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Observation and Forecast","monthly_downloads":131,"total_dependent_repos":2,"total_dependent_packages":0,"readme":"# Note that pull requests should target the dev branch!\n**Master branch**\n\n[![Test pyrad](https://github.com/MeteoSwiss/pyrad/actions/workflows/pyrad_tests_base.yml/badge.svg)](https://github.com/MeteoSwiss/pyrad/actions/workflows/pyrad_tests.yml)\n[![Test pyrad](https://github.com/MeteoSwiss/pyrad/actions/workflows/pyrad_tests_mch.yml/badge.svg)](https://github.com/MeteoSwiss/pyrad/actions/workflows/pyrad_tests_arm.yml)\n[![build-deploy-site](https://github.com/MeteoSwiss/pyrad/actions/workflows/build_docs.yml/badge.svg)](https://github.com/MeteoSwiss/pyrad/actions/workflows/build_docs.yml)\n\n**Dev branch**\n\n[![Test pyrad base dev](https://github.com/MeteoSwiss/pyrad/actions/workflows/pyrad_tests_base_dev.yml/badge.svg?branch=dev)](https://github.com/MeteoSwiss/pyrad/actions/workflows/pyrad_tests_base_dev.yml)\n[![Test pyrad mch dev](https://github.com/MeteoSwiss/pyrad/actions/workflows/pyrad_tests_mch_dev.yml/badge.svg?branch=dev)](https://github.com/MeteoSwiss/pyrad/actions/workflows/pyrad_tests_mch_dev.yml)\n\n\n---\n\n[![Ref doc](https://img.shields.io/badge/docs-users-4088b8.svg)](https://meteoswiss.github.io/pyrad/)\n\n\n![version](https://img.shields.io/badge/python-3.8-blue.svg)\n![version](https://img.shields.io/badge/python-3.9-blue.svg)\n![version](https://img.shields.io/badge/python-3.10-blue.svg)\n![version](https://img.shields.io/badge/python-3.11-blue.svg)\n\n[![Anaconda-Server Badge](https://anaconda.org/conda-forge/pyrad_mch/badges/version.svg)](https://anaconda.org/conda-forge/pyrad_mch)\n[![Anaconda-Server Badge](https://anaconda.org/conda-forge/pyrad_mch/badges/latest_release_date.svg)](https://anaconda.org/conda-forge/pyrad_mch)\n[![Anaconda-Server Badge](https://anaconda.org/conda-forge/pyrad_mch/badges/downloads.svg)](https://anaconda.org/conda-forge/pyrad_mch)\n\n[![Anaconda-Server Badge](https://anaconda.org/conda-forge/pyrad_mch/badges/platforms.svg)](https://anaconda.org/conda-forge/pyrad_mch)\n[![Anaconda-Server Badge](https://anaconda.org/conda-forge/pyrad_mch/badges/license.svg)](https://anaconda.org/conda-forge/pyrad_mch)\n\n# pyrad\nPython Radar Data Processing\n\n# What is Pyrad?\nPyrad is a real-time data processing framework developed by MeteoSwiss and MeteoFrance. The framework is\naimed at processing and visualizing polar data from individual weather radars as well as composite\nCartesian products both off-line and in real time. It is written in the Python language. The\nframework is version controlled and automatic documentation is generated based on doc-strings.\nIt is capable of ingesting data from all the weather radars in Switzerland, namely the operational\nMeteoSwiss C-band rad4alp radar network, the MeteoSwiss X-band DX50 radar and the EPFL MXPol radar\nand radar data in the OPERA file format. Additionally, it can ingest C/FRadial and NEXRAD level 2 files.\n\nThe processing flow is controlled by 3 simple configuration files. Multiple levels of processing can\nbe performed. At each level new datasets (e.g. attenuation corrected reflectivity) are created which\ncan be stored in a file and/or used in the next processing level (for example, creating a rainfall rate\ndataset from the corrected reflectivity). Multiple products can be generated from each dataset (e.g.\nPPI, RHI images, histograms, etc.). In the off-line mode, data from multiple radars can be ingested\nin order to obtain products such as the inter-comparison of reflectivity values at co-located range\ngates.\n\nThe framework is able to ingest polarimetric and Doppler radar moments as well as auxiliary data\nsuch as numerical weather prediction parameters (e.g. temperature, wind speed, etc.), DEM-based\nvisibility and data used in the generation of the products such as rain gauge measurements,\ndisdrometer measurements, solar flux, etc. It can as well work with I/Q data, spectral data and Cartesian\ndata.\n\nThe signal processing and part of the data visualization is performed by a [MeteoSwiss developed version of the Py-ART radar toolkit](https://github.com/meteoswiss-mdr/pyart) which contains enhanced features. MeteoSwiss regularly contributes back to the [main Py-ART branch](https://github.com/ARM-DOE/pyart) once a new functionality has been thoroughly tested and it is considered of interest for the broad weather radar community.\n\nThe processing framework has multiple and expanding capabilities, include various forms of echo classification and\nfiltering, differential phase and specific differential phase estimation, attenuation correction, data\nquality monitoring, multiple rainfall rate algorithms, etc. In addition time series of data in points,\nregions or trajectories of interest can be extracted and comparisons can be performed with other\nsensors. This is particularly useful when performing measurement campaigns where remote\nsensing retrievals are validated with in-situ airplane or ground-based measurements.\n\n# Cloning from github\nMake sure to also get the submodules by running\n\n```\n    git clone --recursive https://github.com/MeteoSwiss/pyrad.git\n```\n\n# Installation with conda\nTo install from the conda repositories simply run\n\n```\n    conda install -c conda-forge pyart_mch\n    conda install -c conda-forge pyrad_mch\n```\nNote that you can also install *arm_pyart* instead of *pyart_mch*, which will use the [official Py-ART](https://github.com/ARM-DOE/pyart), but some functionalities of pyrad will be missing!\n\n# Installation\nTo install Pyrad and its submodules please have a look at the [Pyrad user manual (pdf)](./additional_doc/pyrad_user_manual.pdf).\n\n# Use\nBefore using it have a look at the [cookbook (pdf)](./additional_doc/pyrad-framework-cookbook/DataProcessing.pdf).\n\nFor details on the implemented functions and a list of all pyrad features please check the [pyrad library reference for users](https://meteoswiss.github.io/pyrad/). \n\nExample configuration files can be found in the repository directory [pyrad/config/processing/](./config/processing) and in the dedicated [examples repository](https://github.com/MeteoSwiss/pyrad-examples). \n\nTo use Pyrad for data quality monitoring check the report [pyrad_monitoring_fvj.pdf](./additional_doc/pyrad_monitoring_fvj.pdf).\n\n# Learning pyrad\n\nPlease also check the course that the pyrad team gave at the ASEAN-WMO 2024 workshop: https://github.com/openradar/asean2024-pyrad-course.\nIt includes a list of 10 configuration files and their descriptions, that encompasses a large number of possible use cases.\n\n# Newsletter\n\nIf you would like to be informed about the addition of major features in Pyrad as well as the release of new Pyrad versions, you can subscribe to our [mailing list](https://github.us1.list-manage.com/subscribe?u=2e8561343b026dacadbc70c92\u0026id=9a43ddb927), where we will periodically publish a newsletter. Note that we do not sell, communicate or divulgate your email address to anyone, and you can unsubscribe at any time via a link provided in every newsletter.\n\n# Development\nWe welcome contributions, suggestions of developments and bug reports.\n\nSuggestions of developments and bug reports should use the [Issues page of the github repository](https://github.com/meteoswiss-mdr/pyrad/issues).\n\nThe process to contribute by partners external to MeteoSwiss is described in the [user manual](./additional_doc/pyrad_user_manual.pdf).\n\n# Citation\nThe core of Pyrad is based on Py-ART. Py-ART was originally developed in the context of the [ARM Research Facility](https://www.arm.gov/). If you use Pyrad for your work, please cite BOTH Py-ART and Pyrad papers in your paper:\n\nJ.J. Helmus, S.M. Collis, (2016). The Python ARM Radar Toolkit (Py-ART), a Library for Working with Weather Radar Data in the Python Programming Language. Journal of Open Research Software. 4(1), p.e25. DOI: http://doi.org/10.5334/jors.119\n\nJ. Figueras i Ventura, M. Lainer, Z. Schauwecker, J. Grazioli, U. Germann, (2020). Pyrad: A Real-Time Weather Radar Data Processing Framework Based on Py-ART. Journal of Open Research Software, 8(1), p.28. DOI: http://doi.org/10.5334/jors.330 \n\n# Disclaimer\nThe software is still in a development stage. Please let us know if you would like to test it.\n\nMeteoSwiss cannot be held responsible for errors in the code or problems that could arise from its use.\n\n","funding_links":[],"readme_doi_urls":["http://doi.org/10.5334/jors.119","http://doi.org/10.5334/jors.330"],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["closember","weather-radars","pyart","radar-processing","weather","kd-tree","resampling"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/324916","html_url":"https://ost.ecosyste.ms/projects/324916"}