MetPy A Meteorological Python Library for Data Analysis and Visualization

MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries like NumPy, SciPy, Matplotlib, and xarray. The goal of the project is to bring the weather analysis...

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Vydáno v:Bulletin of the American Meteorological Society Ročník 103; číslo 10; s. E2273 - E2284
Hlavní autoři: May, Ryan M., Goebbert, Kevin H., Thielen, Jonathan E., Leeman, John R., Camron, M. Drew, Bruick, Zachary, Bruning, Eric C., Manser, Russell P., Arms, Sean C., Marsh, Patrick T.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Boston American Meteorological Society 01.10.2022
Témata:
Algorithms
Arrays
Atmospheric sciences
Automation
Best practice
Best practices
Code reuse
Data analysis
Data models
Data science
Documentation
Interfaces
Libraries
Metadata
Meteorological data
Meteorology
Overflow
Programming languages
Python
Robustness
Software
Software development
Software development tools
Software testing
Visualization
Weather analysis
ISSN:0003-0007, 1520-0477
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Abstract MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries like NumPy, SciPy, Matplotlib, and xarray. The goal of the project is to bring the weather analysis capabilities of GEMPAK (and similar software tools) into a modern computing paradigm. MetPy strives to employ best practices in its development, including software tests, continuous integration, and automated publishing of web-based documentation. As such, MetPy represents a sustainable, long-term project that fills a need for the meteorological community. MetPy’s development is substantially driven by its user community, both through feedback on a variety of open, public forums like Stack Overflow, and through code contributions facilitated by the GitHub collaborative software development platform. MetPy has recently seen the release of version 1.0, with robust functionality for analyzing and visualizing meteorological datasets. While previous versions of MetPy have already seen extensive use, the 1.0 release represents a significant milestone in terms of completeness and a commitment to long-term support for the programming interfaces. This article provides an overview of MetPy’s suite of capabilities, including its use of labeled arrays and physical unit information as its core data model, unit-aware calculations, cross sections, skew T and GEMPAK-like plotting, station model plots, and support for parsing a variety of meteorological data formats. The general road map for future planned development for MetPy is also discussed.
AbstractList MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries like NumPy, SciPy, Matplotlib, and xarray. The goal of the project is to bring the weather analysis capabilities of GEMPAK (and similar software tools) into a modern computing paradigm. MetPy strives to employ best practices in its development, including software tests, continuous integration, and automated publishing of web-based documentation. As such, MetPy represents a sustainable, long-term project that fills a need for the meteorological community. MetPy’s development is substantially driven by its user community, both through feedback on a variety of open, public forums like Stack Overflow, and through code contributions facilitated by the GitHub collaborative software development platform. MetPy has recently seen the release of version 1.0, with robust functionality for analyzing and visualizing meteorological datasets. While previous versions of MetPy have already seen extensive use, the 1.0 release represents a significant milestone in terms of completeness and a commitment to long-term support for the programming interfaces. This article provides an overview of MetPy’s suite of capabilities, including its use of labeled arrays and physical unit information as its core data model, unit-aware calculations, cross sections, skew T and GEMPAK-like plotting, station model plots, and support for parsing a variety of meteorological data formats. The general road map for future planned development for MetPy is also discussed.
MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries like NumPy, SciPy, Matplotlib, and xarray. The goal of the project is to bring the weather analysis capabilities of GEMPAK (and similar software tools) into a modern computing paradigm. MetPy strives to employ best practices in its development, including software tests, continuous integration, and automated publishing of web-based documentation. As such, MetPy represents a sustainable, long-term project that fills a need for the meteorological community. MetPy’s development is substantially driven by its user community, both through feedback on a variety of open, public forums like Stack Overflow, and through code contributions facilitated by the GitHub collaborative software development platform. MetPy has recently seen the release of version 1.0, with robust functionality for analyzing and visualizing meteorological datasets. While previous versions of MetPy have already seen extensive use, the 1.0 release represents a significant milestone in terms of completeness and a commitment to long-term support for the programming interfaces. This article provides an overview of MetPy’s suite of capabilities, including its use of labeled arrays and physical unit information as its core data model, unit-aware calculations, cross sections, skew T and GEMPAK-like plotting, station model plots, and support for parsing a variety of meteorological data formats. The general road map for future planned development for MetPy is also discussed.
Author Marsh, Patrick T.
Leeman, John R.
Manser, Russell P.
Bruick, Zachary
Camron, M. Drew
Thielen, Jonathan E.
Bruning, Eric C.
May, Ryan M.
Goebbert, Kevin H.
Arms, Sean C.
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Cites_doi 10.25080/Majora-92bf1922-00a
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Snippet MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python...
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SubjectTerms Algorithms
Arrays
Atmospheric sciences
Automation
Best practice
Best practices
Code reuse
Data analysis
Data models
Data science
Documentation
Interfaces
Libraries
Metadata
Meteorological data
Meteorology
Overflow
Programming languages
Python
Robustness
Software
Software development
Software development tools
Software testing
Visualization
Weather analysis
Subtitle A Meteorological Python Library for Data Analysis and Visualization
Title MetPy
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