def test_attenuation_correction_rsl():
""" Test calculate_attenuation on data read using RSL """
# read in the data
radar = pyart.io.read_rsl(RSLNAME)
# add the fields created by phase_proc
reproc_phase = np.load(PHASENAME)
radar.fields['proc_dp_phase_shift'] = {'data': reproc_phase}
spec_at, cor_z = attenuation.calculate_attenuation(
radar, 8.6, debug=True, a_coef=0.17)
ref_cor_z = np.load(CORZNAME)
ref_spec_at = np.load(SPECATNAME)
# XXX no recasting to float32 should be done here.
cor_z['data'].data[cor_z['data'].mask] = -9999.0
assert_array_equal(ref_spec_at, spec_at['data'].astype('float32'))
assert_array_equal(ref_cor_z, cor_z['data'].astype('float32'))
def test_attenuation_correction_rsl():
""" Test calculate_attenuation on data read using RSL """
# read in the data
radar = pyart.io.read_rsl(RSLNAME)
# add the fields created by phase_proc
reproc_phase = np.load(PHASENAME)
radar.fields['proc_dp_phase_shift'] = {'data': reproc_phase}
spec_at, cor_z = attenuation.calculate_attenuation(radar,
8.6,
debug=True,
a_coef=0.17)
ref_cor_z = np.load(CORZNAME)
ref_spec_at = np.load(SPECATNAME)
# XXX no recasting to float32 should be done here.
cor_z['data'].data[cor_z['data'].mask] = -9999.0
assert_array_equal(ref_spec_at, spec_at['data'].astype('float32'))
assert_array_equal(ref_cor_z, cor_z['data'].astype('float32'))
# append a datetime object
mydatetime = netCDF4.num2date(myradar.time['data'][0],
myradar.time['units'],
calendar=myradar.time['calendar'])
mydict = dt_to_dict(mydatetime)
mydict.update({'scanmode': {'ppi': 'sur', 'rhi': 'rhi'}
[myradar.sweep_mode[0]], 'fac': metadata['facility']})
ofilename = outdir + '%(scanmode)scmac%(fac)s.c0.%(year)04d%(month)02d%(day)02d.%(hour)02d%(minute)02d%(second)02d.nc' % mydict
reproc_phase, sob_kdp = phase_proc.phase_proc(
myradar, params['reflectivity_offset'], sys_phase=params['sys_phase'],
overide_sys_phase=params['overide_sys_phase'], debug=True, nowrap=ng)
myradar.fields.update({'recalculated_diff_phase': sob_kdp,
'proc_dp_phase_shift': reproc_phase})
#attenuation correction
spec_at, cor_z = attenuation.calculate_attenuation(
myradar, params['reflectivity_offset'], debug=True, a_coef=0.17)
myradar.fields.update({'specific_attenuation': spec_at})
myradar.fields.update({'corrected_reflectivity_horizontal': cor_z})
R = 51.3 * (myradar.fields['specific_attenuation']['data']) ** 0.81
rainrate = copy.deepcopy(myradar.fields['diff_phase'])
rainrate['data'] = R
rainrate['valid_min'] = 0.0
rainrate['valid_max'] = 400.0
rainrate['standard_name'] = 'rainfall_rate'
rainrate['long_name'] = 'rainfall_rate'
rainrate['least_significant_digit'] = 1
rainrate['units'] = 'mm/hr'
myradar.fields.update({'rain_rate_A': rainrate})
netcdf_obj = netCDF4.Dataset(ofilename, 'w', format='NETCDF4')
nc_utils.write_radar4(netcdf_obj, myradar)
netcdf_obj.close()
rge = 40.0 * 1000.0
ng = rge / gates
# Perform Linear programming phase processing to get the conditionally
# fitted phase profile and sobel filtered KDP field
reproc_phase, sob_kdp = phase_proc.phase_proc(
myradar, params['reflectivity_offset'],
sys_phase=params['sys_phase'],
overide_sys_phase=params['overide_sys_phase'], debug=True, nowrap=ng)
# Append these back into the radar object
myradar.fields.update({'recalculated_diff_phase': sob_kdp,
'proc_dp_phase_shift': reproc_phase})
# attenuation correction, this time we just use a straight procedural
# method, this is a variant of the ZPHI technique and returns both the
# specific attenuation (dBZ/km) and corrected Z (dBZ)
# Note: no ZDR correction as of yet...
spec_at, cor_z = attenuation.calculate_attenuation(
myradar, params['reflectivity_offset'], debug=True, ncp_min=0.4)
# Append these new fields to the radar object
myradar.fields.update({'specific_attenuation': spec_at})
myradar.fields.update({'corrected_reflectivity_horizontal': cor_z})
# The following lines deal with determining file name
mydatetime = netCDF4.num2date(myradar.time['data'][0],
myradar.time['units'],
calendar=myradar.time['calendar'])
#append a datetime object
mydict = dt_to_dict(mydatetime)
mydict.update({
'scanmode': {'ppi': 'sur', 'rhi': 'rhi'}[myradar.sweep_mode[0]],
'fac': metadata['facility']})
ofilename = outdir + '%(scanmode)scmac%(fac)s.c0.%(year)04d%(month)02d%(day)02d.%(hour)02d%(minute)02d%(second)02d.nc' % mydict
# Open a netcdf file for output
netcdf_obj = netCDF4.Dataset(ofilename, 'w', format='NETCDF4')
rge = 10.0 * 1000.0
ng = rge / gates
mydatetime = netCDF4.num2date(
myradar.time['data'][0], myradar.time['units'],
calendar=myradar.time['calendar']) # append a datetime object
mydict = dt_to_dict(mydatetime)
mydict.update({'scanmode': {'ppi': 'sur', 'rhi': 'rhi'}
[myradar.sweep_mode[0]], 'fac': fac})
ofilename = outdir + '%(scanmode)scmac%(fac)s.c0.%(year)04d%(month)02d%(day)02d.%(hour)02d%(minute)02d%(second)02d.nc' % mydict
reproc_phase, sob_kdp = phase_proc.phase_proc(myradar, offset, debug=True,
nowrap)
myradar.fields.update({'recalculated_diff_phase': sob_kdp,
'proc_dp_phase_shift': reproc_phase})
# attenuation correction
spec_at, cor_z = attenuation.calculate_attenuation(
myradar, offset, debug=True, a_coef=0.17)
myradar.fields.update({'specific_attenuation': spec_at})
myradar.fields.update({'corrected_reflectivity_horizontal': cor_z})
R = 51.3 * (myradar.fields['specific_attenuation']['data']) ** 0.81
rainrate = copy.deepcopy(myradar.fields['diff_phase'])
rainrate['data'] = R
rainrate['valid_min'] = 0.0
rainrate['valid_max'] = 400.0
rainrate['standard_name'] = 'rainfall_rate'
rainrate['long_name'] = 'rainfall_rate'
rainrate['least_significant_digit'] = 1
rainrate['units'] = 'mm/hr'
myradar.fields.update({'rain_rate_A': rainrate})
netcdf_obj = netCDF4.Dataset(ofilename, 'w', format='NETCDF4')
nc_utils.write_radar4(netcdf_obj, myradar)
netcdf_obj.close()
# append a datetime object
mydatetime = netCDF4.num2date(myradar.time['data'][0],
myradar.time['units'],
calendar=myradar.time['calendar'])
mydict = dt_to_dict(mydatetime)
mydict.update({'scanmode': {'ppi': 'sur', 'rhi': 'rhi'}
[myradar.sweep_mode[0]], 'fac': metadata['facility'],
'name':metadata['instrument_name']})
ofilename = outdir + '%(name)s%(scanmode)scmac%(fac)s.c0.%(year)04d%(month)02d%(day)02d.%(hour)02d%(minute)02d%(second)02d.nc' % mydict
reproc_phase, sob_kdp = phase_proc.phase_proc_lp(
myradar, params['reflectivity_offset'], sys_phase=params['sys_phase'],
overide_sys_phase=params['overide_sys_phase'], debug=True, nowrap=ng)
myradar.fields.update({'recalculated_diff_phase': sob_kdp,
'proc_dp_phase_shift': reproc_phase})
#attenuation correction
spec_at, cor_z = attenuation.calculate_attenuation(
myradar, params['reflectivity_offset'], debug=True, a_coef=0.17)
myradar.fields.update({'specific_attenuation': spec_at})
myradar.fields.update({'corrected_reflectivity_horizontal': cor_z})
R = 51.3 * (myradar.fields['specific_attenuation']['data']) ** 0.81
rainrate = copy.deepcopy(myradar.fields['diff_phase'])
rainrate['data'] = R
rainrate['valid_min'] = 0.0
rainrate['valid_max'] = 400.0
rainrate['standard_name'] = 'rainfall_rate'
rainrate['long_name'] = 'rainfall_rate'
rainrate['least_significant_digit'] = 1
rainrate['units'] = 'mm/hr'
myradar.fields.update({'rain_rate_A': rainrate})
mask=myradar.fields['corrected_reflectivity_horizontal']['data'].mask
myradar.fields['rain_rate_A']['data'][np.where(mask)]=0.0
myradar.fields['rain_rate_A'].update({'comment':'Rain rate calculated from specific_attenuation, R=51.3*specific_attenuation**0.81, note R=0.0 where norm coherent power < 0.4 or rhohv < 0.8'})
outdir = sys.argv[2]
# open the radar file
my_mdv_object = py_mdv.read_mdv(filename, debug=True)
myradar = radar.Radar(my_mdv_object)
gates = myradar.range['data'][1] - myradar.range['data'][0]
rge = 10.0 * 1000.0
ng = rge / gates
#append a datetime object
mydatetime = netCDF4.num2date(myradar.time['data'][0],
myradar.time['units'],
calendar=myradar.time['calendar'])
mydict = dt_to_dict(mydatetime)
mydict.update({'scanmode': {'ppi': 'sur', 'rhi': 'rhi'}
[myradar.sweep_mode[0]]})
ofilename = outdir + '%(scanmode)scmacI7.c0.%(year)04d%(month)02d%(day)02d.%(hour)02d%(minute)02d%(second)02d.nc' % mydict
reproc_phase, sob_kdp = phase_proc.phase_proc(myradar, -2.0, debug=True,
nowrap=ng)
myradar.fields.update({'recalculated_diff_phase': sob_kdp,
'proc_dp_phase_shift': reproc_phase})
spec_at, cor_z = attenuation.calculate_attenuation(
myradar, -2.0, debug=True)
myradar.fields.update({'specific_attenuation': spec_at})
myradar.fields.update({'corrected_reflectivity_horizontal': cor_z})
netcdf_obj = netCDF4.Dataset(ofilename, 'w', format='NETCDF4')
nc_utils.write_radar4(netcdf_obj, myradar)
netcdf_obj.close()
