Date of Original Version
The deep ocean is severely undersampled. Whereas shipboard measurements provide irregular spatial and temporal records, moored records establish deep ocean high-resolution time series, but only at limited locations. Here, highlights and challenges of measuring abyssal temperature and salinity on the Kuroshio Extension Observatory (KEO) mooring (32.3°N, 144.6°E) from 2013 to 2019 are described. Using alternating SeaBird 37-SMP instruments on annual deployments, an apparent fresh drift of 0.03–0.06 psu was observed, with each newly deployed sensor returning to historical norms near 34.685 psu. Recurrent salinity discontinuities were pronounced between the termination of each deployment and the initiation of the next, yet consistent pre- and postdeployment calibrations suggested the freshening was “real.” Because abyssal salinities do not vary by 0.03–0.06 psu between deployment locations, the contradictory salinities during mooring overlap pointed toward a sensor issue that self-corrects prior to postcalibration. A persistent nepheloid layer, unique to KEO and characterized by murky, sediment-filled water, is likely responsible for sediment accretion in the conductivity cell. As sediment (or biofouling) increasingly clogs the instrument, salinity drifts toward a fresh bias. During ascent, the cell is flushed, clearing the clogged instrument. In contrast to salinity, deep ocean temperatures appear to increase from 2013 to 2017 by 0.0059°C, whereas a comparison with historical deep temperature measurements does not support a secular temperature increase in the region. It is suggested that decadal or interannual variability associated with the Kuroshio Extension may have an imprint on deep temperatures. Recommendations are discussed for future abyssal temperature and salinity measurements.
Anderson, N. D., K. A. Donohue, M. C. Honda, M. F. Cronin, and D. Zhang, 2020: Challenges of Measuring Abyssal Temperature and Salinity at the Kuroshio Extension Observatory. J. Atmos. Oceanic Technol., 37, 1999–2014, https://doi.org/10.1175/JTECH-D-19-0153.1.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.