A collection of diagnostic and interpolation routines for use with output from the Weather Research and Forecasting (WRF-ARW) Model.
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from __future__ import (absolute_import, division, print_function)
import numpy as np
from .constants import Constants
from .extension import _srhel, _udhel
from .destag import destagger
from .util import extract_vars, extract_global_attrs, either
from .metadecorators import copy_and_set_metadata
from .g_latlon import get_lat
@copy_and_set_metadata(copy_varname="HGT", name="srh",
description="storm relative helicity",
units="m2 s-2")
def get_srh(wrfin, timeidx=0, method="cat", squeeze=True,
cache=None, meta=True, _key=None, top=3000.0):
"""Return the storm relative helicity.
The *top* argument specifies the top of the integration in [m].
This functions extracts the necessary variables from the NetCDF file
object in order to perform the calculation.
Args:
wrfin (:class:`netCDF4.Dataset`, :class:`Nio.NioFile`, or an \
iterable): WRF-ARW NetCDF
data as a :class:`netCDF4.Dataset`, :class:`Nio.NioFile`
or an iterable sequence of the aforementioned types.
timeidx (:obj:`int` or :data:`wrf.ALL_TIMES`, optional): The
desired time index. This value can be a positive integer,
negative integer, or
:data:`wrf.ALL_TIMES` (an alias for None) to return
all times in the file or sequence. The default is 0.
method (:obj:`str`, optional): The aggregation method to use for
sequences. Must be either 'cat' or 'join'.
'cat' combines the data along the Time dimension.
'join' creates a new dimension for the file index.
The default is 'cat'.
squeeze (:obj:`bool`, optional): Set to False to prevent dimensions
with a size of 1 from being automatically removed from the shape
of the output. Default is True.
cache (:obj:`dict`, optional): A dictionary of (varname, ndarray)
that can be used to supply pre-extracted NetCDF variables to the
computational routines. It is primarily used for internal
purposes, but can also be used to improve performance by
eliminating the need to repeatedly extract the same variables
used in multiple diagnostics calculations, particularly when using
large sequences of files.
Default is None.
meta (:obj:`bool`, optional): Set to False to disable metadata and
return :class:`numpy.ndarray` instead of
:class:`xarray.DataArray`. Default is True.
_key (:obj:`int`, optional): A caching key. This is used for internal
purposes only. Default is None.
top (:obj:`float`, optional): The top of the integration in [m].
Default is 3000.0.
Returns:
:class:`xarray.DataArray` or :class:`numpy.ndarray`: The
storm relative helicity.
If xarray is enabled and the *meta* parameter is True, then the result
will be a :class:`xarray.DataArray` object. Otherwise, the result will
be a :class:`numpy.ndarray` object with no metadata.
"""
# Top can either be 3000 or 1000 (for 0-1 srh or 0-3 srh)
lats = get_lat(wrfin, timeidx, method, squeeze,
cache, meta=False, _key=_key, stagger=None)
ncvars = extract_vars(wrfin, timeidx, ("HGT", "PH", "PHB"),
method, squeeze, cache, meta=False,
_key=_key)
ter = ncvars["HGT"]
ph = ncvars["PH"]
phb = ncvars["PHB"]
# As coded in NCL, but not sure this is possible
varname = either("U", "UU")(wrfin)
u_vars = extract_vars(wrfin, timeidx, varname, method, squeeze, cache,
meta=False, _key=_key)
u = destagger(u_vars[varname], -1)
varname = either("V", "VV")(wrfin)
v_vars = extract_vars(wrfin, timeidx, varname, method, squeeze, cache,
meta=False, _key=_key)
v = destagger(v_vars[varname], -2)
geopt = ph + phb
geopt_unstag = destagger(geopt, -3)
z = geopt_unstag / Constants.G
# Re-ordering from high to low
u1 = np.ascontiguousarray(u[..., ::-1, :, :])
v1 = np.ascontiguousarray(v[..., ::-1, :, :])
z1 = np.ascontiguousarray(z[..., ::-1, :, :])
srh = _srhel(u1, v1, z1, ter, lats, top)
return srh
@copy_and_set_metadata(copy_varname="MAPFAC_M", name="updraft_helicity",
description="updraft helicity",
units="m2 s-2")
def get_uh(wrfin, timeidx=0, method="cat", squeeze=True,
cache=None, meta=True, _key=None,
bottom=2000.0, top=5000.0):
"""Return the updraft helicity.
The *bottom* and *top* arguments specify the bottom and top limits
for the integration in [m].
This functions extracts the necessary variables from the NetCDF file
object in order to perform the calculation.
Args:
wrfin (:class:`netCDF4.Dataset`, :class:`Nio.NioFile`, or an \
iterable): WRF-ARW NetCDF
data as a :class:`netCDF4.Dataset`, :class:`Nio.NioFile`
or an iterable sequence of the aforementioned types.
timeidx (:obj:`int` or :data:`wrf.ALL_TIMES`, optional): The
desired time index. This value can be a positive integer,
negative integer, or
:data:`wrf.ALL_TIMES` (an alias for None) to return
all times in the file or sequence. The default is 0.
method (:obj:`str`, optional): The aggregation method to use for
sequences. Must be either 'cat' or 'join'.
'cat' combines the data along the Time dimension.
'join' creates a new dimension for the file index.
The default is 'cat'.
squeeze (:obj:`bool`, optional): Set to False to prevent dimensions
with a size of 1 from being automatically removed from the shape
of the output. Default is True.
cache (:obj:`dict`, optional): A dictionary of (varname, ndarray)
that can be used to supply pre-extracted NetCDF variables to the
computational routines. It is primarily used for internal
purposes, but can also be used to improve performance by
eliminating the need to repeatedly extract the same variables
used in multiple diagnostics calculations, particularly when using
large sequences of files.
Default is None.
meta (:obj:`bool`, optional): Set to False to disable metadata and
return :class:`numpy.ndarray` instead of
:class:`xarray.DataArray`. Default is True.
_key (:obj:`int`, optional): A caching key. This is used for internal
purposes only. Default is None.
bottom (:obj:`float`, optional): The bottom limit for the integration
in [m]. Default is 2000.0.
top (:obj:`float`, optional): The top limit for the integration in [m].
Default is 5000.0.
Returns:
:class:`xarray.DataArray` or :class:`numpy.ndarray`: The
updraft helicity.
If xarray is enabled and the *meta* parameter is True, then the result
will be a :class:`xarray.DataArray` object. Otherwise, the result will
be a :class:`numpy.ndarray` object with no metadata.
"""
ncvars = extract_vars(wrfin, timeidx, ("W", "PH", "PHB", "MAPFAC_M"),
method, squeeze, cache, meta=False, _key=_key)
wstag = ncvars["W"]
ph = ncvars["PH"]
phb = ncvars["PHB"]
mapfct = ncvars["MAPFAC_M"]
attrs = extract_global_attrs(wrfin, attrs=("DX", "DY"))
dx = attrs["DX"]
dy = attrs["DY"]
# As coded in NCL, but not sure this is possible
varname = either("U", "UU")(wrfin)
u_vars = extract_vars(wrfin, timeidx, varname, method, squeeze, cache,
meta=False, _key=_key)
u = destagger(u_vars[varname], -1)
varname = either("V", "VV")(wrfin)
v_vars = extract_vars(wrfin, timeidx, varname, method, squeeze, cache,
meta=False, _key=_key)
v = destagger(v_vars[varname], -2)
zp = (ph + phb) / Constants.G
uh = _udhel(zp, mapfct, u, v, wstag, dx, dy, bottom, top)
return uh