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'])

13:32:12 INFO    opendrift:568: OpenDriftSimulation initialised (version 1.14.3 / v1.14.3-2-g7a367c6)

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)

13:32:12 INFO    opendrift.models.basemodel.environment:206: Adding a global landmask from GSHHG
13:32:16 INFO    opendrift.models.basemodel.environment:229: Fallback values will be used for the following variables which have no readers:
13:32:16 INFO    opendrift.models.basemodel.environment:232:    x_sea_water_velocity: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    y_sea_water_velocity: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    sea_surface_height: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    sea_surface_wave_significant_height: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    sea_ice_area_fraction: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    x_wind: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    y_wind: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    sea_floor_depth_below_sea_level: 100.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    ocean_vertical_diffusivity: 0.020000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    ocean_mixed_layer_thickness: 50.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    sea_water_temperature: 10.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    sea_water_salinity: 34.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    surface_downward_x_stress: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    surface_downward_y_stress: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    turbulent_kinetic_energy: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    turbulent_generic_length_scale: 0.000000
13:32:16 INFO    opendrift.models.basemodel.environment:232:    upward_sea_water_velocity: 0.000000

Running model

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

13:32:16 INFO    opendrift:1789: Storing previous values of element property lon because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
13:32:16 INFO    opendrift:1789: Storing previous values of element property lat because of condition (('general:coastline_action', 'in', ['stranding', 'previous']), 'or', ('general:seafloor_action', 'in', ['previous']))
13:32:16 INFO    opendrift:944: Using existing reader for land_binary_mask to move elements to ocean
13:32:16 INFO    opendrift:974: All points are in ocean
13:32:16 INFO    opendrift:2085: 2025-09-01 13:32:12.297175 - step 1 of 48 - 2000 active elements (0 deactivated)
13:32:16 INFO    opendrift.readers:61: Opening file with xr.open_dataset
13:32:20 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'x': 'x', 'y': 'y', 'time': 'time'}
13:32:20 INFO    opendrift.readers:61: Opening file with xr.open_dataset
13:32:21 INFO    opendrift.readers.reader_netCDF_CF_generic:332: Detected dimensions: {'time': 'time', 'x': 'x', 'y': 'y'}
13:32:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:25 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:25 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:25 INFO    opendrift:2085: 2025-09-01 14:32:12.297175 - step 2 of 48 - 2000 active elements (0 deactivated)
13:32:27 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:27 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:27 INFO    opendrift:2085: 2025-09-01 15:32:12.297175 - step 3 of 48 - 2000 active elements (0 deactivated)
13:32:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:30 INFO    opendrift:2085: 2025-09-01 16:32:12.297175 - step 4 of 48 - 2000 active elements (0 deactivated)
13:32:34 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:34 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:34 INFO    opendrift:2085: 2025-09-01 17:32:12.297175 - step 5 of 48 - 2000 active elements (0 deactivated)
13:32:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:37 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:37 INFO    opendrift:2085: 2025-09-01 18:32:12.297175 - step 6 of 48 - 2000 active elements (0 deactivated)
13:32:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:40 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:40 INFO    opendrift:2085: 2025-09-01 19:32:12.297175 - step 7 of 48 - 2000 active elements (0 deactivated)
13:32:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:42 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:44 INFO    opendrift:2085: 2025-09-01 20:32:12.297175 - step 8 of 48 - 2000 active elements (0 deactivated)
13:32:46 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:46 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:46 INFO    opendrift:2085: 2025-09-01 21:32:12.297175 - step 9 of 48 - 2000 active elements (0 deactivated)
13:32:49 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:49 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:49 INFO    opendrift:2085: 2025-09-01 22:32:12.297175 - step 10 of 48 - 2000 active elements (0 deactivated)
13:32:52 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:52 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:52 INFO    opendrift:2085: 2025-09-01 23:32:12.297175 - step 11 of 48 - 2000 active elements (0 deactivated)
13:32:54 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:54 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:54 INFO    opendrift:2085: 2025-09-02 00:32:12.297175 - step 12 of 48 - 2000 active elements (0 deactivated)
13:32:57 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:57 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:32:57 INFO    opendrift:2085: 2025-09-02 01:32:12.297175 - step 13 of 48 - 2000 active elements (0 deactivated)
13:33:00 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:00 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:00 INFO    opendrift:2085: 2025-09-02 02:32:12.297175 - step 14 of 48 - 2000 active elements (0 deactivated)
13:33:03 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:03 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:03 INFO    opendrift:2085: 2025-09-02 03:32:12.297175 - step 15 of 48 - 2000 active elements (0 deactivated)
13:33:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:05 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:05 INFO    opendrift:2085: 2025-09-02 04:32:12.297175 - step 16 of 48 - 2000 active elements (0 deactivated)
13:33:08 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:08 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:08 INFO    opendrift:2085: 2025-09-02 05:32:12.297175 - step 17 of 48 - 2000 active elements (0 deactivated)
13:33:11 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:11 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:11 INFO    opendrift:2085: 2025-09-02 06:32:12.297175 - step 18 of 48 - 2000 active elements (0 deactivated)
13:33:14 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:14 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:14 INFO    opendrift:2085: 2025-09-02 07:32:12.297175 - step 19 of 48 - 2000 active elements (0 deactivated)
13:33:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:16 INFO    opendrift:2085: 2025-09-02 08:32:12.297175 - step 20 of 48 - 2000 active elements (0 deactivated)
13:33:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:19 INFO    opendrift:2085: 2025-09-02 09:32:12.297175 - step 21 of 48 - 2000 active elements (0 deactivated)
13:33:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:22 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:22 INFO    opendrift:2085: 2025-09-02 10:32:12.297175 - step 22 of 48 - 2000 active elements (0 deactivated)
13:33:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:24 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:25 INFO    opendrift:2085: 2025-09-02 11:32:12.297175 - step 23 of 48 - 2000 active elements (0 deactivated)
13:33:27 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:27 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:27 INFO    opendrift:2085: 2025-09-02 12:32:12.297175 - step 24 of 48 - 2000 active elements (0 deactivated)
13:33:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:30 INFO    opendrift:2085: 2025-09-02 13:32:12.297175 - step 25 of 48 - 2000 active elements (0 deactivated)
13:33:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:33 INFO    opendrift:2085: 2025-09-02 14:32:12.297175 - step 26 of 48 - 2000 active elements (0 deactivated)
13:33:36 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:36 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:36 INFO    opendrift:2085: 2025-09-02 15:32:12.297175 - step 27 of 48 - 2000 active elements (0 deactivated)
13:33:38 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:38 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:38 INFO    opendrift:2085: 2025-09-02 16:32:12.297175 - step 28 of 48 - 2000 active elements (0 deactivated)
13:33:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:41 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:41 INFO    opendrift:2085: 2025-09-02 17:32:12.297175 - step 29 of 48 - 2000 active elements (0 deactivated)
13:33:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:44 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:44 INFO    opendrift:2085: 2025-09-02 18:32:12.297175 - step 30 of 48 - 2000 active elements (0 deactivated)
13:33:47 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:47 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:47 INFO    opendrift:2085: 2025-09-02 19:32:12.297175 - step 31 of 48 - 2000 active elements (0 deactivated)
13:33:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:50 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:50 INFO    opendrift:2085: 2025-09-02 20:32:12.297175 - step 32 of 48 - 2000 active elements (0 deactivated)
13:33:52 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:52 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:52 INFO    opendrift:2085: 2025-09-02 21:32:12.297175 - step 33 of 48 - 2000 active elements (0 deactivated)
13:33:55 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:55 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:55 INFO    opendrift:2085: 2025-09-02 22:32:12.297175 - step 34 of 48 - 2000 active elements (0 deactivated)
13:33:58 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:58 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:33:58 INFO    opendrift:2085: 2025-09-02 23:32:12.297175 - step 35 of 48 - 2000 active elements (0 deactivated)
13:34:01 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:01 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:01 INFO    opendrift:2085: 2025-09-03 00:32:12.297175 - step 36 of 48 - 2000 active elements (0 deactivated)
13:34:04 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:04 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:04 INFO    opendrift:2085: 2025-09-03 01:32:12.297175 - step 37 of 48 - 2000 active elements (0 deactivated)
13:34:07 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:07 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:08 INFO    opendrift:2085: 2025-09-03 02:32:12.297175 - step 38 of 48 - 2000 active elements (0 deactivated)
13:34:10 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:10 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:10 INFO    opendrift:2085: 2025-09-03 03:32:12.297175 - step 39 of 48 - 2000 active elements (0 deactivated)
13:34:13 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:13 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:13 INFO    opendrift:2085: 2025-09-03 04:32:12.297175 - step 40 of 48 - 2000 active elements (0 deactivated)
13:34:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:16 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:16 INFO    opendrift:2085: 2025-09-03 05:32:12.297175 - step 41 of 48 - 2000 active elements (0 deactivated)
13:34:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:19 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:19 INFO    opendrift:2085: 2025-09-03 06:32:12.297175 - step 42 of 48 - 2000 active elements (0 deactivated)
13:34:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:21 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:22 INFO    opendrift:2085: 2025-09-03 07:32:12.297175 - step 43 of 48 - 2000 active elements (0 deactivated)
13:34:25 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:25 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:25 INFO    opendrift:2085: 2025-09-03 08:32:12.297175 - step 44 of 48 - 2000 active elements (0 deactivated)
13:34:27 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:27 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:28 INFO    opendrift:2085: 2025-09-03 09:32:12.297175 - step 45 of 48 - 2000 active elements (0 deactivated)
13:34:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:30 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:30 INFO    opendrift:2085: 2025-09-03 10:32:12.297175 - step 46 of 48 - 2000 active elements (0 deactivated)
13:34:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:33 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:33 INFO    opendrift:2085: 2025-09-03 11:32:12.297175 - step 47 of 48 - 2000 active elements (0 deactivated)
13:34:36 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:36 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:36 INFO    opendrift:2085: 2025-09-03 12:32:12.297175 - step 48 of 48 - 2000 active elements (0 deactivated)
13:34:39 WARNING opendrift.readers.interpolation.structured:63: Ensemble data currently not extrapolated towards seafloor
13:34:39 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 2025-09-0...
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:                                                          0:02:27...
    geospatial_vertical_min:                                          -51.71013
    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]
    2025-09-01T13:32:12.297175 ... 2...

    standard_name :

    time

    long_name :

    time

    dtype :

    <class 'numpy.float64'>

    array(['2025-09-01T13:32:12.297175000', '2025-09-01T14:32:12.297175000',
           '2025-09-01T15:32:12.297175000', '2025-09-01T16:32:12.297175000',
           '2025-09-01T17:32:12.297175000', '2025-09-01T18:32:12.297175000',
           '2025-09-01T19:32:12.297175000', '2025-09-01T20:32:12.297175000',
           '2025-09-01T21:32:12.297175000', '2025-09-01T22:32:12.297175000',
           '2025-09-01T23:32:12.297175000', '2025-09-02T00:32:12.297175000',
           '2025-09-02T01:32:12.297175000', '2025-09-02T02:32:12.297175000',
           '2025-09-02T03:32:12.297175000', '2025-09-02T04:32:12.297175000',
           '2025-09-02T05:32:12.297175000', '2025-09-02T06:32:12.297175000',
           '2025-09-02T07:32:12.297175000', '2025-09-02T08:32:12.297175000',
           '2025-09-02T09:32:12.297175000', '2025-09-02T10:32:12.297175000',
           '2025-09-02T11:32:12.297175000', '2025-09-02T12:32:12.297175000',
           '2025-09-02T13:32:12.297175000', '2025-09-02T14:32:12.297175000',
           '2025-09-02T15:32:12.297175000', '2025-09-02T16:32:12.297175000',
           '2025-09-02T17:32:12.297175000', '2025-09-02T18:32:12.297175000',
           '2025-09-02T19:32:12.297175000', '2025-09-02T20:32:12.297175000',
           '2025-09-02T21:32:12.297175000', '2025-09-02T22:32:12.297175000',
           '2025-09-02T23:32:12.297175000', '2025-09-03T00:32:12.297175000',
           '2025-09-03T01:32:12.297175000', '2025-09-03T02:32:12.297175000',
           '2025-09-03T03:32:12.297175000', '2025-09-03T04:32:12.297175000',
           '2025-09-03T05:32:12.297175000', '2025-09-03T06:32:12.297175000',
           '2025-09-03T07:32:12.297175000', '2025-09-03T08:32:12.297175000',
           '2025-09-03T09:32:12.297175000', '2025-09-03T10:32:12.297175000',
           '2025-09-03T11:32:12.297175000', '2025-09-03T12:32:12.297175000',
           '2025-09-03T13:32:12.297175000'], 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 ... 12.72 12.72

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_east

    standard_name :

    longitude

    long_name :

    longitude

    axis :

    X

    minval :

    12.35679

    maxval :

    14.232291

    array([[14.084752, 14.086376, 14.087496, ..., 14.204078, 14.205501,
            14.208089],
           [14.019218, 14.020016, 14.020429, ..., 14.142245, 14.144239,
            14.147206],
           [14.047049, 14.050022, 14.052487, ..., 14.209351, 14.209351,
            14.209351],
           ...,
           [13.055853, 13.052094, 13.050281, ..., 12.719869, 12.719869,
            12.719869],
           [13.005157, 13.003683, 13.002045, ..., 12.671209, 12.657009,
            12.649702],
           [13.002091, 12.999558, 12.999077, ..., 12.721478, 12.721478,
            12.721478]], shape=(2000, 49), dtype=float32)

  • lat
    (trajectory, time)
    float32
    68.11 68.11 68.11 ... 67.67 67.67

    dtype :

    <class 'numpy.float32'>

    units :

    degrees_north

    standard_name :

    latitude

    long_name :

    latitude

    axis :

    Y

    minval :

    67.523506

    maxval :

    68.42587

    array([[68.10684 , 68.108475, 68.10992 , ..., 68.158035, 68.15774 ,
            68.157166],
           [68.09939 , 68.101364, 68.10313 , ..., 68.16737 , 68.16796 ,
            68.16802 ],
           [68.11965 , 68.12127 , 68.1228  , ..., 68.17341 , 68.17341 ,
            68.17341 ],
           ...,
           [67.79944 , 67.79796 , 67.79588 , ..., 67.66835 , 67.66835 ,
            67.66835 ],
           [67.82828 , 67.82712 , 67.82565 , ..., 67.94918 , 67.96221 ,
            67.97611 ],
           [67.78542 , 67.78394 , 67.781944, ..., 67.66577 , 67.66577 ,
            67.66577 ]], shape=(2000, 49), dtype=float32)

  • z
    (trajectory, time)
    float32
    -40.0 -47.23 ... -10.98 -12.83

    dtype :

    <class 'numpy.float32'>

    units :

    m

    standard_name :

    z

    long_name :

    vertical position

    axis :

    Z

    positive :

    up

    minval :

    -51.71013

    maxval :

    0.0

    array([[-40.       , -47.226627 , -45.273865 , ...,  -2.6880844,
             -1.2481472,  -0.6031155],
           [-40.       , -42.616314 , -41.261055 , ..., -10.227646 ,
             -9.838932 , -34.323734 ],
           [-40.       , -29.219675 , -15.244768 , ...,  -8.355909 ,
             -1.49717  ,  -8.890071 ],
           ...,
           [-40.       , -37.10628  , -33.882114 , ...,  -9.388478 ,
             -9.507873 , -13.129003 ],
           [-40.       , -30.523722 , -17.755024 , ...,  -4.8227587,
             -1.341081 ,  -3.5410326],
           [-40.       , -40.03487  , -26.941374 , ..., -12.053528 ,
            -10.975839 , -12.831059 ]], 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
    0.01878 0.01294 ... -0.2125 -0.2125

    minval :

    -0.5214259

    maxval :

    0.38571507

    array([[ 0.01878332,  0.01294249,  0.00192422, ...,  0.01642343,
             0.02986092,  0.02986092],
           [ 0.00921826,  0.00477498, -0.00553466, ...,  0.02299888,
             0.03421073,  0.03421073],
           [ 0.03436284,  0.0284823 ,  0.01892752, ...,  0.02286358,
             0.0425633 ,  0.0425633 ],
           ...,
           [-0.0440396 , -0.02125697, -0.02723661, ..., -0.29167116,
            -0.20209695, -0.20209695],
           [-0.01725108, -0.01918586, -0.04797348, ..., -0.16523603,
            -0.08496958, -0.08496958],
           [-0.0296949 , -0.005655  , -0.01046943, ..., -0.29866347,
            -0.2124633 , -0.2124633 ]], shape=(2000, 49), dtype=float32)

  • y_sea_water_velocity
    (trajectory, time)
    float32
    0.05047 0.04488 ... 0.07355 0.07355

    minval :

    -0.48595867

    maxval :

    0.57421845

    array([[ 0.05047422,  0.04487865,  0.04033368, ..., -0.0091993 ,
            -0.01776158, -0.01776158],
           [ 0.06127492,  0.05451508,  0.04851298, ...,  0.01803306,
             0.00186048,  0.00186048],
           [ 0.05000866,  0.04768853,  0.0471946 , ...,  0.00048222,
            -0.02025085, -0.02025085],
           ...,
           [-0.04580294, -0.06423743, -0.09679285, ...,  0.05080338,
             0.07972466,  0.07972466],
           [-0.03581861, -0.04551558, -0.05940484, ...,  0.40386677,
             0.43073672,  0.43073672],
           [-0.04596375, -0.06180101, -0.08981302, ...,  0.04279415,
             0.07354978,  0.07354978]], shape=(2000, 49), dtype=float32)

  • sea_surface_height
    (trajectory, time)
    float32
    -0.4371 -0.2175 ... -0.6583 -0.6583

    minval :

    -0.73159707

    maxval :

    0.16724437

    array([[-0.4371071 , -0.21751085, -0.02656646, ..., -0.49652338,
            -0.6718853 , -0.6718853 ],
           [-0.4380107 , -0.2188287 , -0.02810313, ..., -0.49531865,
            -0.6703977 , -0.6703977 ],
           [-0.43812037, -0.21856247, -0.02779597, ..., -0.49657768,
            -0.6723085 , -0.6723085 ],
           ...,
           [-0.46307167, -0.2569444 , -0.07476323, ..., -0.5053733 ,
            -0.6577212 , -0.6577212 ],
           [-0.45617637, -0.25080055, -0.06781428, ..., -0.46589595,
            -0.6075369 , -0.6075369 ],
           [-0.45844615, -0.25356776, -0.07283159, ..., -0.5059438 ,
            -0.65834063, -0.65834063]], shape=(2000, 49), dtype=float32)

  • sea_surface_wave_significant_height
    (trajectory, time)
    float32
    0.2355 0.256 ... 0.5659 0.5659

    minval :

    4.3148652e-06

    maxval :

    5.569647

    array([[0.23548508, 0.25602886, 0.20453355, ..., 0.46442956, 0.54088366,
            0.54088366],
           [0.15717864, 0.26059973, 0.24807581, ..., 1.6036419 , 1.573372  ,
            1.573372  ],
           [0.26757014, 0.27815682, 0.30986476, ..., 0.61763036, 0.46784046,
            0.46784046],
           ...,
           [0.19410081, 0.16718858, 0.16843462, ..., 0.40840673, 1.247859  ,
            1.247859  ],
           [0.19371171, 0.22634052, 0.17862988, ..., 0.07001822, 0.04976205,
            0.04976205],
           [0.28543034, 0.34847215, 0.39691812, ..., 0.41978484, 0.56588906,
            0.56588906]], 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
    -3.084 -3.225 ... -4.09 -4.09

    minval :

    -9.902166

    maxval :

    7.27421

    array([[-3.083765  , -3.224938  , -2.8833942 , ..., -4.331294  ,
            -4.60201   , -4.60201   ],
           [-2.5225458 , -3.2510326 , -3.1692069 , ..., -7.9896502 ,
            -7.947221  , -7.947221  ],
           [-3.027944  , -3.2045143 , -3.5157573 , ..., -4.898273  ,
            -3.6436663 , -3.6436663 ],
           ...,
           [-1.927275  , -2.091917  , -2.4456117 , ..., -0.0183753 ,
             0.3149288 ,  0.3149288 ],
           [-1.5686133 , -2.2807102 , -2.4073117 , ..., -1.1309048 ,
            -0.96976835, -0.96976835],
           [-3.323687  , -3.7430341 , -3.9954035 , ..., -3.9397688 ,
            -4.089854  , -4.089854  ]], shape=(2000, 49), dtype=float32)

  • y_wind
    (trajectory, time)
    float32
    0.2509 0.08633 ... 2.505 2.505

    minval :

    -6.182409

    maxval :

    14.7443

    array([[ 0.25091144,  0.0863313 ,  0.02025044, ..., -0.34516767,
            -0.8992503 , -0.8992503 ],
           [ 0.16167317,  0.15579215,  0.20127106, ..., -1.1636934 ,
            -0.8943678 , -0.8943678 ],
           [ 1.3070544 ,  1.0189584 ,  0.48536566, ...,  1.055389  ,
             2.396164  ,  2.396164  ],
           ...,
           [ 2.0434992 ,  1.5556885 ,  0.93054795, ...,  4.0745015 ,
             7.115251  ,  7.115251  ],
           [ 2.3267815 ,  1.999799  ,  1.2108791 , ...,  1.251928  ,
             1.0403831 ,  1.0403831 ],
           [ 0.7456289 ,  0.3939922 ,  0.41428712, ...,  1.2420334 ,
             2.5053372 ,  2.5053372 ]], 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 90.85 90.18 ... 67.99 67.99

    minval :

    21.464489

    maxval :

    217.28772

    array([[ 91.5983  ,  90.85229 ,  90.18452 , ...,  43.96992 ,  44.200054,
             44.200054],
           [ 94.49078 ,  94.22211 ,  93.94437 , ...,  40.269905,  39.662613,
             39.662613],
           [ 86.55411 ,  85.72591 ,  84.957146, ...,  36.00294 ,  36.086254,
             36.086254],
           ...,
           [131.81073 , 131.42531 , 132.01492 , ...,  64.09399 ,  62.379444,
             62.379444],
           [ 97.5854  ,  97.85066 ,  98.258995, ...,  78.632576,  85.81196 ,
             85.81196 ],
           [122.13024 , 122.04691 , 122.91388 , ...,  68.698   ,  67.9942  ,
             67.9942  ]], 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(['2025-09-01 13:32:12.297175', '2025-09-01 14:32:12.297175',
                   '2025-09-01 15:32:12.297175', '2025-09-01 16:32:12.297175',
                   '2025-09-01 17:32:12.297175', '2025-09-01 18:32:12.297175',
                   '2025-09-01 19:32:12.297175', '2025-09-01 20:32:12.297175',
                   '2025-09-01 21:32:12.297175', '2025-09-01 22:32:12.297175',
                   '2025-09-01 23:32:12.297175', '2025-09-02 00:32:12.297175',
                   '2025-09-02 01:32:12.297175', '2025-09-02 02:32:12.297175',
                   '2025-09-02 03:32:12.297175', '2025-09-02 04:32:12.297175',
                   '2025-09-02 05:32:12.297175', '2025-09-02 06:32:12.297175',
                   '2025-09-02 07:32:12.297175', '2025-09-02 08:32:12.297175',
                   '2025-09-02 09:32:12.297175', '2025-09-02 10:32:12.297175',
                   '2025-09-02 11:32:12.297175', '2025-09-02 12:32:12.297175',
                   '2025-09-02 13:32:12.297175', '2025-09-02 14:32:12.297175',
                   '2025-09-02 15:32:12.297175', '2025-09-02 16:32:12.297175',
                   '2025-09-02 17:32:12.297175', '2025-09-02 18:32:12.297175',
                   '2025-09-02 19:32:12.297175', '2025-09-02 20:32:12.297175',
                   '2025-09-02 21:32:12.297175', '2025-09-02 22:32:12.297175',
                   '2025-09-02 23:32:12.297175', '2025-09-03 00:32:12.297175',
                   '2025-09-03 01:32:12.297175', '2025-09-03 02:32:12.297175',
                   '2025-09-03 03:32:12.297175', '2025-09-03 04:32:12.297175',
                   '2025-09-03 05:32:12.297175', '2025-09-03 06:32:12.297175',
                   '2025-09-03 07:32:12.297175', '2025-09-03 08:32:12.297175',
                   '2025-09-03 09:32:12.297175', '2025-09-03 10:32:12.297175',
                   '2025-09-03 11:32:12.297175', '2025-09-03 12:32:12.297175',
                   '2025-09-03 13:32:12.297175'],
                  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 2025-09-01 13:32:16.807666

  date_created :

  2025-09-01T13:32:16.807685

  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 :

  2025-09-01 13:32:12.297175

  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 :

  2025-09-01 13:32:16.891667

  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 :

  2025-09-03 13:32:12.297175

  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 0:01:06.8 total 0:00:00.0 preparing 0:01:06.7 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 0:01:01.7 total 0:00:00.0 preparing 0:01:01.6 reading 0:00:00.9 interpolation 0:00:00.0 interpolation_time 0:00:00.1 rotating vectors 0:00:00.0 masking -------------------- Performance: 2:27.3 total time 4.5 configuration 0.0 preparing main loop 0.0 moving elements to ocean 2:22.6 main loop 3.5 updating elements 3.4 vertical mixing 0.0 cleaning up --------------------

  geospatial_bounds_crs :

  EPSG:4326

  geospatial_bounds_vertical_crs :

  EPSG:5831

  geospatial_lat_min :

  67.523506

  geospatial_lat_max :

  68.42587

  geospatial_lat_units :

  degrees_north

  geospatial_lat_resolution :

  point

  geospatial_lon_min :

  12.35679

  geospatial_lon_max :

  14.232291

  geospatial_lon_units :

  degrees_east

  geospatial_lon_resolution :

  point

  runtime :

  0:02:27.317508

  geospatial_vertical_min :

  -51.71013

  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
 0:01:06.8  total
 0:00:00.0  preparing
 0:01:06.7  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
 0:01:01.7  total
 0:00:00.0  preparing
 0:01:01.6  reading
 0:00:00.9  interpolation
 0:00:00.0  interpolation_time
 0:00:00.1  rotating vectors
 0:00:00.0  masking
--------------------
Performance:
 2:27.3 total time
    4.5 configuration
    0.0 preparing main loop
      0.0 moving elements to ocean
 2:22.6 main loop
      3.5 updating elements
        3.4 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: 2025-09-01 13:32:12.297175 UTC
        Present: 2025-09-03 13:32:12.297175 UTC
        Calculation steps: 48 * 1:00:00 - total time: 2 days, 0:00:00
        Output steps: 49 * 1:00:00
===========================

13:34:39 WARNING opendrift:2441: Plotting fast. This will make your plots less accurate.
13:34:45 WARNING opendrift:2441: Plotting fast. This will make your plots less accurate.
13:34:46 INFO    opendrift:4609: Saving animation to /root/project/docs/source/gallery/animations/example_codegg_0.gif...
13:35:19 INFO    opendrift:3050: Time to make animation: 0:00:34.501146

o.animate_vertical_distribution()

13:35:21 INFO    opendrift:4609: Saving animation to /root/project/docs/source/gallery/animations/example_codegg_1.gif...
13:35:33 INFO    opendrift.models.oceandrift:642: Time to make animation: 0:00:11.841241