Argovis welcome page

What is Argovis?

Access Argo profiles via API, or visualize temperature, salinity, and BGC data by location at argovis.colorado.edu. View float trajectory forecasts, compare gridded fields with Argovis' grid visualization module, or co-locate Argo data with weather events. Stay tuned for upcoming modules to co-locate Argo data with satellite and other Earth science datasets. For more information see the Argovis User Guide page for more information on its features and how to use it.

Objective of Argovis

Co-locate Argo and other data sets to help everyone from oceanographers to the general public study the ocean and atmosphere from their own computers. For help in using Argovis, please see our User Guide.

Please note that this site is still in active development and may have some bugs or other issues in displaying data. Please report bugs by e-mail found in the Contact section.

News and Events

14 - 16 June 2020: Argovis featured at the 2022 EarthCube Annual Meeting

2 - 4 May 2020: Argovis Hackathon (supported by EarthCube TAC)

The Argovis Team

	Donata Giglio is an Assistant Professor in the Department of Atmospheric and Oceanic Sciences at University of Colorado Boulder and is the PI of the Argovis project. Her research interests are in large scale ocean-atmosphere dynamics, geophysical fluid dynamics, data science, accessibility and visualization.
	Bill Mills is a scientific software developer based in Brooklyn, NY. They got their start developing novel reconstruction algorithms in high energy particle physics for the ATLAS experiment at the LHC, and developed web apps for the nuclear structure community for years before heading to the private sector to teach organizations how to design and operate software at scale using Docker and Kubernetes. They are currently working in Prof. Giglio's group at University of Colorado Boulder as the lead engineer on Argovis.
	Megan Scanderbeg is the Argo Program Science Coordinator and the Argo Data Management Team Co-chair. She works at Scripps Institution of Oceanography and is interested in making oceanographic data freely available and understandable for all.
	Tyler Tucker lives and works (and plays) on the Big Island of Hawaii. He is currently a scientific software engineer at the W.M. Keck Observatory on the Big Island. In 2019-2020, he worked as a Research Assistant in Professor Giglio's group at University of Colorado Boulder. Tyler started developing Argovis as part of his Master's thesis entitled “Mathematics and big data technology development to visualize, deliver and analyze IMS and ARGO data” defended in May 2018 at San Diego State University. The Argovis project started in 2017 when Tyler was an Applied Mathematics MS student at the Climate Informatics Lab, San Diego State University, supervised by Professor Samuel Shen, and working in collaboration with Donata Giglio and Megan Scanderbeg.

Collaborators on NSF project (award #2026954) to include GO-SHIP data in Argovis: Dr. Sarah Purkey, Steve Diggs, Lynne Merchant, Andrew Barna

Collaborator on NOAA project (award #NA21OAR4310261) to produce a new Argo gridded product with uncertainties and include it in Argovis: Dr. Mikael Kuusela

Other Collaborators (current and/or past): Sam Shen, Gui Castelao, Matt Mazloff, Aneesh Subramanian, Lynne Talley, Julien Pierret

Identification of Data Sources

Citation for the Argovis web application and the Argovis database:
Tucker, T., D. Giglio, M. Scanderbeg, and S.S.P. Shen: Argovis: A Web Application for Fast Delivery, Visualization, and Analysis of Argo Data. J. Atmos. Oceanic Technol., 37, 401–416, https://doi.org/10.1175/JTECH-D-19-0041.1

In addition to citing Argovis, please cite the reference for the dataset you are using. For citations on the datasets included in Argovis, see our FAQ page for more information.

Data Producer Responsibility

The developers are not responsible for the use made of the data accessible via Argovis or errors or omissions that potentially may occur in the data sets. While we aim to make accessible the most recent and up to date data, occasionally a delay in the data feed to Argovis may be experienced.

Acknowledgements

Argovis is hosted on a server of the Department of Atmospheric and Oceanic Sciences (ATOC) at the University of Colorado Boulder. Currently, Argovis is funded by the NSF Earthcube program (Award #1928305) and (Award #2026954).

In the past, Argovis has been funded by (starting with the most recent):

Giglio's research funds provided by University of Colorado Boulder
the SOCCOM Project through grant number NSF PLR-1425989
the US Argo Program through NOAA Grant NA15OAR4320071 (CIMEC) the National Oceanic and Atmospheric Administration – Cooperative Science Center for Earth System Sciences and Remote Sensing Technologies (NOAA-CREST) under the Cooperative Agreement Grant \#: NA16SEC4810008
the U.S. NOAA Cooperative Institute for Climate Science (Award No. 13342-Z7812001)
The City College of New York, NOAA-CREST program and NOAA Office of Education, Educational Partnership Program which provided full fellowship support to Tyler Tucker at San Diego State University

The initial development of Argovis referenced the codes and ideas of the 4-Dimensional Visual Delivery (4DVD) technology developed at the Climate Informatics Lab, San Diego State University. The computer code for 4DVD is at https://github.com/dafrenchyman/4dvd, and is available for download under the GNU General Public License open source license. All applicable restrictions, disclaimers of warranties, and limitations of liability in the GNU General Public License also applies to uses of 4DVD on this website.