pyiwr#

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pyiwr#

pyiwr is an advanced open-source library developed by researchers at the SIGMA Research Lab at IIT Indore. This powerful tool is designed to effortlessly read, analyze, and visualize Indian Doppler Weather Radar (DWR) data. pyiwr also provides a range of useful tools and visualization functions to facilitate Gridding data for Constant Altitude Plan Position Indicator (CAPPI), Radar Reflectivity correction, Radar Quantitative Precipitation estimation (QPE) using Polarimetric products, Radar Reflectivity Contour Frequency by Altitude Diagram and Time Series Analysis both spatially and at a given location. In addition, for further information, please consult the documentation available at https://nitigsingh.github.io/pyiwr.

Features#

  • Converts raw Indian Doppler Weather Radar (DWR) data files into radar/gridded objects NetCDF files.

  • Restructure and format correct the DWR NetCDF files with missing data moments and attributes.

  • Converts radial sweeps format data into cartesian gridded data NetCDF files.

  • Capable of merging multiple sweep files into a single volumetric CFradial file, with the facility of saving the files into gridded or CFradial format data after format correction.

  • Provides convenient tools for data processing and analysis.

  • Offers visualization functions for better understanding and interpretation of radar data.

Installation#

pyiwr can be installed as:

conda create -n pyiwr python=3.9 jupyter git -c conda-forge
conda activate pyiwr
pip install git+https://github.com/nitigsingh/pyiwr.git

Note:#

As an active project, pyiwr seeks contributions from the research community, making it a dynamic and collaborative toolkit for weather radar research and applications. Future work includes implementing advanced data processing algorithms like quality control, precipitation type classifications and radar Quantitative Precipitation Estimation (QPE) etc.