• DOI:10.3389/fmars.2021.617691
• Corpus ID: 232144841

Divers as Citizen Scientists: Response Time, Accuracy and Precision of Water Temperature Measurement Using Dive Computers

@inproceedings{Marlowe2021DiversAC,
  title={Divers as Citizen Scientists: Response Time, Accuracy and Precision of Water Temperature Measurement Using Dive Computers},
  author={Celia Marlowe and Kieran Hyder and Martin D J Sayer and Jan Kaiser},
  booktitle={Frontiers in Marine Science},
  year={2021}
}

• Celia Marlowe, K. Hyder, +1 author J. Kaiser
• Published in Frontiers in Marine Science 9 March 2021
• Environmental Science

There is a lack of depth-resolved temperature data, especially in coastal areas, which are often commonly dived by SCUBA divers. Many case studies have demonstrated that citizen science can provide high quality data, although users require more confidence in the accuracy of these data. This study examined the response time, accuracy and precision of water temperature measurement in 28 dive computers plus three underwater cameras, from 12 models. A total of 239 temperature response times (τ) were collected from 29 devices over 11 chamber dives. Mean τ by device ranged from (17 ± 6) to (341 ± 69) s, with significant between-model differences found for τ across all models. Clear differences were found in τ by pressure sensor location and material, but not by size. Two models had comparable τ to designed-for-purpose aquatic temperature loggers. 337 mean data points were collected from equilibrated temperatures in hyperbaric chamber (n = 185) and sea (n = 152) dives, compared with baseline mean temperature from Castaway CTDs over the same time period. Mean bias, defined as mean device temperature minus baseline temperature, by model ranged from (0.0 ± 0.5) to (−1.4 ± 2.1) °C and by device from (0.0 ± 0.6) to (−3.4 ± 1.0) °C. Nine of the twelve models were found to have “good” accuracy (≤0.5 °C) overall. Irrespective of model, the overall mean bias of (−0.2 ± 1.1) °C is comparable with existing commonly used coastal temperature data sets, and within global ocean observing system accuracy requirements for in situ temperature. Our research shows that the quality of temperature data in dive computers could be improved, but, with collection of appropriate metadata to allow assessment of data quality, some models of dive computers have a role in future oceanographic monitoring.