VAPOR
VAPOR is the Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 4 DOI reference(s) in README -
✓Academic publication links
Links to: mdpi.com, zenodo.org -
✓Committers with academic emails
13 of 25 committers (52.0%) from academic institutions -
✓Institutional organization owner
Organization ncar has institutional domain (ncar.ucar.edu) -
○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (16.2%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
VAPOR is the Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers
Basic Info
- Host: GitHub
- Owner: NCAR
- License: bsd-3-clause
- Language: C++
- Default Branch: main
- Homepage: https://www.vapor.ucar.edu/
- Size: 77.4 MB
Statistics
- Stars: 190
- Watchers: 18
- Forks: 50
- Open Issues: 358
- Releases: 48
Topics
Metadata Files
README.md
Vapor:
VAPOR is the Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers. VAPOR provides an interactive 3D visualization environment that can also produce animations and still frame images. VAPOR runs on most UNIX and Windows systems equipped with modern 3D graphics cards.
The VAPOR Data Collection (VDC) data model allows users progressively access the fidelity of their data, allowing for the visualization of terascale data sets on commodity hardware. VAPOR can also directly import data formats including WRF, MOM, POP, ROMS, and some GRIB and NetCDF files.
Users can perform ad-hoc analysis with VAPOR's interactive Python interpreter; which allows for the creation, modification, and visualization of new variables based on input model data.
VAPOR is a product of the NSF National Center for Atmospheric Research's Computational and Information Systems Lab. Support for VAPOR is provided by the U.S. National Science Foundation (grants # 03-25934 and 09-06379, ACI-14-40412), and by the Korea Institute of Science and Technology Information
Project homepage and binary releases can be found at https://www.vapor.ucar.edu/
Citation
If VAPOR benefits your research, please kindly cite this publication:
@Article{atmos10090488,
AUTHOR = {Li, Shaomeng and Jaroszynski, Stanislaw and Pearse, Scott and Orf, Leigh and Clyne, John},
TITLE = {VAPOR: A Visualization Package Tailored to Analyze Simulation Data in Earth System Science},
JOURNAL = {Atmosphere},
VOLUME = {10},
YEAR = {2019},
NUMBER = {9},
ARTICLE-NUMBER = {488},
URL = {https://www.mdpi.com/2073-4433/10/9/488},
ISSN = {2073-4433},
ABSTRACT = {Visualization is an essential tool for analysis of data and communication of findings in the sciences, and the Earth System Sciences (ESS) are no exception. However, within ESS, specialized visualization requirements and data models, particularly for those data arising from numerical models, often make general purpose visualization packages difficult, if not impossible, to use effectively. This paper presents VAPOR: a domain-specific visualization package that targets the specialized needs of ESS modelers, particularly those working in research settings where highly-interactive exploratory visualization is beneficial. We specifically describe VAPOR’s ability to handle ESS simulation data from a wide variety of numerical models, as well as a multi-resolution representation that enables interactive visualization on very large data while using only commodity computing resources. We also describe VAPOR’s visualization capabilities, paying particular attention to features for geo-referenced data and advanced rendering algorithms suitable for time-varying, 3D data. Finally, we illustrate VAPOR’s utility in the study of a numerically- simulated tornado. Our results demonstrate both ease-of-use and the rich capabilities of VAPOR in such a use case.},
DOI = {10.3390/atmos10090488}
}
Project Members:
- Nihanth Cherukuru
- John Clyne
- Scott Pearse
- Samuel Li
- Stanislaw Jaroszynski
- Kenny Gruchalla
- Niklas Roeber
- Pamela Gillman

Owner
- Name: NSF National Center for Atmospheric Research
- Login: NCAR
- Kind: organization
- Location: Boulder, CO
- Website: http://ncar.ucar.edu
- Repositories: 934
- Profile: https://github.com/NCAR
NSF NCAR is sponsored by the U.S. National Science Foundation and managed by the University Corporation for Atmospheric Research.
GitHub Events
Total
- Create event: 87
- Release event: 36
- Issues event: 138
- Watch event: 14
- Delete event: 51
- Issue comment event: 65
- Push event: 242
- Pull request review comment event: 53
- Pull request event: 83
- Pull request review event: 81
- Fork event: 1
Last Year
- Create event: 87
- Release event: 36
- Issues event: 138
- Watch event: 14
- Delete event: 51
- Issue comment event: 65
- Push event: 242
- Pull request review comment event: 53
- Pull request event: 83
- Pull request review event: 81
- Fork event: 1
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Scott Pearse | p****e@u****u | 1,123 |
| Stanislaw Jaroszynski | s****j@u****u | 1,058 |
| Samuel Li | s****g@u****u | 1,018 |
| John Clyne | c****e@u****u | 446 |
| Ian Franda | 1****a | 11 |
| Stanislaw Jaroszynski | S****i | 7 |
| U-CISL-MADISON\stasj-admin | C****n@C****u | 5 |
| Nihanth Wagmi Cherukuru | n****u@u****u | 3 |
| dependabot[bot] | 4****] | 2 |
| Stas | s****s@c****u | 2 |
| Samuel Li | s****g@c****u | 2 |
| Rémi Lacroix | r****x@i****r | 1 |
| John Clyne | c****e@c****u | 1 |
| Legacy Code | v****r@u****u | 1 |
| Samuel Li | S****m@N****a | 1 |
| Samuel Li | s****g@c****r | 1 |
| Stas | s****s@S****n | 1 |
| U-CIT\pearse | p****e@c****u | 1 |
| pavolklacansky | k****y@s****u | 1 |
| Orion Poplawski | o****n@n****m | 1 |
| Orhan Eroglu | 3****n | 1 |
| Kevin Hallock | k****k | 1 |
| Joel Daves | j****s@u****u | 1 |
| Giovanni Rosa | g****3@y****m | 1 |
| CoreCode | c****e | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 2,380
- Total pull requests: 1,424
- Average time to close issues: 8 months
- Average time to close pull requests: 6 days
- Total issue authors: 55
- Total pull request authors: 16
- Average comments per issue: 1.25
- Average comments per pull request: 1.04
- Merged pull requests: 1,285
- Bot issues: 0
- Bot pull requests: 4
Past Year
- Issues: 67
- Pull requests: 95
- Average time to close issues: 21 days
- Average time to close pull requests: 5 days
- Issue authors: 5
- Pull request authors: 5
- Average comments per issue: 0.37
- Average comments per pull request: 0.53
- Merged pull requests: 74
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- sgpearse (635)
- StasJ (574)
- shaomeng (541)
- clyne (456)
- jvalan (36)
- NihanthCW (32)
- leighorf (12)
- hawbecker (9)
- ifranda (9)
- Padanian (6)
- winash12 (6)
- MattRehme (4)
- ogressel (3)
- MarkUoLeeds (2)
- robsopuh87 (2)
Pull Request Authors
- sgpearse (490)
- StasJ (463)
- clyne (253)
- shaomeng (216)
- ifranda (23)
- NihanthCW (4)
- dependabot[bot] (4)
- ghost (4)
- ayenpure (2)
- core-code (1)
- khallock (1)
- erogluorhan (1)
- RemiLacroix-IDRIS (1)
- klacansky (1)
- opoplawski (1)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- centos 7.4.1708 build
- ubuntu 18.04 build
- cppyy *
- ipython *
- jupyter *
- matplotlib *
- scipy *
- xarray *