A python toolbox for deriving rainfall information from commerical microwave link (CML) data.
pycomlink works with Python 2.7 and can be installed via pip. However, since one of its dependencies, numba is easiest to install via the Anaconda Python distribution, we recommend to install Anaconda Python first and then do
$ conda install numba
$ pip install pycomlink
To run the example notebooks you will also need the Jupyter Notebook and ipython, both also available via conda or pip.
- Jupyter notebook on how to get started with CML data from a CSV file
- More examples to come...
- Read and write the common data format
cmlh5for CML data - Quickly visualize the CML network on a dynamic map
- Perform all required CML data processing steps to derive rainfall information from raw signal levels:
- data sanity checks
- wet/dry classification
- baseline calculation
- wet antenna correction
- transformation from attenuation to rain rate
- Generate rainfall maps from the data of a CML network
- Validate you results against gridded rainfall data or rain gauges networks