Gridded oceanographic data-based tridacnine oxygen isotope thermometers: advantages and problems
- Keywords:
- Tridacna, oxygen isotopes, sea surface temperature, salinity, Ryukyu Islands, Okinoerabu Jima, Ishigaki Jima, gridded data, in situ monitoring data
Tridacnine oxygen isotope thermometers (TOITs) commonly utilize gridded sea surface temperature (SST) and sea surface salinity (SSS) data without carefully checking whether they were appropriate substitutes for in situ monitoring records at the tridacnine growth site. Many SST and SSS datasets are available, but those best suited for establishing TOITs have yet to be examined sufficiently. In this study, we have established TOITs for shells collected at two islands (Okinoerabu Jima in the north and Ishigaki Jima in the south) in the northwestern Pacific using six combinations of SST (Extended Reconstructed Sea Surface Temperature [ERSST], Sea Surface Temperature data of Integrated Global Ocean Services System [IGOSS SST], and Hadley Centre Sea Ice and Sea Surface Temperature dataset [HadISST]) and SSS (Simple Ocean Data Assimilation ocean/sea ice reanalysis [SODA3.15.2] and Met Office Hadley Centre “EN” series [EN4.2.2]) datasets and evaluated the differences among the TOITs. Consequently, the slopes and intercepts of all TOITs fell within or near the range of TOITs reported in previous studies, regardless of the combination of datasets. However, a significant difference in the coldest month SST at Okinoerabu Jima (~1.0 °C) exists between IGOSS SST and ERSST, caused by that an SST drop by the southward migration of the Kuroshio Front during winter is detected not in IGOSS SST (1° gridded data) but in ERSST (2° gridded data). Thus, the choice of SST dataset can lead to up to 1.0 °C difference in reconstructed winter SST. SSS differences exist between SODA SSS and EN SSS around the two islands up to 0.8 (equivalent to ~0.25 ‰ in oxygen isotope composition of seawater), practically leading to insignificant variations of the slopes and intercepts of the TOITs. To establish TOITs using the gridded SST and SSS datasets, we should select datasets with SSTs and SSSs similar to those at the growth sites of the studied tridacnine shells. Even if a gridded SST (SSS) dataset and an in situ monitoring SST (SSS) record show good correspondence, it could be a coincidence. We propose an averaged Ryukyu TOIT: SST = −3.95 ± 1.02× (δ18Oshell [VPDB] − δ18Osw [VSMOW]) + 20.50 ± 2.75 (2σ).