Note
Go to the end to download the full example code.
Fjord
from datetime import timedelta
from opendrift.readers import reader_global_landmask
from opendrift.readers import reader_netCDF_CF_generic
from opendrift.models.leeway import Leeway
o = Leeway(loglevel=20) # Set loglevel to 0 for debug information
12:50:56 INFO opendrift.models.basemodel:515: OpenDriftSimulation initialised (version 1.11.13 / v1.11.13-99-gd2132d3)
Add readers for wind and current
reader_arome = reader_netCDF_CF_generic.Reader(o.test_data_folder() +
'16Nov2015_NorKyst_z_surface/arome_subset_16Nov2015.nc')
reader_norkyst = reader_netCDF_CF_generic.Reader(o.test_data_folder() +
'16Nov2015_NorKyst_z_surface/norkyst800_subset_16Nov2015.nc')
o.add_reader([reader_norkyst, reader_arome])
12:50:56 INFO opendrift.readers.reader_netCDF_CF_generic:102: Opening dataset: /root/project/tests/test_data/16Nov2015_NorKyst_z_surface/arome_subset_16Nov2015.nc
/opt/conda/envs/opendrift/lib/python3.11/site-packages/pyproj/crs/crs.py:1286: UserWarning: You will likely lose important projection information when converting to a PROJ string from another format. See: https://proj.org/faq.html#what-is-the-best-format-for-describing-coordinate-reference-systems
proj = self._crs.to_proj4(version=version)
12:50:56 INFO opendrift.readers.reader_netCDF_CF_generic:325: Detected dimensions: {'time': 'time', 'x': 'x', 'y': 'y'}
12:50:56 INFO opendrift.readers.reader_netCDF_CF_generic:102: Opening dataset: /root/project/tests/test_data/16Nov2015_NorKyst_z_surface/norkyst800_subset_16Nov2015.nc
/opt/conda/envs/opendrift/lib/python3.11/site-packages/pyproj/crs/crs.py:1286: UserWarning: You will likely lose important projection information when converting to a PROJ string from another format. See: https://proj.org/faq.html#what-is-the-best-format-for-describing-coordinate-reference-systems
proj = self._crs.to_proj4(version=version)
12:50:56 INFO opendrift.readers.reader_netCDF_CF_generic:325: Detected dimensions: {'x': 'X', 'y': 'Y', 'z': 'depth', 'time': 'time'}
Seed elements
time = reader_arome.start_time
object_type = 1 # 1: Person-in-water (PIW), unknown state (mean values)
o.seed_elements(lon=6.55, lat=61.117594, radius=50, number=5000, time=time, object_type=object_type)
12:50:56 INFO opendrift.models.leeway:319: Seeding elements of object type 1: PIW-1 (Person-in-water (PIW), unknown state (mean values))
12:50:56 INFO opendrift.models.basemodel.environment:218: Adding a dynamical landmask with max. priority based on assumed maximum speed of 5.0 m/s. Adding a customised landmask may be faster...
12:51:00 INFO opendrift.models.basemodel.environment:245: Fallback values will be used for the following variables which have no readers:
12:51:00 INFO opendrift.models.basemodel.environment:248: sea_surface_wave_stokes_drift_x_velocity: 0.000000
12:51:00 INFO opendrift.models.basemodel.environment:248: sea_surface_wave_stokes_drift_y_velocity: 0.000000
Running model for 12 hours, using small time step due to high resolution coastline
o.run(duration=timedelta(hours=12), time_step=300, time_step_output=3600)
12:51:01 INFO opendrift.models.basemodel:936: Using existing reader for land_binary_mask
12:51:01 INFO opendrift.models.basemodel:947: All points are in ocean
12:51:01 INFO opendrift.models.basemodel:2038: 2015-11-16 00:00:00 - step 1 of 144 - 5000 active elements (0 deactivated)
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12:51:02 INFO opendrift.models.basemodel:2038: 2015-11-16 00:10:00 - step 3 of 144 - 5000 active elements (0 deactivated)
12:51:02 INFO opendrift.models.basemodel:2038: 2015-11-16 00:15:00 - step 4 of 144 - 5000 active elements (0 deactivated)
/root/project/opendrift/readers/interpolation/interpolators.py:17: RuntimeWarning: overflow encountered in cast
data[mask] = np.finfo(np.float64).min
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Print and plot results
print(o)
o.animation()
===========================
--------------------
Reader performance:
--------------------
/root/project/tests/test_data/16Nov2015_NorKyst_z_surface/norkyst800_subset_16Nov2015.nc
0:00:01.8 total
0:00:00.0 preparing
0:00:00.2 reading
0:00:00.1 interpolation
0:00:00.0 interpolation_time
0:00:01.6 rotating vectors
0:00:00.0 masking
--------------------
/root/project/tests/test_data/16Nov2015_NorKyst_z_surface/arome_subset_16Nov2015.nc
0:00:01.8 total
0:00:00.0 preparing
0:00:00.2 reading
0:00:00.1 interpolation
0:00:00.0 interpolation_time
0:00:01.5 rotating vectors
0:00:00.0 masking
--------------------
global_landmask
0:00:01.6 total
0:00:00.0 preparing
0:00:01.6 reading
0:00:00.0 masking
--------------------
Performance:
15.1 total time
5.7 configuration
0.0 preparing main loop
0.0 moving elements to ocean
9.4 main loop
0.5 updating elements
0.0 cleaning up
--------------------
===========================
Model: Leeway (OpenDrift version 1.11.13)
1101 active LeewayObj particles (3899 deactivated, 0 scheduled)
-------------------
Environment variables:
-----
x_sea_water_velocity
y_sea_water_velocity
1) /root/project/tests/test_data/16Nov2015_NorKyst_z_surface/norkyst800_subset_16Nov2015.nc
-----
x_wind
y_wind
1) /root/project/tests/test_data/16Nov2015_NorKyst_z_surface/arome_subset_16Nov2015.nc
-----
land_binary_mask
1) global_landmask
-----
Readers not added for the following variables:
sea_surface_wave_stokes_drift_x_velocity
sea_surface_wave_stokes_drift_y_velocity
Discarded readers:
Time:
Start: 2015-11-16 00:00:00 UTC
Present: 2015-11-16 12:00:00 UTC
Calculation steps: 144 * 0:05:00 - total time: 12:00:00
Output steps: 13 * 1:00:00
===========================
/opt/conda/envs/opendrift/lib/python3.11/site-packages/cartopy/mpl/geoaxes.py:1692: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored
result = super().scatter(*args, **kwargs)
12:51:34 INFO opendrift.models.basemodel:4613: Saving animation to /root/project/docs/source/gallery/animations/example_fjord_0.gif...
12:52:20 INFO opendrift.models.basemodel:3037: Time to make animation: 0:01:09.205854
o.plot()
(<GeoAxes: title={'center': 'OpenDrift - Leeway (PIW-1)\n2015-11-16 00:00 to 2015-11-16 12:00 UTC (13 steps)'}>, <Figure size 1100x719.682 with 1 Axes>)
Total running time of the script: (1 minutes 47.738 seconds)