(**check reply section )I want to derive the latitude and longitude from the given dimension which is time:3960 the concept of time is 360 azimuth and ele:11 the range is: 1600

aswin · February 9, 2024, 6:55am

OrderedDict([(‘time_coverage_start’,
OrderedDict([(‘data’,
array(‘2023-12-3T0:14:49Z’, dtype=‘<U3960’))])),
(‘time_coverage_end’,
OrderedDict([(‘data’, array(‘’, dtype=‘<U3960’))])),
(‘time’,
OrderedDict([(‘standard_name’, ‘time’),
(‘long_name’, ‘time_in_seconds_since_volume_start’),
(‘units’, ‘seconds since yyyy-mm-ddThh:mm:ssZ’),
(‘calendar’, ‘gregorian’),
(‘data’,
masked_array(data=[5.55555556e-02, 1.66666667e-01, 2.77777778e-01, …,
4.39722222e+02, 4.39833333e+02, 4.39944444e+02],
mask=False,
fill_value=1e+20))])),
(‘range’,
OrderedDict([(‘standard_name’, ‘projection_range_coordinate’),
(‘long_name’, ‘range_to_measurement_volume’),
(‘units’, ‘meters’),
(‘spacing_is_constant’, ‘true’),
(‘meters_to_center_of_first_gate’, ‘true’),
(‘axis’, ‘radial_range_coordinate’),
(‘data’,
masked_array(data=[7.50000e+01, 2.25000e+02, 3.75000e+02, …,
2.39625e+05, 2.39775e+05, 2.39925e+05],
mask=False,
fill_value=1e+20))])),
(‘latitude’,
OrderedDict([(‘units’, ‘degrees_north’),
(‘data’,
masked_array(data=8.5374,
mask=False,
fill_value=1e+20))])),
(‘longitude’,
OrderedDict([(‘units’, ‘degrees_east’),
(‘data’,
masked_array(data=76.8657,
mask=False,
fill_value=1e+20))])),
(‘altitude’,
OrderedDict([(‘units’, ‘meters’),
(‘data’, masked_array(data=27.,
mask=False,
fill_value=1e+20))])),
(‘PolType’,
OrderedDict([(‘data’, array(‘Dual Zdr’, dtype=‘<U32’))])),
(‘sweep_number’,
OrderedDict([(‘data’,
masked_array(data=[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
mask=False,
fill_value=999999))])),
(‘sweep_mode’,
OrderedDict([(‘data’,
array([‘azimuth surveillance’, ‘azimuth surveillance’,
‘azimuth surveillance’, ‘azimuth surveillance’,
‘azimuth surveillance’, ‘azimuth surveillance’,
‘azimuth surveillance’, ‘azimuth surveillance’,
‘azimuth surveillance’, ‘azimuth surveillance’,
‘azimuth surveillance’], dtype=‘<U32’))])),
(‘fixed_angle’,
OrderedDict([(‘units’, ‘degrees’),
(‘data’,
masked_array(data=[ 0.5, 1. , 2. , 3. , 4. , 7. , 9. , 12. , 15. ,
18. , 21. ],
mask=False,
fill_value=1e+20,
dtype=float32))])),
(‘sweep_start_ray_index’,
OrderedDict([(‘data’,
masked_array(data=[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
mask=False,
fill_value=999999))])),
(‘sweep_end_ray_index’,
OrderedDict([(‘data’,
masked_array(data=[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
mask=False,
fill_value=999999))])),
(‘azimuth’,
OrderedDict([(‘standard_name’, ‘ray_azimuth_angle’),
(‘units’, ‘degrees’),
(‘long_name’, ‘azimuth_angle_from_true_north’),
(‘axis’, ‘radial_azimuth_coordinate’),
(‘data’,
masked_array(data=[ 0., 1., 2., …, 357., 358., 359.],
mask=False,
fill_value=1e+20,
dtype=float32))])),
(‘elevation’,
OrderedDict([(‘standard_name’, ‘ray_elevation_angle’),
(‘units’, ‘degrees’),
(‘long_name’,
‘elevation_angle_from_horizontal_plane’),
(‘axis’, ‘radial_azimuth_coordinate’),
(‘data’,
masked_array(data=[ 0.5, 0.5, 0.5, …, 21. , 21. , 0. ],
mask=False,
fill_value=1e+20,
dtype=float32))])),
(‘DBZ’,
OrderedDict([(‘units’, ‘dBZ’),
(‘standard_name’, ‘equivalent_reflectivity_factor’),
(‘Polarization’, ‘Horizontal’),
(‘scale_factor’, 0.5),
(‘add_offset’, -32),
(‘FillValue’, 0),
(‘coordinates’, ‘time range’),
(‘data’,
masked_array(
data=[[–, --, 42.5, …, --, --, --],
[–, --, 46.5, …, --, --, --],
[–, --, 50.5, …, --, --, --],
…,
[–, --, 12.0, …, --, --, --],
[–, --, 7.5, …, --, --, --],
[–, --, 11.5, …, --, --, --]],
mask=[[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
…,
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True]],
fill_value=0.0,
dtype=float32))])),
(‘VEL’,
OrderedDict([(‘units’, ‘m/s’),
(‘standard_name’,
'radial_velocity_of_scatterers away_from_instrument’),
(‘Polarization’, ‘Horizontal’),
(‘scale_factor’, 0.18737028625000005),
(‘add_offset’, -23.983396640000006),
(‘_FillValue’, 0),
(‘coordinates’, ‘time range’),
(‘data’,
masked_array(
data=[[–, --, -0.18737030029296875, …, --, --, --],
[–, --, 0.0, …, --, --, --],
[–, --, 0.5621109008789062, …, --, --, --],
…,
[–, --, 0.0, …, --, --, --],
[–, --, 0.18737030029296875, …, --, --, --],
[–, --, -0.18737030029296875, …, --, --, --]],
mask=[[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
…,
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True]],
fill_value=0.0,
dtype=float32))])),
(‘WIDTH’,
OrderedDict([(‘units’, ‘m/s’),
(‘standard_name’, ‘doppler_spectrum_width’),
(‘Polarization’, ‘Horizontal’),
(‘scale_factor’, 0.1),
(‘add_offset’, 0),
(‘_FillValue’, 0),
(‘coordinates’, ‘time range’),
(‘data’,
masked_array(
data=[[–, --, 0.6000000238418579, …, --, --, --],
[–, --, 1.0, …, --, --, --],
[–, --, 0.6000000238418579, …, --, --, --],
…,
[–, --, 0.5, …, --, --, --],
[–, --, 0.6000000238418579, …, --, --, --],
[–, --, 0.800000011920929, …, --, --, --]],
mask=[[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
…,
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True]],
fill_value=0.0,
dtype=float32))])),
(‘ZDR’,
OrderedDict([(‘units’, ‘dB’),
(‘standard_name’,
‘log_differential_reflectivity_hv’),
(‘Polarization’, ‘Horizontal and Vertical’),
(‘scale_factor’, 0.05),
(‘add_offset’, -4),
(‘_FillValue’, 0),
(‘coordinates’, ‘time range’),
(‘data’,
masked_array(
data=[[–, --, 1.0500001907348633, …, --, --, --],
[–, --, 1.1500000953674316, …, --, --, --],
[–, --, -1.9500000476837158, …, --, --, --],
…,
[–, --, -1.8999998569488525, …, --, --, --],
[–, --, -3.5, …, --, --, --],
[–, --, 1.4000000953674316, …, --, --, --]],
mask=[[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
…,
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True]],
fill_value=0.0,
dtype=float32))])),
(‘PHIDP’,
OrderedDict([(‘units’, ‘degrees’),
(‘standard_name’, ‘differential_phase_hv’),
(‘Polarization’, ‘Horizontal and Vertical’),
(‘scale_factor’, 0.088),
(‘add_offset’, -180.0),
(‘_FillValue’, 0),
(‘coordinates’, ‘time range’),
(‘data’,
masked_array(
data=[[–, --, -31.720001220703125, …, --, --, --],
[–, --, -31.720001220703125, …, --, --, --],
[–, --, -31.720001220703125, …, --, --, --],
…,
[–, --, -31.720001220703125, …, --, --, --],
[–, --, -31.720001220703125, …, --, --, --],
[–, --, -31.720001220703125, …, --, --, --]],
mask=[[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
…,
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True]],
fill_value=0.0,
dtype=float32))])),
(‘RHOHV’,
OrderedDict([(‘units’, ‘’),
(‘standard_name’, ‘cross_correlation_ratio_hv’),
(‘Polarization’, ‘Horizontal and Vertical’),
(‘scale_factor’, 0.003921569),
(‘add_offset’, 0),
(‘_FillValue’, 0),
(‘coordinates’, ‘time range’),
(‘data’,
masked_array(
data=[[–, --, 0.6745098233222961, …, --, --, --],
[–, --, 1.0, …, --, --, --],
[–, --, 1.0, …, --, --, --],
…,
[–, --, 0.847058892250061, …, --, --, --],
[–, --, 1.0, …, --, --, --],
[–, --, 0.9568628072738647, …, --, --, --]],
mask=[[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
…,
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True],
[ True, True, False, …, True, True, True]],
fill_value=0.0,
dtype=float32))]))])
"this my variables and its data "

mgrover1 · February 9, 2024, 3:38pm

How did you read in the data? This looks like a Py-ART radar object.

aswin · February 9, 2024, 5:57pm

i am using wradlib for reading data

import wradlib as wrl
import warnings
from mpl_toolkits.basemap import Basemap
warnings.filterwarnings(“ignore”)
import matplotlib.pyplot as plt
import numpy as np
import xradar as xd
import datatree as xt
import xarray as xr
import os
import cartopy.crs as ccrs
try:
get_ipython().run_line_magic(“matplotlib inline”)
except:
plt.ion()

import numpy as np
import matplotlib.pyplot as plt
import wradlib

Replace ‘your_file.nc’ with the actual file path

file_path = “D:\ASWIN NSA\PROJECT\TERLS\B_3-9\RCTLS_03DEC2023_001449_L2B_STD.nc”

Read the NetCDF file

data = wradlib.io.read_generic_netcdf(file_path)
data
print(“Available variables:”, list(data.keys()))

LINK FOR NC FILE AND CODING WHICH I DONE CHECK ON IT
BELOW RADAR PROPERTIES

mgrover1 · February 9, 2024, 8:50pm

I would suggest following the workflow outlined in the wradlib documentation, specifically the section where they talk about georeferencing the data

https://docs.wradlib.org/en/stable/notebooks/basics/wradlib_workflow.html#Georeferencing-and-Projection

aswin · February 10, 2024, 4:56am

Okay let me try it. Thank you for the help

syedhamidali · February 14, 2024, 3:59pm

You may want to explore the following Notebooks where we have demonstrated handling TERLS data.

syedhamidali · February 14, 2024, 7:16pm

And once you have a Cf/Radial file, you can get the lats and lons:

radar = pyart.io.read_cfradial("CFRADIAL/RCTLS_03DEC2023_001206_L2B_STD.nc")
lat, lon, alt = radar.get_gate_lat_lon_alt(sweep=0)

aswin · February 15, 2024, 3:16am

Thanks bro i got my lat,lon.

def read_terls(file=None, outdir=None):
‘’‘TERLS Mosdac’‘’
radar = pyart.io.read_cfradial(file)
# Just open as simple xarray.Dataset, not decoding times
vol = xr.open_dataset(file, decode_times=False)
# 1./2. fix time unit and time_coverage_start
start_time = “”.join(vol.time_coverage_start.astype(str).values)
start_time = datetime.strptime(start_time, “%Y-%m-%dT%H:%M:%SZ”)
vol[“time_coverage_start”] = start_time
# time-units is wrong: “seconds since yyyy-mm-ddThh:mm:ssZ”
vol[“time”].attrs[“units”] = f"seconds since {start_time}"
radar.time[‘units’] = f"seconds since {start_time}"
# now we can decode time (!)
vol = xr.decode_cf(vol)
ele = sorted(list(set(vol.elevation.values) ^ {0}))
vele = vol.elevation
sweep_start_ray_index = [vele.where(vele==el).argmin(“time”).values.item() for el in ele]
sweep_end_ray_index = [vol.dims[“time”] -
vele.where(vele==el)[::-1].argmin(“time”).values.item() for el in ele]
# vol[“sweep_start_ray_index”].values = sweep_start_ray_index
# vol[“sweep_end_ray_index”].values = sweep_end_ray_index
radar.sweep_start_ray_index[‘data’] = np.ma.masked_array(sweep_start_ray_index)
radar.sweep_end_ray_index[‘data’] = np.ma.masked_array(sweep_end_ray_index)
if outdir is None:
outdir = “CFRADIAL”
os.makedirs(outdir, exist_ok=True)
outfile = os.path.join(outdir, os.path.basename(file))
pyart.io.write_cfradial(outfile, radar=radar)
print(f"Cfrad saved as {outfile}")
return None

" can i add WIDTH variable to create CF radial file along with that varaible"

syedhamidali · February 15, 2024, 4:29am

What do you mean by width variable? Spectrum Width?

aswin · February 15, 2024, 6:55am

YES,Data variable name is ‘WIDTH’ and its standard name is ‘doppler_spectrum_width’ in that nc file

syedhamidali · February 15, 2024, 6:25pm

There is already a variable “WIDTH” in your data. Again, once you have the Cf/Radial files, you can use pyart to check your fields,

radar = pyart.io.read_cfradial("CFRADIAL/RCTLS_03DEC2023_001206_L2B_STD.nc")
lat, lon, alt = radar.get_gate_lat_lon_alt(sweep=0)
print(radar.fields.keys())

Also, check the following ERAD2022 Radar course, there are a lot of notebooks, that should give you enough information to deal with the radar data.
https://openradarscience.org/erad2022/notebooks/pyart/pyart-basics.html

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(**check reply section )I want to derive the latitude and longitude from the given dimension which is time:3960 the concept of time is 360 azimuth and ele:11 the range is: 1600

Replace ‘your_file.nc’ with the actual file path

Read the NetCDF file

Related Topics