wradlib: An Open Source Library for Weather Radar Data Processing¶
Release: | 1.1.0 |
---|---|
Date: | September 04, 2018 |
The \(\omega radlib\) project has been initiated in order facilitate the use of weather radar data as well as to provide a common platform for research on new algorithms. \(\omega radlib\) is an open source library which is well documented and easy to use. It is written in the free programming language Python.
Note
Please cite \(\omega radlib\) as Heistermann, M., Jacobi, S., and Pfaff, T.: Technical Note: An open source library for processing weather radar data (wradlib), Hydrol. Earth Syst. Sci., 17, 863-871, doi:10.5194/hess-17-863-2013, 2013
Weather radar data is potentially useful in meteorology, hydrology and risk management. Its ability to provide information on precipitation with high spatio-temporal resolution over large areas makes it an invaluable tool for short term weather forecasting or flash flood forecasting.
\(\omega radlib\) is designed to assist you in the most important steps of processing weather radar data. These may include: reading common data formats, georeferencing, converting reflectivity to rainfall intensity, identifying and correcting typical error sources (such as clutter or attenuation) and visualising the data.
This documentation is under steady development. It provides a complete library reference as well as a set of tutorials which will get you started in working with \(\omega radlib\).
- Getting Started
- Tutorials and Examples
- How to use the tutorials and examples?
- Integrated Development Environments for Python
- An incomplete introduction to Python
- Getting started with wradlib
- Data Input - Data Output
- Attenuation correction
- Beam Blockage Calculation using a DEM
- Clutter and Echo Classification
- Georeferencing
- Match spaceborn SR (GPM/TRMM) with ground radars GR
- How to use wradlib’s ipol module for interpolation tasks?
- Adjusting radar-base rainfall estimates by rain gauge observations
- Routine verification measures for radar-based precipitation estimates
- Recipes
- RADOLAN
- Zonal Statistics
- Library Reference
- Community
- For Developers
- Using Docker
- Bibliography
- Release Notes