Dataset: Remotely-generated submesoscale coherent vortices (SCV) within Argo profiles

ValidatedFinal no updates expectedDOI: 10.26008/1912/bco-dmo.836648.1Version 1 (2021-01-15)Dataset Type:Other Field Results

Principal Investigator: Daniele Bianchi (University of California-Los Angeles)

Co-Principal Investigator: Daniel McCoy (University of California-Los Angeles)

Co-Principal Investigator: Andrew L. Stewart (University of California-Los Angeles)

BCO-DMO Data Manager: Shannon Rauch (Woods Hole Oceanographic Institution)

Project: CAREER: Multiple Scales of Nitrogen Cycle in Oxygen Minimum Zones (Multiple Scales of Nitrogen Cycle in the Ocean)

Project: Collaborative Research: Understanding the distribution and biogeochemical role of anaerobic microenvironments in the ocean (Ocean Particles and Microenvironments)

Abstract

Remotely-generated submesoscale coherent vortices (SCV) within Argo profiles. The data reveal the date, locations, and identification information of Argo profiles that pierced spicy-core (anomalously warm and salty) and minty-core (anomalously cold and fresh) SCVs. We also include statistics gathered for each SCV, such as core water mass characteristics and height/length scales. These data are described in McCoy et al. (2020); doi: 10.1016/j.pocean.2020.102452

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Final results for submesoscale coherent vortices (SCVs) detected in McCoy et al. (2020).

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Related Publications

Results
McCoy, D., Bianchi, D., & Stewart, A. L. (2020). Global observations of submesoscale coherent vortices in the ocean. Progress in Oceanography, 189, 102452. doi:10.1016/j.pocean.2020.102452
Software
McCoy, D. (2020). DcCoy/ArgoSCVs: Finalized matlab scripts for Argo-based SCV detection (Version v1.3) [Computer software]. Zenodo. https://doi.org/10.5281/ZENODO.4037179

Bianchi, D., McCoy, D., Stewart, A. L. (2021) Remotely-generated submesoscale coherent vortices (SCV) within Argo profiles. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2021-01-15 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.836648.1 [access date]

Terms of Use

This dataset is licensed under Creative Commons Attribution 4.0.


If you wish to use this dataset, it is highly recommended that you contact the original principal investigators (PI). Should the relevant PI be unavailable, please contact BCO-DMO (info@bco-dmo.org) for additional guidance. For general guidance please see the BCO-DMO Terms of Use document.

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Funded by the U.S. National Science Foundation