Difference between revisions of "Csu radartools tutorial"
From Lrose Wiki
| Line 22: | Line 22: | ||
---- | ---- | ||
| − | The Example file is from the C-band polarimetric SEA-POL radar. The raw data are in sigmet native format: | + | The Example file is from the C-band polarimetric SEA-POL radar. The raw data are in sigmet native format:</br> |
SEA20190917_073004 | SEA20190917_073004 | ||
| + | </br> | ||
| + | *First convert the data to cfradial data to be more easily transferable to other programs.</br> | ||
| − | + | <code>RadxConvert -f SEA20190917_073004 -outdir .</code></br> | |
| − | + | This will put the output in a directory for the date at the current level (‘.’).</br> | |
| − | |||
| − | This will put the output in a directory for the date at the current level (‘.’). | ||
Now we have a file called: | Now we have a file called: | ||
| − | cfrad.20190917_073005.718_to_20190917_073349.992_SEAPOL_v1_PISTON_RMAP_SUR.nc | + | cfrad.20190917_073005.718_to_20190917_073349.992_SEAPOL_v1_PISTON_RMAP_SUR.nc</br> |
There are a lot of variables in this file, but the ones of interest are: | There are a lot of variables in this file, but the ones of interest are: | ||
| Line 43: | Line 43: | ||
PHIDP: Differential phase | PHIDP: Differential phase | ||
SNR: Signal to noise ratio | SNR: Signal to noise ratio | ||
| − | + | </br> | |
| − | + | *Next do some quality control using PyART and CSU_Radartools.</br> | |
<code lang="python" line> | <code lang="python" line> | ||
Revision as of 15:10, 3 August 2021
Contents
Overview
This tutorial will walk through the steps to read and convert a raw radar file, quality control the data (removing unwanted artifacts and echoes, unfold radial velocity and calculate Kdp), then grid the data, and finally process the gridded data to end up with hydrometeor identification, precipitation rates, and DSD information. This is generally focused on surface polarimetric X, C, or S-band radar. We will apply a series of corrections
- Unfold radial velocity
- Calculate Kdp
- Apply thresholds to remove non-meteorological data
- Calculate the attenuation and differential attenuation
- Despeckle and remove 2nd trip
Modules available from GitHub
Scientific Background
Step-by-step Instructions
The Example file is from the C-band polarimetric SEA-POL radar. The raw data are in sigmet native format:
SEA20190917_073004
- First convert the data to cfradial data to be more easily transferable to other programs.
RadxConvert -f SEA20190917_073004 -outdir .
This will put the output in a directory for the date at the current level (‘.’).
Now we have a file called:
cfrad.20190917_073005.718_to_20190917_073349.992_SEAPOL_v1_PISTON_RMAP_SUR.nc
There are a lot of variables in this file, but the ones of interest are:
DBZ: Reflectivity
ZDR: Differential Reflectivity’
UNKNOWN_ID_82: Correlation Coefficient
VEL: Radial velocity
SQI: Signal Quality Index
PHIDP: Differential phase
SNR: Signal to noise ratio
- Next do some quality control using PyART and CSU_Radartools.
import numpy as np
from copy import deepcopy
import pyart
from CSU_RadarTools.csu_radartools import csu_kdp
from CSU_RadarTools.csu_radartools import csu_misc
%matplotlib inline