skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language

Abstract

The Python ARM Radar Toolkit is a package for reading, visualizing, correcting and analysing data from weather radars. Development began to meet the needs of the Atmospheric Radiation Measurement Climate Research Facility and has since expanded to provide a general-purpose framework for working with data from weather radars in the Python programming language. The toolkit is built on top of libraries in the Scientific Python ecosystem including NumPy, SciPy, and matplotlib, and makes use of Cython for interfacing with existing radar libraries written in C and to speed up computationally demanding algorithms. As a result, the source code for the toolkit is available on GitHub and is distributed under a BSD license.

Authors:
 [1];  [1]
  1. Argonne National Lab. (ANL), Argonne, IL (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
Argonne National Laboratory; USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1339572
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Journal of Open Research Software
Additional Journal Information:
Journal Volume: 4; Journal ID: ISSN 2049-9647
Publisher:
Software Sustainability Institute
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; doppler velocity; Python; radar; weather; weather radar

Citation Formats

Helmus, Jonathan J., and Collis, Scott M. The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language. United States: N. p., 2016. Web. doi:10.5334/jors.119.
Helmus, Jonathan J., & Collis, Scott M. The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language. United States. doi:10.5334/jors.119.
Helmus, Jonathan J., and Collis, Scott M. Mon . "The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language". United States. doi:10.5334/jors.119. https://www.osti.gov/servlets/purl/1339572.
@article{osti_1339572,
title = {The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language},
author = {Helmus, Jonathan J. and Collis, Scott M.},
abstractNote = {The Python ARM Radar Toolkit is a package for reading, visualizing, correcting and analysing data from weather radars. Development began to meet the needs of the Atmospheric Radiation Measurement Climate Research Facility and has since expanded to provide a general-purpose framework for working with data from weather radars in the Python programming language. The toolkit is built on top of libraries in the Scientific Python ecosystem including NumPy, SciPy, and matplotlib, and makes use of Cython for interfacing with existing radar libraries written in C and to speed up computationally demanding algorithms. As a result, the source code for the toolkit is available on GitHub and is distributed under a BSD license.},
doi = {10.5334/jors.119},
journal = {Journal of Open Research Software},
issn = {2049-9647},
number = ,
volume = 4,
place = {United States},
year = {2016},
month = {7}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Save / Share:

Works referenced in this record:

The Atmospheric Radiation Measurement Program
journal, January 2003

  • Ackerman, Thomas P.; Stokes, Gerald M.
  • Physics Today, Vol. 56, Issue 1
  • DOI: 10.1063/1.1554135

The Arm Climate Research Facility: A Review of Structure and Capabilities
journal, March 2013

  • Mather, James H.; Voyles, Jimmy W.
  • Bulletin of the American Meteorological Society, Vol. 94, Issue 3
  • DOI: 10.1175/BAMS-D-11-00218.1

A Real-Time Four-Dimensional Doppler Dealiasing Scheme
journal, October 2001


Fast two-dimensional phase-unwrapping algorithm based on sorting by reliability following a noncontinuous path
journal, January 2002

  • Herráez, Miguel Arevallilo; Burton, David R.; Lalor, Michael J.
  • Applied Optics, Vol. 41, Issue 35
  • DOI: 10.1364/AO.41.007437

Polarimetric Attenuation Correction in Heavy Rain at C Band
journal, January 2011

  • Gu, Ji-Young; Ryzhkov, A.; Zhang, P.
  • Journal of Applied Meteorology and Climatology, Vol. 50, Issue 1
  • DOI: 10.1175/2010JAMC2258.1

An Application of Linear Programming to Polarimetric Radar Differential Phase Processing
journal, August 2013

  • Giangrande, Scott E.; McGraw, Robert; Lei, Lei
  • Journal of Atmospheric and Oceanic Technology, Vol. 30, Issue 8
  • DOI: 10.1175/JTECH-D-12-00147.1

An Operational Objective Analysis System
journal, October 1959


A Technique for Maximizing Details in Numerical Weather Map Analysis
journal, August 1964


Python for Scientific Computing
journal, January 2007


Matplotlib: A 2D Graphics Environment
journal, January 2007


The Emergence of Open-Source Software for the Weather Radar Community
journal, January 2015

  • Heistermann, M.; Collis, S.; Dixon, M. J.
  • Bulletin of the American Meteorological Society, Vol. 96, Issue 1
  • DOI: 10.1175/BAMS-D-13-00240.1

F2PY: a tool for connecting Fortran and Python programs
journal, January 2009

  • Peterson, Pearu
  • International Journal of Computational Science and Engineering, Vol. 4, Issue 4
  • DOI: 10.1504/IJCSE.2009.029165

On Polarimetric Radar Signatures of Deep Convection for Model Evaluation: Columns of Specific Differential Phase Observed during MC3E*
journal, February 2016

  • van Lier-Walqui, Marcus; Fridlind, Ann M.; Ackerman, Andrew S.
  • Monthly Weather Review, Vol. 144, Issue 2
  • DOI: 10.1175/MWR-D-15-0100.1

Technical Note: An open source library for processing weather radar data ( wradlib )
journal, January 2013

  • Heistermann, M.; Jacobi, S.; Pfaff, T.
  • Hydrology and Earth System Sciences, Vol. 17, Issue 2
  • DOI: 10.5194/hess-17-863-2013

An Open Virtual Machine for Cross-Platform Weather Radar Science
journal, October 2015

  • Heistermann, M.; Collis, S.; Dixon, M. J.
  • Bulletin of the American Meteorological Society, Vol. 96, Issue 10
  • DOI: 10.1175/BAMS-D-14-00220.1

    Works referencing / citing this record:

    An Inverse Model for Raindrop Size Distribution Retrieval with Polarimetric Variables
    journal, July 2018

    • Wen, Guang; Chen, Haonan; Zhang, Guifu
    • Remote Sensing, Vol. 10, Issue 8
    • DOI: 10.3390/rs10081179

    Mobile ground‐based SMART radar observations and wind retrievals during the landfall of Hurricane Harvey (2017)
    journal, September 2019

    • Alford, A. Addison; Biggerstaff, Michael I.; Carrie, Gordon D.
    • Geoscience Data Journal, Vol. 6, Issue 2
    • DOI: 10.1002/gdj3.82

    Automated detection of bird roosts using NEXRAD radar data and Convolutional Neural Networks
    journal, July 2018

    • Chilson, Carmen; Avery, Katherine; McGovern, Amy
    • Remote Sensing in Ecology and Conservation, Vol. 5, Issue 1
    • DOI: 10.1002/rse2.92

    Analysis of two derecho events in Southern Brazil
    journal, January 2019

    • Lima de Figueiredo, Eliton; de Lima Nascimento, Ernani; Ilha de Oliveira, Maurício
    • Meteorology and Atmospheric Physics, Vol. 131, Issue 5
    • DOI: 10.1007/s00703-018-0654-x

    Combining ASCAT and NEXRAD Retrieval Analysis to Explore Wind Features of Mesoscale Oceanic Systems
    journal, September 2018

    • Priftis, G.; Lang, T. J.; Chronis, T.
    • Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 18
    • DOI: 10.1029/2017jd028137

    Near‐Surface Maximum Winds During the Landfall of Hurricane Harvey
    journal, January 2019

    • Alford, A. Addison; Biggerstaff, Michael I.; Carrie, Gordon D.
    • Geophysical Research Letters, Vol. 46, Issue 2
    • DOI: 10.1029/2018gl080013

    Retrievals of Riming and Snow Density From Vertically Pointing Doppler Radars
    journal, December 2018

    • Mason, S. L.; Chiu, C. J.; Hogan, R. J.
    • Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 24
    • DOI: 10.1029/2018jd028603

    Variations of Thunderstorm Charge Structures in West Texas on 4 June 2012: VARIATIONS OF THUNDERSTORM CHARGING
    journal, September 2018

    • Chmielewski, Vanna C.; Bruning, Eric C.; Ancell, Brian C.
    • Journal of Geophysical Research: Atmospheres, Vol. 123, Issue 17
    • DOI: 10.1029/2018jd029006

    Inadvertent Localized Intensification of Precipitation by Aircraft
    journal, February 2019

    • Moisseev, Dmitri; Lautaportti, Susanna; Alku, Laura
    • Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 4
    • DOI: 10.1029/2018jd029449

    Midlatitude Oceanic Cloud and Precipitation Properties as Sampled by the ARM Eastern North Atlantic Observatory
    journal, April 2019

    • Giangrande, Scott E.; Wang, Die; Bartholomew, Mary Jane
    • Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 8
    • DOI: 10.1029/2018jd029667

    Strange Floods: The Upper Tail of Flood Peaks in the United States
    journal, September 2018

    • Smith, James A.; Cox, Alexander A.; Baeck, Mary Lynn
    • Water Resources Research, Vol. 54, Issue 9
    • DOI: 10.1029/2018wr022539

    Using Overshooting Top Area to Discriminate Potential for Large, Intense Tornadoes
    journal, November 2019

    • Marion, G. R.; Trapp, R. J.; Nesbitt, S. W.
    • Geophysical Research Letters, Vol. 46, Issue 21
    • DOI: 10.1029/2019gl084099

    Meteorological Aspects of Self‐Initiated Upward Lightning at the Säntis Tower (Switzerland)
    journal, December 2019

    • Pineda, Nicolau; Figueras i. Ventura, Jordi; Romero, David
    • Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 24
    • DOI: 10.1029/2019jd030834

    Sensitivity of Simulated Deep Convection to a Stochastic Ice Microphysics Framework
    journal, November 2019

    • Stanford, McKenna W.; Morrison, Hugh; Varble, Adam
    • Journal of Advances in Modeling Earth Systems, Vol. 11, Issue 11
    • DOI: 10.1029/2019ms001730

    TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting
    journal, July 2020


    Declines in an abundant aquatic insect, the burrowing mayfly, across major North American waterways
    journal, January 2020

    • Stepanian, Phillip M.; Entrekin, Sally A.; Wainwright, Charlotte E.
    • Proceedings of the National Academy of Sciences, Vol. 117, Issue 6
    • DOI: 10.1073/pnas.1913598117

    Opportunities and challenges in using weather radar for detecting and monitoring flying animals in the Southern Hemisphere: WSR Ecology in the Southern Hemisphere
    journal, September 2019

    • Rogers, Rebecca M.; Buler, Jeffrey J.; Wainwright, Charlotte E.
    • Austral Ecology, Vol. 45, Issue 1
    • DOI: 10.1111/aec.12823

    Phased-Array Radar System Simulator (PASIM): Development and Simulation Result Assessment
    journal, February 2019

    • Li, Zhe; Perera, Sudantha; Zhang, Yan
    • Remote Sensing, Vol. 11, Issue 4
    • DOI: 10.3390/rs11040422

    A Random Forest Method to Forecast Downbursts Based on Dual-Polarization Radar Signatures
    journal, April 2019

    • Medina, Bruno; Carey, Lawrence; Amiot, Corey
    • Remote Sensing, Vol. 11, Issue 7
    • DOI: 10.3390/rs11070826

    Observations of the microphysical evolution of convective clouds in the southwest of the United Kingdom
    journal, January 2018

    • Jackson, Robert; French, Jeffrey R.; Leon, David C.
    • Atmospheric Chemistry and Physics, Vol. 18, Issue 20
    • DOI: 10.5194/acp-18-15329-2018

    A 17 year climatology of the macrophysical properties of convection in Darwin
    journal, January 2018

    • Jackson, Robert C.; Collis, Scott M.; Louf, Valentin
    • Atmospheric Chemistry and Physics, Vol. 18, Issue 23
    • DOI: 10.5194/acp-18-17687-2018

    A novel approach for characterizing the variability in mass–dimension relationships: results from MC3E
    journal, January 2019

    • Finlon, Joseph A.; McFarquhar, Greg M.; Nesbitt, Stephen W.
    • Atmospheric Chemistry and Physics, Vol. 19, Issue 6
    • DOI: 10.5194/acp-19-3621-2019

    Planetary boundary layer evolution over the Amazon rainforest in episodes of deep moist convection at the Amazon Tall Tower Observatory
    journal, January 2020

    • Oliveira, Maurício I.; Acevedo, Otávio C.; Sörgel, Matthias
    • Atmospheric Chemistry and Physics, Vol. 20, Issue 1
    • DOI: 10.5194/acp-20-15-2020

    Enhancing the consistency of spaceborne and ground-based radar comparisons by using beam blockage fraction as a quality filter
    journal, January 2018

    • Crisologo, Irene; Warren, Robert A.; Mühlbauer, Kai
    • Atmospheric Measurement Techniques, Vol. 11, Issue 9
    • DOI: 10.5194/amt-11-5223-2018

    Retrieval of snowflake microphysical properties from multifrequency radar observations
    journal, January 2018

    • Leinonen, Jussi; Lebsock, Matthew D.; Tanelli, Simone
    • Atmospheric Measurement Techniques, Vol. 11, Issue 10
    • DOI: 10.5194/amt-11-5471-2018

    The NCAS mobile dual-polarisation Doppler X-band weather radar (NXPol)
    journal, January 2018

    • Neely III, Ryan R.; Bennett, Lindsay; Blyth, Alan
    • Atmospheric Measurement Techniques, Vol. 11, Issue 12
    • DOI: 10.5194/amt-11-6481-2018

    Use of polarimetric radar measurements to constrain simulated convective cell evolution: a pilot study with Lagrangian tracking
    journal, January 2019

    • Fridlind, Ann M.; van Lier-Walqui, Marcus; Collis, Scott
    • Atmospheric Measurement Techniques, Vol. 12, Issue 6
    • DOI: 10.5194/amt-12-2979-2019

    A Gaussian mixture method for specific differential phase retrieval at X-band frequency
    journal, January 2019

    • Wen, Guang; Fox, Neil I.; Market, Patrick S.
    • Atmospheric Measurement Techniques, Vol. 12, Issue 10
    • DOI: 10.5194/amt-12-5613-2019

    Pysteps: an open-source Python library for probabilistic precipitation nowcasting (v1.0)
    journal, January 2019

    • Pulkkinen, Seppo; Nerini, Daniele; Pérez Hortal, Andrés A.
    • Geoscientific Model Development, Vol. 12, Issue 10
    • DOI: 10.5194/gmd-12-4185-2019