Lake Superior inorganic carbon cycling reconstruction 2019-2023

Sandborn, Daniel E
Minor, Elizabeth C
Austin, Jay A
2025-04-14
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https://hdl.handle.net/11299/271198
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2019-01-01
2023-12-31

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Title

Lake Superior inorganic carbon cycling reconstruction 2019-2023

Published Date

2025-04-14

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University of Minnesota Duluth, Large Lakes Observatory

Author Contact

Sandborn, Daniel
sandb425@umn.edu

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Abstract

A gap-filling reconstruction of Lake Superior pCO2 was trained on underway observations utilizing machine learning regression. The output fields in this repository accompany the publication "A neural network-based estimate of the seasonal to inter-annual variability of the Lake Superior carbon cycle" by Sandborn et al. (in review).

Description

Three files are included in this repository: 1) regression_output.nc A netCDF-4 file containing daily mean pCO2 and CO2 air-lake flux fields produced by this work, describing Lake Superior with a spatial resolution of 0.02 degrees over 2019-2023. 2) winter_mooring.csv Data from a mooring deployment in Lake Superior in 2022-2023. This data was used for validation of the reconstruction output. 3) bottles.csv Results of chemical analyses of water samples from Lake Superior. This data was used for validation of the reconstruction output.

Referenced by

Sandborn, D.E.; Minor, E.C.; Austin, J.A. "A neural network-based estimate of the seasonal to inter-annual variability of the Lake Superior carbon cycle". Journal of Geophysical Research: Biogeosciences. In Review.

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Attribution 4.0 International
 http://creativecommons.org/licenses/by/4.0/

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Data Repository for U of M (DRUM)

Funding information

NSF: OCE-PO-1829895

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Sandborn, Daniel E; Minor, Elizabeth C; Austin, Jay A. (2025). Lake Superior inorganic carbon cycling reconstruction 2019-2023. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://hdl.handle.net/11299/271198.

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README.txt
(3.28 KB)

regression_output.nc
(3.82 GB)

bottles.csv
(6.64 KB)

winter_mooring.csv
(1.26 MB)

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