Source code for polaris.ocean.vertical.ztilde

"""
Conversions between Omega pseudo-height and pressure.

Omega's vertical coordinate is pseudo-height
    z_tilde = -p / (rho0 * g)
with z_tilde positive upward. Here, ``p`` is sea pressure in Pascals (Pa),
``rho0`` is a reference density (kg m^-3) supplied by the caller, and
``g`` is gravitational acceleration obtained from
``mpas_tools.cime.constants``.
"""

import logging

import numpy as np
import xarray as xr

from polaris.config import PolarisConfigParser
from polaris.constants import get_constant
from polaris.ocean.eos import compute_specvol

__all__ = [
    'z_tilde_from_pressure',
    'pressure_from_z_tilde',
    'pressure_and_spec_vol_from_state_at_geom_height',
    'pressure_from_geom_thickness',
]

Gravity = get_constant('standard_acceleration_of_gravity')


[docs] def z_tilde_from_pressure(p: xr.DataArray, rho0: float) -> xr.DataArray: """ Convert sea pressure to pseudo-height. z_tilde = -p / (rho0 * g) Parameters ---------- p : xarray.DataArray Sea pressure in Pascals (Pa). rho0 : float Reference density in kg m^-3. Returns ------- xarray.DataArray Pseudo-height with the same shape and coords as ``p`` (units: m). """ z = -(p) / (rho0 * Gravity) return z.assign_attrs( { 'long_name': 'pseudo-height', 'units': 'm', 'note': 'z_tilde = -p / (rho0 * g)', } )
[docs] def pressure_from_z_tilde(z_tilde: xr.DataArray, rho0: float) -> xr.DataArray: """ Convert pseudo-height to sea pressure. p = -z_tilde * (rho0 * g) Parameters ---------- z_tilde : xarray.DataArray Pseudo-height in meters (m), positive upward. rho0 : float Reference density in kg m^-3. Returns ------- xarray.DataArray Sea pressure with the same shape and coords as ``z_tilde`` (Pa). """ p = -(z_tilde) * (rho0 * Gravity) return p.assign_attrs( { 'long_name': 'sea pressure', 'units': 'Pa', 'note': 'p = -rho0 * g * z_tilde', } )
[docs] def pressure_from_geom_thickness( surf_pressure: xr.DataArray, geom_layer_thickness: xr.DataArray, spec_vol: xr.DataArray, ) -> tuple[xr.DataArray, xr.DataArray]: """ Compute the pressure at layer interfaces and midpoints given surface pressure, geometric layer thicknesses, and specific volume. This calculation assumes a constant specific volume within each layer. Parameters ---------- surf_pressure : xarray.DataArray The surface pressure at the top of the water column. geom_layer_thickness : xarray.DataArray The geometric thickness of each layer, set to zero for invalid layers. spec_vol : xarray.DataArray The specific volume at each layer. Returns ------- p_interface : xarray.DataArray The pressure at layer interfaces. p_mid : xarray.DataArray The pressure at layer midpoints. """ dp = Gravity / spec_vol * geom_layer_thickness p_interface = dp.cumsum(dim='nVertLevels').pad( nVertLevels=(1, 0), mode='constant', constant_values=0.0 ) p_interface = surf_pressure + p_interface p_interface = p_interface.rename({'nVertLevels': 'nVertLevelsP1'}) p_interface_top = p_interface.isel(nVertLevelsP1=slice(0, -1)).rename( {'nVertLevelsP1': 'nVertLevels'} ) p_mid = p_interface_top + 0.5 * dp dims = list(geom_layer_thickness.dims) interface_dims = [dim for dim in dims if dim != 'nVertLevels'] interface_dims.append('nVertLevelsP1') p_interface = p_interface.transpose(*interface_dims) p_mid = p_mid.transpose(*dims) return p_interface, p_mid
[docs] def pressure_and_spec_vol_from_state_at_geom_height( config: PolarisConfigParser, geom_layer_thickness: xr.DataArray, temperature: xr.DataArray, salinity: xr.DataArray, surf_pressure: xr.DataArray, iter_count: int, logger: logging.Logger | None = None, ) -> tuple[xr.DataArray, xr.DataArray, xr.DataArray]: """ Compute the pressure at layer interfaces and midpoints, as well as the specific volume at midpoints given geometric layer thicknesses, temperature and salinity at layer midpoints (i.e. constant in geometric height, not pseudo-height), and surface pressure. The solution is found iteratively starting from a specific volume calculated from the reference density. Requires config option ``[vertical_grid] rho0`` and those required for {py:func}`polaris.ocean.eos.compute_specvol()`. Parameters ---------- config : polaris.config.PolarisConfigParser Configuration options with parameters defining the equation of state and ``rho0`` for the pseudo-height. geom_layer_thickness : xarray.DataArray The geometric thickness of each layer. temperature : xarray.DataArray The temperature at layer midpoints. salinity : xarray.DataArray The salinity at layer midpoints. surf_pressure : xarray.DataArray The surface pressure at the top of the water column. iter_count : int The number of iterations to perform. logger : logging.Logger, optional A logger for logging iteration information. Returns ------- p_interface : xarray.DataArray The pressure at layer interfaces. p_mid : xarray.DataArray The pressure at layer midpoints. spec_vol : xarray.DataArray The specific volume at layer midpoints. """ rho0 = config.getfloat('vertical_grid', 'rho0') if rho0 is None: raise ValueError( 'Config option [vertical_grid] rho0 must be set to use ' 'pressure_and_spec_vol_from_state_at_geom_height().' ) spec_vol = 1.0 / rho0 * xr.ones_like(geom_layer_thickness) p_interface, p_mid = pressure_from_geom_thickness( surf_pressure=surf_pressure, geom_layer_thickness=geom_layer_thickness, spec_vol=spec_vol, ) prev_spec_vol = spec_vol for iter in range(iter_count): spec_vol = compute_specvol( config=config, temperature=temperature, salinity=salinity, pressure=p_mid, ) if logger is not None: delta_spec_vol = spec_vol - prev_spec_vol max_delta = np.abs(delta_spec_vol).max().item() prev_spec_vol = spec_vol logger.info( f'Max change in specific volume during EOS iteration {iter}: ' f'{max_delta:.3e} m3 kg-1' ) p_interface, p_mid = pressure_from_geom_thickness( surf_pressure=surf_pressure, geom_layer_thickness=geom_layer_thickness, spec_vol=spec_vol, ) return p_interface, p_mid, spec_vol
[docs] def geom_height_from_pseudo_height( geom_z_bot: xr.DataArray, h_tilde: xr.DataArray, spec_vol: xr.DataArray, min_level_cell: np.ndarray, max_level_cell: np.ndarray, rho0: float, ) -> tuple[xr.DataArray, xr.DataArray]: """ Sum geometric heights from pseudo-heights and specific volume. Parameters ---------- geom_z_bot : xarray.DataArray Geometric height at the bathymetry for each water column. h_tilde : xarray.DataArray Pseudo-thickness of vertical layers, set to zero for invalid layers. spec_vol : xarray.DataArray Specific volume at midpoints of vertical layers. min_level_cell : xarray.DataArray Minimum valid zero-based level index for each cell. max_level_cell : xarray.DataArray Maximum valid zero-based level index for each cell. rho0 : float Reference density in kg m^-3. Returns ------- geom_z_inter : xarray.DataArray Geometric height at layer interfaces. geom_z_mid : xarray.DataArray Geometric height at layer midpoints. """ # geometric height starts with geom_z_bot at the bottom # and adds up the contributions from each layer above n_vert_levels = spec_vol.sizes['nVertLevels'] z_index = xr.DataArray(np.arange(n_vert_levels), dims=['nVertLevels']) mid_mask = np.logical_and( z_index >= min_level_cell, z_index <= max_level_cell ) geom_thickness = (spec_vol * h_tilde * rho0).where(mid_mask, 0.0) dz_rev = geom_thickness.isel(nVertLevels=slice(None, None, -1)) sum_from_level = dz_rev.cumsum(dim='nVertLevels').isel( nVertLevels=slice(None, None, -1) ) geom_z_inter_top = geom_z_bot + sum_from_level geom_z_inter = geom_z_inter_top.pad( nVertLevels=(0, 1), mode='constant', constant_values=0.0 ) geom_z_inter[dict(nVertLevels=n_vert_levels)] = geom_z_bot geom_z_inter = geom_z_inter.rename({'nVertLevels': 'nVertLevelsP1'}) z_index_p1 = xr.DataArray( np.arange(n_vert_levels + 1), dims=['nVertLevelsP1'] ) inter_mask = np.logical_and( z_index_p1 >= min_level_cell, z_index_p1 <= max_level_cell + 1, ) geom_z_inter = geom_z_inter.where(inter_mask) geom_z_inter_lower = geom_z_inter.isel( nVertLevelsP1=slice(1, None) ).rename({'nVertLevelsP1': 'nVertLevels'}) geom_z_mid = (geom_z_inter_lower + 0.5 * geom_thickness).where(mid_mask) # transpose to match h_tilde. For geom_z_inter, replace nVertLevels with # nVertLevelsP1 at the same index in the list of dimensions z_mid_dims = list(h_tilde.dims) z_inter_dims = z_mid_dims.copy() z_inter_dims[z_mid_dims.index('nVertLevels')] = 'nVertLevelsP1' geom_z_inter = geom_z_inter.transpose(*z_inter_dims) geom_z_mid = geom_z_mid.transpose(*z_mid_dims) return geom_z_inter, geom_z_mid