This is a toolbox to perform quality checks on ground-based microwave radiometer (MWR) observations. Generally speaking this code provides an additional flagging of biased MWR brightness temperature (TB) data during and after rain events.
The additional flag and a status flag for the radome hygroscopic properties is added to the data. The radome status flag can help find the optimal time to replace the radome.
This toolset is compatible with the HDCP2 SAMD data format and the E-PROFILE data format. It is also functional with the standard RPG (HATPRO) data format, however this is not recommended. The RPG spectral retrieval (SPC) is currently required.
The code has been tested with python 3.6 and above and on Unix based machines. However, you will find it easy to integrate into your pipeline.
The following packages are required:
numpy, xarray, collections, datetime, glob, typing, shutil, re, os, sys, matplotlib, json
Take a look into the example in ./envVars/rao_mwr02/.
For each instrument you would like to check, please copy
env_vars_general.json to ./envVars/<station>/ and define
all the variables listed in the example.
The output will then be saved in the folder structure you
define.
"format" can be "e-profile", "", or undefined.
Put your environment-variable-json-files in a folder with the same name as your station (which you can choose freely.).
The variable "timePeriodUpdate" can be set to "lastXDays", with X replaced by an integer. OR by a time period similar to ["2022-01-31", "2022-12-31"]. In this way you can process a larger dataset or run a cron job to give you a regular update.
In order to run call
python3 -m MWR_radome <station>
in case of the given example
python3 -m MWR_radome rao_mwr02