def test_lift_above_seafloor(self):
# See an element at some depth, and progapate towards coast
# (shallower water) and check that it is not penetrating seafloor
o = OceanDrift(loglevel=50)
o.max_speed = 100
reader_norkyst = reader_netCDF_CF_generic.Reader(
o.test_data_folder() +
'14Jan2016_NorKyst_z_3d/NorKyst-800m_ZDEPTHS_his_00_3Dsubset.nc')
reader_norkyst.buffer = 200
o.add_reader([reader_norkyst],
variables='sea_floor_depth_below_sea_level')
o.set_config('environment:fallback:x_sea_water_velocity',
10) # Pure eastward motion
o.set_config('environment:fallback:y_sea_water_velocity', 0)
o.set_config('environment:fallback:land_binary_mask', 0)
o.seed_elements(3.9, 62.0, z=-200, time=reader_norkyst.start_time)
o.set_config('drift:vertical_mixing', False)
o.run(steps=12, time_step=300)
seafloor_depth, status = o.get_property(
'sea_floor_depth_below_sea_level')
z, status = o.get_property('z')
# Uncomment to plot
#import matplotlib.pyplot as plt
#plt.plot(-seafloor_depth, label='Seafloor depth')
#plt.plot(z, label='Element depth')
#plt.legend(loc='best')
#plt.show()
# Check that element has not penetrated seafloor
self.assertFalse(
o.elements.z < -o.environment.sea_floor_depth_below_sea_level)
self.assertIsNone(
np.testing.assert_array_almost_equal(o.elements.z, -134.5, 1))
"""
Use a shapefile as landmask
===========================
"""
import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from opendrift.readers import reader_netCDF_CF_generic
from opendrift.readers import reader_ROMS_native
from opendrift.readers import reader_shape
from opendrift.models.oceandrift import OceanDrift
o = OceanDrift(loglevel=20) # Set loglevel to 0 for debug information
o.max_speed = 3
# This example works better using hourly input from Thredds than the daily data from test folder
reader_nordic = reader_netCDF_CF_generic.Reader(
'https://thredds.met.no/thredds/dodsC/sea/nordic4km/zdepths1h/aggregate_be'
)
#%%
# Use shapes from Cartopy for tests. These shapefiles are less acurate than those
# provided by the GSHHS dataset (available though the reader_global_landmask reader).
import cartopy.io.shapereader as shpreader
shpfilename = shpreader.natural_earth(resolution='110m',
category='cultural',
name='admin_0_countries')
reader_natural = reader_shape.Reader.from_shpfiles(shpfilename)
#reader_nordic = reader_ROMS_native.Reader(o.test_data_folder() +
import numpy as np
from datetime import datetime, timedelta
from opendrift.readers import reader_global_landmask
from opendrift.readers import reader_ROMS_native_MOANA
from opendrift.models.oceandrift import OceanDrift
#from opendrift.models.pelagicplankton_moana import PelagicPlanktonDrift
#from opendrift.models.sedimentdrift import SedimentDrift
###############################
# MODEL SELECTION
###############################
o = OceanDrift(loglevel=100)
#o = SedimentDrift(loglevel=100) # 0 for debug output
#o = PelagicPlanktonDrift(loglevel=50) # Set loglevel to 0 for debug information
o.max_speed = 3.0 #
###############################
# READERS
###############################
thredds_path_1 = 'http://thredds.moanaproject.org:8080/thredds/dodsC/moana/ocean/NZB/v1.9/raw_3D/nz5km_his_201709.nc?ntimes,dt,hc,grid,s_rho[5:1:12],Cs_r[5:1:12],h[0:1:466][0:1:396],lon_rho[0:1:466][0:1:396],lat_rho[0:1:466][0:1:396],lon_u[0:1:466][0:1:395],lat_u[0:1:466][0:1:395],lon_v[0:1:465][0:1:396],lat_v[0:1:465][0:1:396],lon_psi[0:1:465][0:1:395],angle[0:1:466][0:1:396],mask_rho[0:1:466][0:1:396],mask_u[0:1:466][0:1:395],mask_v[0:1:465][0:1:396],ocean_time[0:1:240],z_rho[0:1:240][5:1:12][0:1:466][0:1:396],u_eastward[0:1:240][5:1:12][0:1:466][0:1:396],v_northward[0:1:240][5:1:12][0:1:466][0:1:396]' # Limit to selected depths (raw data: [0:1:39])#'http://thredds.moanaproject.org:8080/thredds/dodsC/moana/ocean/NZB/v1.9/raw_3D/nz5km_his_201710.nc'
reader_moana_v19_1 = reader_ROMS_native_MOANA.Reader(
[thredds_path_1]) #load data for that year
reader_moana_v19_1.multiprocessing_fail = True # bypass the use of multi core for coordinates conversion and seems to make the model run much faster.
thredds_path_2 = 'http://thredds.moanaproject.org:8080/thredds/dodsC/moana/ocean/NZB/v1.9/raw_3D/nz5km_his_201708.nc?ntimes,dt,hc,grid,s_rho[5:1:12],Cs_r[5:1:12],h[0:1:466][0:1:396],lon_rho[0:1:466][0:1:396],lat_rho[0:1:466][0:1:396],lon_u[0:1:466][0:1:395],lat_u[0:1:466][0:1:395],lon_v[0:1:465][0:1:396],lat_v[0:1:465][0:1:396],lon_psi[0:1:465][0:1:395],angle[0:1:466][0:1:396],mask_rho[0:1:466][0:1:396],mask_u[0:1:466][0:1:395],mask_v[0:1:465][0:1:396],ocean_time[0:1:248],z_rho[0:1:248][5:1:12][0:1:466][0:1:396],u_eastward[0:1:248][5:1:12][0:1:466][0:1:396],v_northward[0:1:248][5:1:12][0:1:466][0:1:396]' # to finish the run in the previous month
reader_moana_v19_2 = reader_ROMS_native_MOANA.Reader([thredds_path_2]) #
reader_moana_v19_2.multiprocessing_fail = True
thredds_path_3 = 'http://thredds.moanaproject.org:8080/thredds/dodsC/moana/ocean/NZB/v1.9/raw_3D/nz5km_his_201707.nc?ntimes,dt,hc,grid,s_rho[5:1:12],Cs_r[5:1:12],h[0:1:466][0:1:396],lon_rho[0:1:466][0:1:396],lat_rho[0:1:466][0:1:396],lon_u[0:1:466][0:1:395],lat_u[0:1:466][0:1:395],lon_v[0:1:465][0:1:396],lat_v[0:1:465][0:1:396],lon_psi[0:1:465][0:1:395],angle[0:1:466][0:1:396],mask_rho[0:1:466][0:1:396],mask_u[0:1:466][0:1:395],mask_v[0:1:465][0:1:396],ocean_time[0:1:248],z_rho[0:1:248][5:1:12][0:1:466][0:1:396],u_eastward[0:1:248][5:1:12][0:1:466][0:1:396],v_northward[0:1:248][5:1:12][0:1:466][0:1:396]' # to finish the run in the previous month
#!/usr/bin/env python
import numpy as np
from opendrift.readers import reader_netCDF_CF_generic
from opendrift.readers import reader_ROMS_native
from opendrift.models.oceandrift import OceanDrift
o = OceanDrift(loglevel=0) # Set loglevel to 0 for debug information
o.max_speed = 3
# This example works better using hourly input from Thredds than the daily data from test folder
reader_nordic = reader_netCDF_CF_generic.Reader('http://thredds.met.no/thredds/dodsC/sea/nordic4km/zdepths1h/aggregate_be')
#reader_nordic = reader_ROMS_native.Reader(o.test_data_folder() +
# '2Feb2016_Nordic_sigma_3d/Nordic-4km_SLEVELS_avg_00_subset2Feb2016.nc')
o.add_reader([reader_nordic])
o.set_config('general:basemap_resolution', 'h')
o.set_config('general:coastline_action', 'previous')
# Seeding elements on a grid
lons = np.linspace(12, 14.5, 30)
lats = np.linspace(67.5, 68.5, 30)
lons, lats = np.meshgrid(lons, lats)
lon = lons.ravel()
lat = lats.ravel()
time = reader_nordic.start_time
o.seed_elements(lon, lat, radius=0, number=30*30, time=time)
from opendrift.models.oceandrift import OceanDrift
from opendrift.readers import reader_oscillating
# readers
o = OceanDrift(loglevel=50)
reader_norkyst = reader_netCDF_CF_generic.Reader(o.test_data_folder() + '14Jan2016_NorKyst_z_3d/NorKyst-800m_ZDEPTHS_his_00_3Dsubset.nc')
reader_osc = reader_oscillating.Reader('x_sea_water_velocity', amplitude=10, period_seconds=3600)
runs = []
seafloor_actions = ['previous', 'deactivate', 'lift_to_seafloor']
for seafloor_action in seafloor_actions:
o = OceanDrift(loglevel=50) # Set loglevel to 0 for debug information
o.max_speed = 10
o.add_reader([reader_osc, reader_norkyst])
o.set_config('drift:horizontal_diffusivity', 0)
o.set_config('environment:constant:y_sea_water_velocity', 0)
o.set_config('environment:constant:land_binary_mask', 0)
o.set_config('general:use_auto_landmask', False)
o.set_config('general:seafloor_action', seafloor_action)
# Seeding some particles 50m above seafloor
o.seed_elements(lon=4.2, lat=62.0, z='seafloor+50',
radius=7000, number=200, time=reader_norkyst.start_time)
o.run(duration=timedelta(hours=2), time_step=120)
runs.append(o)
