Coral‐Based Sea Surface Salinity Reconstructions and the Role of Observational Uncertainties in Inferred Variability and Trends

Abstract

Climate observations in much of the tropical oceans are scarce during most of the 20th century, so paleoclimate proxies are needed to understand the full range of natural climate variability. Past proxy studies have focused primarily on sea surface temperatures, but there are comparatively few salinity reconstructions. Such reconstructions can extend our understanding of hydroclimate across the tropical oceans, including variability in precipitation, evaporation, and ocean circulation. Here we compile a network of salinity‐sensitive coral δ18O records, then apply a reduced‐space method based on empirical orthogonal function analysis to reconstruct annual tropical salinity anomalies over the 20th century. A comparison of surface salinity data sets, including reanalyzes (SODA2/3, Ocean ReAnalysis System 5 (ORAS5), Global Ocean Data Assimilation System) and objective analyses (Institute of Atmospheric Physics (IAP), EN4, Delcroix), show large discrepancies in the spatial structure, temporal evolution, and importance of the leading modes of variability. Two salinity data sets, IAP and ORAS5, are retained for climate reconstruction. Our coral‐based salinity reconstructions reveal significant long‐term trends over the 20th century, which are likely associated with hydrological cycle intensification and possibly a weakening of the Walker Circulation. These reconstructions also capture the spatial and temporal patterns of salinity anomalies associated with the El Niño‐Southern Oscillation, Interdecadal Pacific Oscillation, and Atlantic Multidecadal Oscillation. Ultimately, this approach can enhance our understanding of tropical hydroclimate prior to the observational era.

Natural and Anthropogenic Climate Variability Signals in a 237‐Year‐Long Coral Record From the Philippines

“…Reed et al. (2022) found large discrepancies in the spatial structure and temporal evolution of SSS between surface salinity data sets. Although SSS records by the Institute of Atmospheric Physics (IAP) are likely to be suitable for coral proxy applications based on Reed et al.…”

Machine Learning Solutions to Regional Surface Ocean δ18O‐Salinity Relationships for Paleoclimatic Reconstruction

“…The linear relationships defined in this work can aid in reconstruction of salinity from proxy δ 18 O and δ 18 O sw records. Additionally, coral δ 18 O forward modeling, which uses observational δ 18 O sw and SST to predict "pseudocoral" time series, requires both regional δ 18 O sw data and the locally calibrated slope value to predict the δ 18 O sw contribution to coral δ 18 O records (Reed et al, 2022;Thompson et al, 2011Thompson et al, , 2022. In this way, the regional slope indicates whether the coral record should be interpreted as largely responding to δ 18 O sw (salinity) or to SST, and the pseudocorals are highly sensitive to changes in this slope (Thompson et al, 2022).…”

“…Stable oxygen isotope (δ 18 O) values of fossil marine carbonates are widely used to understand past climate and ocean variability, including changes in sea surface temperature and salinity on interannual to million‐year timescales (e.g., Abram et al., 2020; Chen et al., 2018; Gorman et al., 2012; Grothe et al., 2020; Holbourn et al., 2021; Reed et al., 2022). These δ 18 O values are primarily a function of ocean temperature and the stable oxygen isotope composition of seawater (δ 18 O sw ) during formation (Epstein et al., 1953), with a smaller contribution from seawater pH (Krief et al., 2010; Robbins et al., 2017; Spiro et al., 1997).…”

Equatorial Undercurrent Influence on Surface Seawater δ18O Values in the Galápagos

“…Seawater δ 18 O (hereafter δ 18 O sw ) values also preserve information about precipitation and evaporation over the ocean, which assert a large control on mixed layer δ 18 O sw values. As such, δ 18 O sw values have a strong, linear relationship with salinity, given that freshwater fluxes influence both variables in a similar manner (Conroy et al., 2017; Reed et al., 2022; Thompson et al., 2022). However, δ 18 O sw values reflect more than salinity, as precipitation δ 18 O values vary spatially and temporally, and because atmospheric conditions alter the degree of isotope fractionation during evaporation (Craig & Gordon, 1965).…”