A python package which can read CINRAD radar data, perform calculations and visualize the data.

中文说明

Python 3.5 +

Cartopy

Metpy

Shapefile

Pyresample

You can directly install this module via

pip install cinrad

Alternatively, you can download from github page and then excecute

python setup.py install

This submodule contains data structure used in this program.

Radial type data: cinrad.datastruct.Radial

Cross-section type data: cinrad.datastruct._Slice

Grid type data: cinrad.datastruct.Grid

Decode CINRAD radar data.

Simple demonstration:

from cinrad.io import CinradReader, StandardData
f = CinradReader(your_radar_file) #Old version data
f = StandardData(your_radar_file) #New standard data
f.get_data(tilt, drange, dtype) #Get data
f.rhi(azimuth, drange) #Get range-height indicator data

f.to_nc(path_to_nc_file)

cinrad.io.PUP provides functions to decode PUP data. The extracted data can be further used to create PPI. (Only radial data are supported.)

from cinrad.io import PUP
f = PUP(your_radar_file)
data = f.get_data()

This submodule provides some useful algorithms in radar meteorology. All functions contained only accept numpy.ndarray. This submodule extends the usage of this program, as these functions can accept customized data rather than only the data decoded by cinrad.io.

For directly computation of decoded data, cinrad.easycalc provides functions that simplify the process of calculation. For functions contained in this submodule, only a list of reflectivity data is required as the argument.

Code to generate the required list:

r_list = [f.get_data(i, 230, 'REF') for i in f.angleindex_r]

cinrad.easycalc.VCS provides calculation of vertical cross-section.

Sample code

import cinrad
from cinrad.visualize import Section
f = cinrad.io.CinradReader(your_radar_file)
rl = [f.get_data(i, 230, 'REF') for i in f.angleindex_r]
vcs = cinrad.easycalc.VCS(rl)
sec = vcs.get_section(start_cart=(111, 25.5), end_cart=(112, 26.7)) # pass geographic coordinates (latitude, longitude)
sec = vcs.get_section(start_polar=(115, 350), end_polar=(130, 30)) # pass polar coordinates (distance, azimuth)
fig = Section(sec)
fig('D:\\')

Visualize the data stored in acceptable format (cinrad.datastruct). It also means that you can using customized data to construct a object belongs to one of the class in cinrad.datastruct and then perform visualization. For further information about this method, please see the examples contained in example folder.

Simple demonstration:

from cinrad.visualize import PPI
fig = PPI(R) #Plot PPI
fig('D:\\') #Pass the path to save the fig
from cinrad.visualize import Section
fig = Section(_Slice) #Plot RHI
fig('D:\\')

The path passed into the class can either be the folder path or the file path. Also, if no path is passed, the figure will be saved at the folder named PyCINRAD in the home folder (e.g. C:\Users\tom).

The summary of args that can be passed into PPI are listed as follows.

Besides args, class PPI has some other auxiliary plotting functions.

Plot range rings on the PPI plot.

Plot VCS section under the PPI plot.

This function is very similar to vcs argument of PPI, but the range of y-axis can be adjusted only by this function.

If you are interested in this program, you can join the developers of this program. Any contribution is appreciated!

If you have some questions or advise about this program, you can create a issue or email me at 274555447@qq.com.