Dataset: Inter-comparison 2016: MicroCAT CTD temperature salinity
Data Citation:
Shangguan, Q., DeGrandpre, M., Martz, T. R. (2022) Temperature and salinity by a MicroCAT CTD during an inter-comparison of autonomous in situ instruments for ocean CO2 measurements under laboratory-controlled conditions at Scripps Institution of Oceanography in 2016. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-03-01 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.870412.1 [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.
DOI:10.26008/1912/bco-dmo.870412.1
Temporal Extent: 2016-08-16 - 2016-08-27
Project:
A new tool for ocean carbon cycle and ocean acidification studies
(Bermuda Biochem Timeseries)
Principal Investigator:
Michael DeGrandpre (University of Montana)
Co-Principal Investigator:
Todd R. Martz (University of California-San Diego, UCSD-SIO)
Student:
Qipei Shangguan (University of Montana)
Contact:
Qipei Shangguan (University of Montana)
BCO-DMO Data Manager:
Amber D. York (Woods Hole Oceanographic Institution, WHOI BCO-DMO)
Version:
1
Version Date:
2022-03-01
Restricted:
No
Validated:
Yes
Current State:
Final no updates expected
Temperature and salinity by a MicroCAT CTD during an inter-comparison of autonomous in situ instruments for ocean CO2 measurements under laboratory-controlled conditions at Scripps Institution of Oceanography in 2016
Abstract:
This dataset contains temperature and salinity by a MicroCAT CTD at a 15-min frequency. These data were part of an inter-comparison of autonomous in situ instruments for ocean CO2 measurements under laboratory-controlled conditions at Scripps Institution of Oceanography in August of 2016. These data were published in Shangguan et al. (2022).