DataSheet_1_Citizen scientists’ dive computers resolve seasonal and interannual temperature variations in the Red Sea.docx

• Main Authors: Celia Marlowe, Kieran Hyder, Martin D. J. Sayer, Jan Kaiser
• Format: Dataset
• Language: unknown
• Published: 2022
• Subjects: Oceanography; Marine Biology; Marine Geoscience; Biological Oceanography; Chemical Oceanography; Physical Oceanography; Marine Engineering; citizen science; dive computer; sea temperature; Red Sea; satellite; in situ comparison; Sea ice
• Online Access: https://doi.org/10.3389/fmars.2022.976771.s001; https://figshare.com/articles/dataset/DataSheet_1_Citizen_scientists_dive_computers_resolve_seasonal_and_interannual_temperature_variations_in_the_Red_Sea_docx/21226652

Dive computers have the potential to provide depth resolved temperature data that is often lacking especially in close to shore, but spatiotemporal assessment of the robustness of this citizen science approach has not been done. In this study, we provide this assessment for the Red Sea, one of the most dived areas in the world. A comparison was conducted between 17 years of minimum water temperatures collected from SCUBA dive computers in the northern Red Sea (23–30° N, 32–39.4° E), satellite-derived sea surface temperatures from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) optimal interpolation product, and depth-banded monthly mean in-situ temperature from the TEMPERSEA dataset, which incorporates data originating from several in-situ recording platforms (including Argo floats, ships and gliders). We show that dive computer temperature data clearly resolve seasonal patterns, which are in good agreement in both phase and amplitude with OSTIA and TEMPERSEA. On average, dive computer temperatures had an overall negative bias of (–0.5 ± 1.1) °C compared with OSTIA and (–0.2 ± 1.4) °C compared with TEMPERSEA. As may be expected, increased depth-related biases were found to be associated with stratified periods and shallower mixed layer depths, i.e., stronger vertical temperature gradients. A south-north temperature gradient consistent with values reported in the literature was also identifiable. Bias remains consistent even when subsampling just 1% of the total 9310 dive computer datapoints. We conclude that dive computers offer potential as an alternative source of depth-resolved temperatures to complement existing in situ and satellite SST data sources.