wradlib: An Open Source Library for Weather Radar Data Processing¶
Release: | 1.2.0 |
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Date: | 2018-10-31 |
notebooks: | 5d89883 |
docs: | a645fac |
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 \(\omega radlib\).
- Installation
- User Guide
- Tutorials and Examples
- An incomplete introduction to python
- Getting started with wradlib
- wradlib in an hour
- Data Input - Data Output
- Attenuation correction
- Beam Blockage Calculation usingDEM
- Clutter and Echo Classification
- Georeferencing
- Match spaceborn SR (GPM/TRRM) with ground radarsGR
- Data Interpolation
- Adjusting rainfall estimates by raingauges
- Verification for precipitationestimates
- Recipes
- RADOLAN Composite
- Zonal Statistics
- Library Reference
- Gage adjustment
- Attenuation Correction
- Hydrometeor Classification (HMC)
- Clutter Identification
- Composition
- Dual-Pol and Differential Phase
- Georeferencing
- Raw Data I/O
- Interpolation
- Data Quality
- Data Transformation
- Utility functions
- Verification
- Visualisation
- Vertical Profile of Reflectivity (VPR)
- Zonal Statistics
- Z-R Conversions
- Developer Guide
- Bibliography
- Release Notes