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129 lines
4.3 KiB
Python
129 lines
4.3 KiB
Python
#-----------------------------------------------------
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# Author: Yaqiang Wang
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# Date: 2018-11-23
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# Purpose: MeteoInfoLab wrf module
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# Note: Jython, some functions revised from wrf-python
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#-----------------------------------------------------
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from org.meteoinfo.math.meteo import MeteoMath
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from mipylib.numeric.core import NDArray, DimArray
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import constants as constants
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from .calc.thermo import relative_humidity_from_specific_humidity, temperature_from_potential_temperature
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__all__ = [
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'destagger','get_slp','get_rh','get_rh2m'
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]
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def destagger(var, stagger_dim):
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"""
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Return the variable data array on the unstaggered grid.
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This function destaggers the variable by taking the average of the
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values located on either side of the grid box.
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:param var: (*array*) A variable on a staggered grid.
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:param stagger_dim: (*int*) The dimension index to destagger.
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Negative values can be used to choose dimensions referenced
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from the right hand side (-1 is the rightmost dimension).
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:returns: (*array*) The destaggered variable data array.
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"""
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var_shape = var.shape
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num_dims = var.ndim
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stagger_dim_size = var_shape[stagger_dim]
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# Dynamically building the range slices to create the appropriate
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# number of ':'s in the array accessor lists.
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# For example, for a 3D array, the calculation would be
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# result = .5 * (var[:,:,0:stagger_dim_size-2]
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# + var[:,:,1:stagger_dim_size-1])
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# for stagger_dim=2. So, full slices would be used for dims 0 and 1, but
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# dim 2 needs the special slice.
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full_slice = slice(None)
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slice1 = slice(0, stagger_dim_size - 1, 1)
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slice2 = slice(1, stagger_dim_size, 1)
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# default to full slices
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dim_ranges_1 = [full_slice] * num_dims
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dim_ranges_2 = [full_slice] * num_dims
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# for the stagger dim, insert the appropriate slice range
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dim_ranges_1[stagger_dim] = slice1
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dim_ranges_2[stagger_dim] = slice2
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result = .5*(var[tuple(dim_ranges_1)] + var[tuple(dim_ranges_2)])
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return result
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def get_slp(wrfin, timeidx=0, units='hPa'):
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'''
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Return the sea level pressure in the specified units.
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This function extracts the necessary variables from the NetCDF file
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object in order to perform the calculation.
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:param wrfin: (*DimDataFile*) Data file.
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:param timeidx: (*int*) Time index.
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:param units: (*string*) The desired units.
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:returns: (*array*) Sea level pressure.
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'''
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t = wrfin['T'][timeidx,:,:,:]
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p = wrfin['P'][timeidx,:,:,:]
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pb = wrfin['PB'][timeidx,:,:,:]
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qvapor = wrfin['QVAPOR'][timeidx,:,:,:]
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ph = wrfin['PH'][timeidx,:,:,:]
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phb = wrfin['PHB'][timeidx,:,:,:]
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full_t = t + constants.T_BASE
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full_p = p + pb
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qvapor[qvapor < 0] = 0.
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full_ph = (ph + phb) / constants.g
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destag_ph = destagger(full_ph, -3)
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tk = temperature_from_potential_temperature(full_p * 0.01, full_t)
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slp = MeteoMath.calSeaPrs(destag_ph._array, tk._array, full_p._array, qvapor._array)
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return DimArray(slp, dims=t.dims[1:])
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def get_rh(wrfin, timeidx=0):
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'''
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Return the relative humidity.
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This functions extracts the necessary variables from the NetCDF file
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object in order to perform the calculation.
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:param wrfin: (*DimDataFile*) Data file.
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:param timeidx: (*int*) Time index.
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:returns: (*array*) Relative humidity.
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'''
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t = wrfin['T'][timeidx,:,:,:]
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p = wrfin['P'][timeidx,:,:,:]
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pb = wrfin['PB'][timeidx,:,:,:]
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qvapor = wrfin['QVAPOR'][timeidx,:,:,:]
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full_t = t + constants.T_BASE
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full_p = p + pb
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qvapor[qvapor < 0] = 0.
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tk = temperature_from_potential_temperature(full_p * 0.01, full_t)
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rh = relative_humidity_from_specific_humidity(full_p * 0.01, tk, qvapor)
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return rh
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def get_rh2m(wrfin, timeidx=0):
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'''
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Return the 2m relative humidity.
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This functions extracts the necessary variables from the NetCDF file
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object in order to perform the calculation.
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:param wrfin: (*DimDataFile*) Data file.
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:param timeidx: (*int*) Time index.
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:returns: (*array*) Relative humidity.
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'''
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t2 = wrfin['T2'][timeidx,:,:]
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psfc = wrfin['PSFC'][timeidx,:,:]
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q2 = wrfin['Q2'][timeidx,:,:]
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q2[q2 < 0] = 0.
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rh = relative_humidity_from_specific_humidity(psfc * 0.01, t2, q2)
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return rh |