-0.9106842 , -0.82829314, -0.59302366, ...,  0.26980552,
            -0.15015611, -0.15015611],
           [-0.91201836, -0.8303462 , -0.59483564, ...,  0.27014023,
            -0.149602  , -0.149602  ],
           ...,
           [-0.88395375, -0.8006482 , -0.5872116 , ...,  0.1942412 ,
            -0.14811265, -0.14811265],
           [-0.8814317 , -0.80185217, -0.5903878 , ...,  0.17295031,
            -0.15900232, -0.15900232],
           [-0.88137317, -0.7977108 , -0.58484584, ...,  0.19065964,
            -0.15288559, -0.15288559]], shape=(2000, 49), dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    1.114 1.529 1.961 ... 4.564 4.564

    minval :

    0.29003945

    maxval :

    9.718283

    array([[1.1139392 , 1.5287861 , 1.9611622 , ..., 1.7143264 , 1.4239943 ,
            1.4239943 ],
           [1.6628509 , 2.1390893 , 1.646206  , ..., 2.9551215 , 2.693399  ,
            2.693399  ],
           [1.1885773 , 1.4635926 , 2.322197  , ..., 1.559834  , 1.4575764 ,
            1.4575764 ],
           ...,
           [0.6444926 , 0.5553348 , 0.5951708 , ..., 3.9230673 , 3.9452796 ,
            3.9452796 ],
           [0.9024722 , 1.2759832 , 1.7275074 , ..., 5.02784   , 4.7739897 ,
            4.7739897 ],
           [0.40646496, 0.38887918, 0.5553039 , ..., 4.821274  , 4.5641637 ,
            4.5641637 ]], shape=(2000, 49), dtype=float32)

  • sea_ice_area_fraction
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(2000, 49), dtype=float32)

  • x_wind
    (trajectory, time)
    float32
    -5.825 -5.96 ... -11.24 -11.24

    minval :

    -16.76613

    maxval :

    1.7558291

    array([[ -5.8252916,  -5.959511 ,  -4.4113593, ...,  -6.9432535,
             -6.3895173,  -6.3895173],
           [ -8.214516 ,  -9.270593 ,  -7.1179442, ...,  -7.8700905,
             -7.4060793,  -7.4060793],
           [ -6.3049173,  -5.803463 ,  -3.822085 , ...,  -7.23784  ,
             -6.948037 ,  -6.948037 ],
           ...,
           [ -3.2138255,  -2.140398 ,  -1.9075347, ..., -11.023686 ,
            -11.052853 , -11.052853 ],
           [ -4.2937965,  -4.3404236,  -4.822611 , ..., -11.674904 ,
            -11.195707 , -11.195707 ],
           [ -3.4975188,  -3.3103352,  -2.4154146, ..., -11.378521 ,
            -11.238975 , -11.238975 ]], shape=(2000, 49), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    3.369 5.16 7.763 ... 7.695 7.695

    minval :

    -0.05844176

    maxval :

    16.910013

    array([[3.3686876 , 5.1604266 , 7.762858  , ..., 4.6345754 , 4.130378  ,
            4.130378  ],
           [0.34248582, 1.0054725 , 4.0316024 , ..., 7.628144  , 7.391735  ,
            7.391735  ],
           [2.9264605 , 5.0808916 , 8.932521  , ..., 3.3198729 , 3.3129833 ,
            3.3129833 ],
           ...,
           [3.9837434 , 4.2418494 , 4.533789  , ..., 6.1605706 , 6.181558  ,
            6.181558  ],
           [4.2719054 , 5.74717   , 6.8531966 , ..., 8.251083  , 8.2898    ,
            8.2898    ],
           [2.0713105 , 2.2022212 , 4.0913444 , ..., 8.155736  , 7.6954894 ,
            7.6954894 ]], shape=(2000, 49), dtype=float32)

  • land_binary_mask
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(2000, 49), dtype=float32)

  • sea_floor_depth_below_sea_level
    (trajectory, time)
    float32
    91.6 91.3 90.59 ... 138.2 138.2

    minval :

    18.15371

    maxval :

    216.8858

    array([[ 91.5983  ,  91.30437 ,  90.59413 , ...,  24.525787,  23.411407,
             23.411407],
           [ 94.49078 ,  94.6548  ,  94.75074 , ...,  49.12142 ,  47.687828,
             47.687828],
           [ 86.55411 ,  86.17218 ,  85.429245, ...,  25.366638,  24.588863,
             24.588863],
           ...,
           [131.81073 , 130.1003  , 130.04636 , ..., 124.82852 , 137.53879 ,
            137.53879 ],
           [ 97.5854  ,  97.51921 ,  99.63876 , ..., 160.70842 , 169.99466 ,
            169.99466 ],
           [122.13025 , 121.47252 , 123.754425, ..., 126.1873  , 138.1677  ,
            138.1677  ]], shape=(2000, 49), dtype=float32)

  • ocean_vertical_diffusivity
    (trajectory, time)
    float32
    0.02 0.02 0.02 ... 0.02 0.02 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],
           ...,
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02],
           [0.02, 0.02, 0.02, ..., 0.02, 0.02, 0.02]],
          shape=(2000, 49), dtype=float32)

  • ocean_mixed_layer_thickness
    (trajectory, time)
    float32
    50.0 50.0 50.0 ... 50.0 50.0 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.],
           ...,
           [50., 50., 50., ..., 50., 50., 50.],
           [50., 50., 50., ..., 50., 50., 50.],
           [50., 50., 50., ..., 50., 50., 50.]],
          shape=(2000, 49), dtype=float32)

  • sea_water_temperature
    (trajectory, time)
    float32
    10.0 10.0 10.0 ... 10.0 10.0 10.0

    minval :

    10.0

    maxval :

    10.0

    array([[10., 10., 10., ..., 10., 10., 10.],
           [10., 10., 10., ..., 10., 10., 10.],
           [10., 10., 10., ..., 10., 10., 10.],
           ...,
           [10., 10., 10., ..., 10., 10., 10.],
           [10., 10., 10., ..., 10., 10., 10.],
           [10., 10., 10., ..., 10., 10., 10.]],
          shape=(2000, 49), dtype=float32)

  • sea_water_salinity
    (trajectory, time)
    float32
    34.0 34.0 34.0 ... 34.0 34.0 34.0

    minval :

    34.0

    maxval :

    34.0

    array([[34., 34., 34., ..., 34., 34., 34.],
           [34., 34., 34., ..., 34., 34., 34.],
           [34., 34., 34., ..., 34., 34., 34.],
           ...,
           [34., 34., 34., ..., 34., 34., 34.],
           [34., 34., 34., ..., 34., 34., 34.],
           [34., 34., 34., ..., 34., 34., 34.]],
          shape=(2000, 49), dtype=float32)

  • surface_downward_x_stress
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(2000, 49), dtype=float32)

  • surface_downward_y_stress
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(2000, 49), dtype=float32)

  • turbulent_kinetic_energy
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(2000, 49), dtype=float32)

  • turbulent_generic_length_scale
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(2000, 49), dtype=float32)

  • upward_sea_water_velocity
    (trajectory, time)
    float32
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    minval :

    0.0

    maxval :

    0.0

    array([[0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           ...,
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.],
           [0., 0., 0., ..., 0., 0., 0.]], shape=(2000, 49), dtype=float32)

• Indexes: (2)
  • trajectory
    PandasIndex

    PandasIndex(Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,
           ...
           1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999],
          dtype='int64', name='trajectory', length=2000))

  • time
    PandasIndex

    PandasIndex(DatetimeIndex(['2025-10-03 14:21:54.450134', '2025-10-03 15:21:54.450134',
                   '2025-10-03 16:21:54.450134', '2025-10-03 17:21:54.450134',
                   '2025-10-03 18:21:54.450134', '2025-10-03 19:21:54.450134',
                   '2025-10-03 20:21:54.450134', '2025-10-03 21:21:54.450134',
                   '2025-10-03 22:21:54.450134', '2025-10-03 23:21:54.450134',
                   '2025-10-04 00:21:54.450134', '2025-10-04 01:21:54.450134',
                   '2025-10-04 02:21:54.450134', '2025-10-04 03:21:54.450134',
                   '2025-10-04 04:21:54.450134', '2025-10-04 05:21:54.450134',
                   '2025-10-04 06:21:54.450134', '2025-10-04 07:21:54.450134',
                   '2025-10-04 08:21:54.450134', '2025-10-04 09:21:54.450134',
                   '2025-10-04 10:21:54.450134', '2025-10-04 11:21:54.450134',
                   '2025-10-04 12:21:54.450134', '2025-10-04 13:21:54.450134',
                   '2025-10-04 14:21:54.450134', '2025-10-04 15:21:54.450134',
                   '2025-10-04 16:21:54.450134', '2025-10-04 17:21:54.450134',
                   '2025-10-04 18:21:54.450134', '2025-10-04 19:21:54.450134',
                   '2025-10-04 20:21:54.450134', '2025-10-04 21:21:54.450134',
                   '2025-10-04 22:21:54.450134', '2025-10-04 23:21:54.450134',
                   '2025-10-05 00:21:54.450134', '2025-10-05 01:21:54.450134',
                   '2025-10-05 02:21:54.450134', '2025-10-05 03:21:54.450134',
                   '2025-10-05 04:21:54.450134', '2025-10-05 05:21:54.450134',
                   '2025-10-05 06:21:54.450134', '2025-10-05 07:21:54.450134',
                   '2025-10-05 08:21:54.450134', '2025-10-05 09:21:54.450134',
                   '2025-10-05 10:21:54.450134', '2025-10-05 11:21:54.450134',
                   '2025-10-05 12:21:54.450134', '2025-10-05 13:21:54.450134',
                   '2025-10-05 14:21:54.450134'],
                  dtype='datetime64[ns]', name='time', freq='h'))

• Attributes: (140)

  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 2025-10-03 14:21:58.684984

  date_created :

  2025-10-03T14:21:58.684998

  source :

  Output from simulation with OpenDrift

  model_url :

  https://github.com/OpenDrift/opendrift

  opendrift_class :

  PelagicEggDrift

  opendrift_module :

  opendrift.models.pelagicegg

  readers :

  odict_keys(['LazyReader: https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml', 'LazyReader: https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc', 'global_landmask'])

  time_coverage_start :

  2025-10-03 14:21:54.450134

  time_step_calculation :

  1:00:00

  time_step_output :

  1:00:00

  config_environment:constant:x_sea_water_velocity :

  None

  config_environment:fallback:x_sea_water_velocity :

  0

  config_environment:constant:y_sea_water_velocity :

  None

  config_environment:fallback:y_sea_water_velocity :

  0

  config_environment:constant:sea_surface_height :

  None

  config_environment:fallback:sea_surface_height :

  0

  config_environment:constant:sea_surface_wave_significant_height :

  None

  config_environment:fallback:sea_surface_wave_significant_height :

  0

  config_environment:constant:sea_ice_area_fraction :

  None

  config_environment:fallback:sea_ice_area_fraction :

  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:land_binary_mask :

  None

  config_environment:fallback:land_binary_mask :

  None

  config_environment:constant:sea_floor_depth_below_sea_level :

  None

  config_environment:fallback:sea_floor_depth_below_sea_level :

  100

  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_water_temperature :

  None

  config_environment:fallback:sea_water_temperature :

  10

  config_environment:constant:sea_water_salinity :

  None

  config_environment:fallback:sea_water_salinity :

  34

  config_environment:constant:surface_downward_x_stress :

  None

  config_environment:fallback:surface_downward_x_stress :

  0

  config_environment:constant:surface_downward_y_stress :

  None

  config_environment:fallback:surface_downward_y_stress :

  0

  config_environment:constant:turbulent_kinetic_energy :

  None

  config_environment:fallback:turbulent_kinetic_energy :

  0

  config_environment:constant:turbulent_generic_length_scale :

  None

  config_environment:fallback:turbulent_generic_length_scale :

  0

  config_environment:constant:upward_sea_water_velocity :

  None

  config_environment:fallback:upward_sea_water_velocity :

  0

  config_general:use_auto_landmask :

  True

  config_drift:current_uncertainty :

  0

  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 :

  0

  config_drift:relative_wind :

  False

  config_drift:deactivate_north_of :

  None

  config_drift:deactivate_south_of :

  None

  config_drift:deactivate_east_of :

  None

  config_drift:deactivate_west_of :

  None

  config_seed:origin_marker :

  0

  config_seed:z :

  0

  config_seed:wind_drift_factor :

  0.02

  config_seed:current_drift_factor :

  1

  config_seed:terminal_velocity :

  0.0

  config_seed:diameter :

  0.0014

  config_seed:neutral_buoyancy_salinity :

  31.25

  config_seed:density :

  1028.0

  config_seed:hatched :

  0.0

  config_drift:vertical_advection :

  True

  config_drift:vertical_advection_at_surface :

  True

  config_drift:water_column_stretching :

  False

  config_drift:vertical_advection_correction :

  False

  config_drift:vertical_mixing :

  True

  config_drift:vertical_mixing_at_surface :

  True

  config_vertical_mixing:timestep :

  60.0

  config_vertical_mixing:diffusivitymodel :

  windspeed_Sundby1983

  config_vertical_mixing:background_diffusivity :

  1.2e-05

  config_vertical_mixing:TSprofiles :

  False

  config_drift:wind_drift_depth :

  0.1

  config_drift:stokes_drift :

  True

  config_drift:stokes_drift_profile :

  Phillips

  config_drift:use_tabularised_stokes_drift :

  False

  config_drift:tabularised_stokes_drift_fetch :

  25000

  config_general:seafloor_action :

  lift_to_seafloor

  config_drift:truncate_ocean_model_below_m :

  None

  config_seed:seafloor :

  False

  opendrift_version :

  1.14.3

  seed_geojson :

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

  simulation_time :

  2025-10-03 14:21:58.692081

  reader_x_sea_water_velocity :

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

  reader_y_sea_water_velocity :

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

  reader_sea_surface_height :

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

  reader_sea_surface_wave_significant_height :

  0

  reader_sea_ice_area_fraction :

  0

  reader_x_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_y_wind :

  ['https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc']

  reader_land_binary_mask :

  ['global_landmask']

  reader_sea_floor_depth_below_sea_level :

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

  reader_ocean_vertical_diffusivity :

  0.02

  reader_ocean_mixed_layer_thickness :

  50

  reader_sea_water_temperature :

  10

  reader_sea_water_salinity :

  34

  reader_surface_downward_x_stress :

  0

  reader_surface_downward_y_stress :

  0

  reader_turbulent_kinetic_energy :

  0

  reader_turbulent_generic_length_scale :

  0

  reader_upward_sea_water_velocity :

  0

  time_coverage_end :

  2025-10-05 14:21:54.450134

  time_coverage_duration :

  P2DT0H0M0S

  time_coverage_resolution :

  P0DT1H0M0S

  performance :

  -------------------- Reader performance: -------------------- global_landmask 0:00:01.5 total 0:00:00.0 preparing 0:00:01.5 reading 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml 0:00:57.7 total 0:00:00.0 preparing 0:00:57.5 reading 0:00:00.1 interpolation 0:00:00.0 interpolation_time 0:00:00.1 rotating vectors 0:00:00.0 masking -------------------- https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc 0:00:36.7 total 0:00:00.0 preparing 0:00:36.6 reading 0:00:00.8 interpolation 0:00:00.0 interpolation_time 0:00:00.1 rotating vectors 0:00:00.0 masking -------------------- Performance: 1:51.5 total time 4.2 configuration 0.0 preparing main loop 0.0 moving elements to ocean 1:47.2 main loop 2.9 updating elements 2.9 vertical mixing 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  67.732445

  geospatial_lat_max :

  68.398926

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  12.314689

  geospatial_lon_max :

  14.16527

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:01:51.544452

  geospatial_vertical_min :

  -53.267063

  geospatial_vertical_max :

  0.0

  geospatial_vertical_positive :

  up

Print and plot results. At the end the wind vanishes, and eggs come to surface

print(o)

o.plot(fast=True)
o.animation(fast=True, color='z')

===========================
--------------------
Reader performance:
--------------------
global_landmask
 0:00:01.5  total
 0:00:00.0  preparing
 0:00:01.5  reading
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
 0:00:57.7  total
 0:00:00.0  preparing
 0:00:57.5  reading
 0:00:00.1  interpolation
 0:00:00.0  interpolation_time
 0:00:00.1  rotating vectors
 0:00:00.0  masking
--------------------
https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
 0:00:36.7  total
 0:00:00.0  preparing
 0:00:36.6  reading
 0:00:00.8  interpolation
 0:00:00.0  interpolation_time
 0:00:00.1  rotating vectors
 0:00:00.0  masking
--------------------
Performance:
 1:51.5 total time
    4.2 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
 1:47.2 main loop
      2.9 updating elements
        2.9 vertical mixing
    0.0 cleaning up
--------------------
===========================
Model:  PelagicEggDrift     (OpenDrift version 1.14.3)
        2000 active PelagicEgg particles  (0 deactivated, 0 scheduled)
-------------------
Environment variables:
  -----
  land_binary_mask
     1) global_landmask
  -----
  sea_floor_depth_below_sea_level
  sea_surface_height
  x_sea_water_velocity
  y_sea_water_velocity
     1) https://thredds.met.no/thredds/dodsC/cmems/topaz6/dataset-topaz6-arc-15min-3km-be.ncml
  -----
  x_wind
  y_wind
     1) https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc
  -----
Readers not added for the following variables:
  ocean_mixed_layer_thickness
  ocean_vertical_diffusivity
  sea_ice_area_fraction
  sea_surface_wave_significant_height
  sea_water_salinity
  sea_water_temperature
  surface_downward_x_stress
  surface_downward_y_stress
  turbulent_generic_length_scale
  turbulent_kinetic_energy
  upward_sea_water_velocity

Discarded readers:

Time:
        Start: 2025-10-03 14:21:54.450134 UTC
        Present: 2025-10-05 14:21:54.450134 UTC
        Calculation steps: 48 * 1:00:00 - total time: 2 days, 0:00:00
        Output steps: 49 * 1:00:00
===========================

14:23:46 WARNING opendrift:2445: Plotting fast. This will make your plots less accurate.
14:23:51 WARNING opendrift:2445: Plotting fast. This will make your plots less accurate.
14:23:52 INFO    opendrift:4613: Saving animation to /root/project/docs/source/gallery/animations/example_codegg_0.gif...
14:24:25 INFO    opendrift:3054: Time to make animation: 0:00:33.837882

o.animate_vertical_distribution()

14:24:27 INFO    opendrift:4613: Saving animation to /root/project/docs/source/gallery/animations/example_codegg_1.gif...
14:24:38 INFO    opendrift.models.oceandrift:642: Time to make animation: 0:00:11.093144