Contextualizing time-series data: quantification of short-term regional variability in the San Pedro Channel using high-resolution in situ glider data

Teel, Elizabeth N.; Liu, Xiao; Seegers, Bridget N.; Ragan, Matthew A.; Haskell, William Z.; Jones, Burton H.; Levine, Naomi M.

doi:https://doi.org/10.5194/bg-15-6151-2018

Articles | Volume 15, issue 20

https://doi.org/10.5194/bg-15-6151-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-15-6151-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 20

Research article

|

19 Oct 2018

Research article |

| 19 Oct 2018

Contextualizing time-series data: quantification of short-term regional variability in the San Pedro Channel using high-resolution in situ glider data

Elizabeth N. Teel, Xiao Liu, Bridget N. Seegers, Matthew A. Ragan, William Z. Haskell, Burton H. Jones, and Naomi M. Levine

Supplement

https://doi.org/10.5194/bg-15-6151-2018-supplement

Data sets

Collaborative Research: Use of Triple Oxygen Isotopes and O2/Ar to constrain Net/Gross Oxygen Production during upwelling and non-upwelling periods in a Coastal Setting BCO-DMO http://bco-dmo.org/project/675313

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Short summary

Time-series sites have been instrumental in providing insight into how the ocean functions. However, to extrapolate the results from a single site to a larger region, the dynamics at the site must be placed into the context of regional-scale dynamics. We develop a framework for determining the spatial domain of a time-series site using high-resolution data. This framework quantifies the representativeness of the site and can be used to improve sampling to better capture the dynamics at the site.