Collaborators

A range of funding agencies, academic institutions, companies, and individuals contribute to Pangeo in different ways.

Funding Agencies

We are grateful to have formal funding support from several funding agencies.

EarthCube

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Pangeo currently receives support from the US NSF EarthCube Program, which funds cyberinfrastructure projects related to Earth Science. This award supports scientists and developers at Lamont Doherty Earth Observatory, National Center for Atmospheric Research, and Anaconda Inc. The public details of the awards can be found on the NSF website:

Anaconda is funded via a subaward through Columbia. We were awarded $1.2M over a three year period (Oct. 2017 - Sept. 2020).

The specific solicitation we responded to is here. Our project is technically called an “EarthCube integration.” This type of project requires a close link to “Geoscience Use Cases,” i.e. actual science applications. The need to closely intertwine the technical development and the scientific applications determined the structure of our proposal and the makeup of the team.

The proposal Project Description, entitled Pangeo: An Open Source Big Data Climate Science Platform is published under a CC BY 4.0 license on Figshare:

You may share and adapt this document as you wish, but please acknowledge the authors.

ACCESS

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Pangeo receives support from the NASA ACCESS Program, which funds projects that enhance, extend, and improve existing components of NASA’s distributed and heterogeneous data and information systems infrastructure. This award supports scientists and engineers at the University of Washington (UW), the National Center for Atmospheric Research (NCAR), Anaconda Inc., and Element 84. The public details of the awards will be published when NASA makes them available. In total, we were awarded $1.5M over a two year period (Sept. 2018 - Aug. 2020).

The specific solicitation we responded to is here.

The project’s focus will be on the development of new data discovery tools and processing of remote sensing datasets.

Sloan Foundation

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Early work on Pangeo was partly supported via the Alfred P. Sloan foundation, via a Sloan Research Fellowship in Ocean Sciences awarded to Ryan Abernathey in 2016.

Institutions

These institutions devote significant resources to the Pangeo project. We are always looking to expand this list.

Lamont Doherty Earth Observatory

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LDEO is a primary recipient of the EarthCube award. Several scientists and programmers at LDEO are active in the development of Pangeo architecture and scientific use cases.

National Center for Atmospheric Research

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NCAR is a primary recipient of the EarthCube and ACCESS awards. NCAR scientists and programmers are leading the deployment of Pangeo on NCAR’s high-performance computing systems and conducting scientific investigations using Pangeo tools.

Anaconda Inc.

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Anaconda (formerly Continuum Analytics) receives support from the EarthCube and ACCESS awards. Anaconda developers are contributing to the development of xarray, dask, and the Pangeo cloud infrastructure.

UK Met Office

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Developers at the UK Met Office Informatics Lab are contributing to the Pangeo cloud infrastructure.

The University of Washington

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UW is a primary recipient of the ACCESS award. Scientists and programmers at UW are active in the development of Pangeo cloud architecture and scientific applications.

Element84

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Element 84 is a primary recipient of the ACCESS award. Element84 developers are contributing to the development of data-discovery tools in the Pangeo ecosystem.

People

These individuals identify themselves as contributors to Pangeo. Don’t hesitate to ADD YOURSELF to the list.

Lamont-Doherty Earth Observatory physical oceanography climate
University of Washington alpine hydrology geospatial mapping remote sensing
  • Anderson Banihirwe
National Center for Atmospheric Research distributed computing climate software
Univesrsity of Miami ocean wave modelling subseasonal forecasting
  • David Blodgett
U.S. Geological Survey hydrology information modeling cyberinfrastructure geoinformatics
CSIRO/University of Western Australia physical oceanography coastal ocean modelling image analysis particle imaging velocimetry
  • Noah Brenowitz
University of Washington atmospheric science machine learning
University of Oslo climate snow hydrology energy transport cryosphere-aerosol remote sensing
University of Miami climate modeling physical oceanography
  • Spencer Clark
Princeton University atmospheric science climate
Moss Landing Marine Labs physical oceanography coasts and estuaries observations numerical modeling teaching
Lamont-Doherty Earth Observatory marine geophysics image analysis seafloor instrumentation
  • Philippe Delandmeter
Institute for Marine and Atmospheric research Utrecht, Utrecht University, Netherlands ocean numerical modelling Lagrangian modelling particle tracking finite element methods
  • Leif Denby
ICAS, University of Leeds numerical modelling atmospheric dynamics cloud computing
Massachusetts Institute of Technology physical oceanography
  • Guillaume Eynard-Bontemps
CNES, French space agency distributed computing data engineering and analysis HPC cloud computing infrastructure IT architecture
University of Washington remote sensing sensor networks data visualization cloud computing embedded hardware education and public outreach
National Center for Atmospheric Research climate hydrology water resources distributed computing
National Center for Atmospheric Research climate hydrology water resources
University of Washington remote sensing active tectonics geodesy
  • Naomi Henderson
Lamont-Doherty Earth Observatory atmospheric modeling research computing
Texas A&M University physical oceanography coastal ocean modeling
UCLA Dept. of Atmospheric & Oceanic Sciences, and Caltech Division of Geological & Planetary Sciences atmospheric dynamics climate
  • Chris Hill
Massachusetts Institute of Technology ocean modeling hpc research computing cyberinfrastructure
software algorithms
  • Damien Irving
CSIRO physical oceanography climate software carpentry
University of Colorado-Boulder / NOAA Global Systems Division HPC climate software GIS
NCAS, University of Reading climate simulation hpc data infrastructure cloud computing
  • Julien Le Sommer
Institut des Géosciences de l’Environnement physical oceanography ocean models climate
  • Chiara Lepore
Lamont-Doherty Earth Observatory hydrology
Institut des Géosciences de l’Environnement machine learning computer vision
  • Fabien Maussion
University of Innsbruck climate glaciology
University Corporation for Atmospheric Research/Unidata atmospheric science remote sensing algorithms
University of Washington Department of Atmospheric Sciences atmospheric science climate
  • Joy Monteiro
Stockholm University climate atmospheric science modeling
Memorial University of Newfoundland physical oceanography
University of Washington climate hydrology water resources
Columbia University physical oceanography climate
National Center for Atmospheric Research climate distributed computing algorithms
Met Office Informatics Lab atmospheric science distributed computing algorithms
GEOMAR Helmholtz Centre for Ocean Research Kiel physical oceanography distributed computing ocean-data management HPC
  • Colin Raymond
Columbia University climate atmospheric science modeling
Met Office Informatics Lab atmospheric science distributed computing cloud computing HPC
  • Matthew Rocklin
Anaconda Inc distributed computing algorithms
University at Albany climate atmospheric science physical oceanography modeling
Massachusetts Institute of Technology climate meteorology policy
array storage engines scientific computing infrastructure
USGS physical oceanography coastal ocean modeling geoinformatics
  • Maike Sonnewald
Massachusetts Insitute of Technology statistics modeling/HPC physical oceanography
  • Guillaume Sérazin
Laboratoire d'Étude en Géophysique et Océanographie Spatiale physical oceanography climate
University of Washington cloud computing containers water resources
Met Office Informatics Lab atmospheric science distributed computing kubernetes docker cloud computing infrastructure IT architecture
Institute for Marine and Atmospheric research Utrecht, Utrecht University, Netherlands physical oceanography climate software
University of Toronto paleoclimate HPC physical oceanography
  • Duncan Watson-Parris
University of Oxford atmospheric physics numerical modelling observations data fusion machine learning
University of Saskatchewan hydrology atmospheric science
  • Phillip Wolfram
Los Alamos National Laboratory physical oceanography modeling climate
Harvard University atmospheric chemistry numerical methods HPC