Comparison of observed and simulated tropical climate trends using a forward model of coralδ¹⁸O

Abstract

[1] The response of the tropical Pacific Ocean to future climate change remains highly uncertain, in part because of the disagreement among observations and coupled general circulation models (CGCMs) regarding 20th-century trends. Here we use forward models of climate proxies to compare CGCM simulations and proxy observations to address 20th-century trends and assess remaining uncertainties in both proxies and models. We model coral oxygen isotopic composition (d 18 O) in a 23-site Indo-Pacific network as a linear function of sea-surface temperature (SST) and seasurface salinity (SSS) obtained from historical marine observations (instrumental data) and a multimodel ensemble of 20th-century CGCM output. When driven with instrumental data from 1958 to 1990, the forward modeled corals (pseudocorals) capture the spatial pattern and temporal evolution of the El Niño-Southern Oscillation (ENSO). Comparison of the linear trend observed in corals and instrumental pseudocorals suggests that the trend in corals between 1958 and 1990 results from both warming (60%) and freshening (40%). From 1890 to 1990, the warming/freshening trend in CGCM pseudocorals is weaker than that observed in corals. Corals display a moderate trend towards a reduced zonal SST gradient and decreased ENSO-related variance between 1895 and 1985, whereas CGCM pseudocorals display a range of trend patterns and an increase in ENSO-related variance over the same period. Differences between corals and CGCM pseudocorals may arise from uncertainties in the linear bivariate coral model, uncertainties in the way corals record climate, undersensitivity of CGCMs to radiative forcing during the 20th century, and/or biases in the simulated CGCM SSS fields.

On the utility of proxy system models for estimating climate states over the common era

“…While a number of other variables have been used to reconstruct temperature from trees (e.g., maximum latewood density), we are not aware of a publicly available forward model for these additional variables, and so do not consider them here. The coral forward model follows the parameterization described in Thompson et al [2011] and depends on both sea surface temperature and salinity anomalies; both the ice core and coral records were modeled using the water isotope-enabled model fields coupled with a synthesis of previously published models for water isotopes in high-resolution proxy data (PRYSM) [Dee et al, 2015]. The ice core model takes into account precipitation accumulation, local temperature, and incorporates dynamical information from the water isotope physics fields (d 18 O of precipitation) of SPEEDY-IER and ECHAM5-wiso.…”

Paleoclimate Data–Model Comparison and the Role of Climate Forcings over the Past 1500 Years*

“…The pseudocoral derived here differs from the bivariate pseudocorals used by Brown et al (2008) and Thompson et al (2011). Although the incorporation of the DP and DE terms into our pseudocoral only increases the fraction of ENSO variance described from 65% to 70%, this nonetheless demonstrates the potential to improve pseudocoral formulations by incorporating more complete descriptions of the physical processes that determine the evolution of coral d Figure 5 shows the record of Cobb et al (2003) and compares it with pseudocorals derived from the preindustrial control simulation and the three members of ensemble OGSV.…”

“…Based on previous studies (Brown et al 2006(Brown et al , 2008Thompson et al 2011) and physical understanding of the factors influencing coral d 18 O, we consider four model variables as being potential predictors of the simulated ENSO signal: sea surface temperature SST, sea surface salinity SSS, precipitation P, and evaporation E. The first of these variables appears directly in Eq. (1) A 1000-yr CSIRO Mk3L preindustrial control simulation is used to construct a pseudocoral from these model variables.…”

“…By examining changes in both the mean state of the central Pacific and ENSO, we will be able to use the model simulations to test the conclusion of Cobb et al (2003) that changes in O to local sea surface temperature and salinity (Thompson et al 2011) …”

“…O in terms of nonisotopic climate variables (Brown et al 2008;Thompson et al 2011). Linear regression is used to derive empirical calibrations for such models, based on either observational or climate model data.…”