Source code for opendrift.models.pelagicegg

# This file is part of OpenDrift.
#
# OpenDrift is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, version 2
#
# OpenDrift is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with OpenDrift.  If not, see <https://www.gnu.org/licenses/>.
#
# Copyright 2015, Knut-Frode Dagestad, MET Norway

import numpy as np
import logging; logger = logging.getLogger(__name__)

from opendrift.models.oceandrift import OceanDrift, Lagrangian3DArray
#from opendrift.elements import LagrangianArray


# Defining the oil element properties
[docs]class PelagicEgg(Lagrangian3DArray): """Extending Lagrangian3DArray with specific properties for pelagic eggs """ variables = Lagrangian3DArray.add_variables([ ('diameter', {'dtype': np.float32, 'units': 'm', 'default': 0.0014}), # for NEA Cod ('neutral_buoyancy_salinity', {'dtype': np.float32, 'units': '[]', 'default': 31.25}), # for NEA Cod ('density', {'dtype': np.float32, 'units': 'kg/m^3', 'default': 1028.}), ('hatched', {'dtype': np.float32, 'units': '', 'default': 0.})])
[docs]class PelagicEggDrift(OceanDrift): """Buoyant particle trajectory model based on the OpenDrift framework. Developed at MET Norway Generic module for particles that are subject to vertical turbulent mixing with the possibility for positive or negative buoyancy Particles could be e.g. oil droplets, plankton, or sediments Under construction. """ ElementType = PelagicEgg required_variables = { 'x_sea_water_velocity': {'fallback': 0}, 'y_sea_water_velocity': {'fallback': 0}, 'sea_surface_wave_significant_height': {'fallback': 0}, 'sea_ice_area_fraction': {'fallback': 0}, 'x_wind': {'fallback': 0}, 'y_wind': {'fallback': 0}, 'land_binary_mask': {'fallback': None}, 'sea_floor_depth_below_sea_level': {'fallback': 100}, 'ocean_vertical_diffusivity': {'fallback': 0.02, 'profiles': True}, 'sea_water_temperature': {'fallback': 10, 'profiles': True}, 'sea_water_salinity': {'fallback': 34, 'profiles': True}, 'surface_downward_x_stress': {'fallback': 0}, 'surface_downward_y_stress': {'fallback': 0}, 'turbulent_kinetic_energy': {'fallback': 0}, 'turbulent_generic_length_scale': {'fallback': 0}, 'upward_sea_water_velocity': {'fallback': 0}, } # The depth range (in m) which profiles shall cover required_profiles_z_range = [-120, 0] # Default colors for plotting status_colors = {'initial': 'green', 'active': 'blue', 'hatched': 'red', 'eaten': 'yellow', 'died': 'magenta'} def __init__(self, *args, **kwargs): # Calling general constructor of parent class super(PelagicEggDrift, self).__init__(*args, **kwargs) # By default, eggs do not strand towards coastline self.set_config('general:coastline_action', 'previous') # Vertical mixing is enabled by default self.set_config('drift:vertical_mixing', True)
[docs] def update_terminal_velocity(self, Tprofiles=None, Sprofiles=None, z_index=None): """Calculate terminal velocity for Pelagic Egg according to S. Sundby (1983): A one-dimensional model for the vertical distribution of pelagic fish eggs in the mixed layer Deep Sea Research (30) pp. 645-661 Method copied from ibm.f90 module of LADIM: Vikebo, F., S. Sundby, B. Aadlandsvik and O. Otteraa (2007), Fish. Oceanogr. (16) pp. 216-228 """ g = 9.81 # ms-2 # Pelagic Egg properties that determine buoyancy eggsize = self.elements.diameter # 0.0014 for NEA Cod eggsalinity = self.elements.neutral_buoyancy_salinity # 31.25 for NEA Cod # prepare interpolation of temp, salt if not (Tprofiles is None and Sprofiles is None): if z_index is None: z_i = range(Tprofiles.shape[0]) # evtl. move out of loop # evtl. move out of loop z_index = interp1d(-self.environment_profiles['z'], z_i, bounds_error=False) zi = z_index(-self.elements.z) upper = np.maximum(np.floor(zi).astype(np.uint8), 0) lower = np.minimum(upper+1, Tprofiles.shape[0]-1) weight_upper = 1 - (zi - upper) # do interpolation of temp, salt if profiles were passed into # this function, if not, use reader by calling self.environment if Tprofiles is None: T0 = self.environment.sea_water_temperature else: T0 = Tprofiles[upper, range(Tprofiles.shape[1])] * \ weight_upper + \ Tprofiles[lower, range(Tprofiles.shape[1])] * \ (1-weight_upper) if Sprofiles is None: S0 = self.environment.sea_water_salinity else: S0 = Sprofiles[upper, range(Sprofiles.shape[1])] * \ weight_upper + \ Sprofiles[lower, range(Sprofiles.shape[1])] * \ (1-weight_upper) # The density difference bettwen a pelagic egg and the ambient water # is regulated by their salinity difference through the # equation of state for sea water. # The Egg has the same temperature as the ambient water and its # salinity is regulated by osmosis through the egg shell. DENSw = self.sea_water_density(T=T0, S=S0) DENSegg = self.sea_water_density(T=T0, S=eggsalinity) dr = DENSw-DENSegg # density difference # water viscosity my_w = 0.001*(1.7915 - 0.0538*T0 + 0.007*(T0**(2.0)) - 0.0023*S0) # ~0.0014 kg m-1 s-1 # terminal velocity for low Reynolds numbers W = (1.0/my_w)*(1.0/18.0)*g*eggsize**2 * dr # check if we are in a Reynolds regime where Re > 0.5 highRe = np.where(W*1000*eggsize/my_w > 0.5) # Use empirical equations for terminal velocity in # high Reynolds numbers. # Empirical equations have length units in cm! my_w = 0.01854 * np.exp(-0.02783 * T0) # in cm2/s d0 = (eggsize * 100) - 0.4 * \ (9.0 * my_w**2 / (100 * g) * DENSw / dr)**(1.0 / 3.0) # cm W2 = 19.0*d0*(0.001*dr)**(2.0/3.0)*(my_w*0.001*DENSw)**(-1.0/3.0) # cm/s W2 = W2/100. # back to m/s W[highRe] = W2[highRe] self.elements.terminal_velocity = W
[docs] def update(self): """Update positions and properties of buoyant particles.""" # Turbulent Mixing self.update_terminal_velocity() self.vertical_mixing() # Horizontal advection self.advect_ocean_current() # Vertical advection if self.get_config('drift:vertical_advection') is True: self.vertical_advection()