Search for: All records

SUMMARY Fossil corals are commonly used to reconstruct Last Interglacial (∼125 ka, LIG) sea level. Sea level reconstructions assume the water depth at which the coral lived, called the ‘relative water depth’. However, relative water depth varies in time and space due to coral reef growth in response to relative sea level (RSL) changes. RSL changes can also erode coral reefs, exposing older reef surfaces with different relative water depths. We use a simplified numerical model of coral evolution to investigate how sea level history systematically influences the preservation of corals in the Bahamas and western Australia, regions which house >100 LIG coral fossils. We construct global ice histories spanning the uncertainty of LIG global mean sea level (GMSL) and predict RSL with a glacial isostatic adjustment model. We then simulate coral evolution since 132 ka. We show that preserved elevations and relative water depths of modelled LIG corals are sensitive to the magnitude, timing and number of GMSL highstand(s). In our simulations, the influence of coral growth and erosion (i.e. the ‘growth effect’) can have an impact on RSL reconstructions that is comparable to glacial isostatic adjustment. Thus, without explicitly accounting for the growth effect, additional uncertainty is introduced into sea level reconstructions. Our results suggest the growth effect is most pronounced in western Australia due to Holocene erosion, but also plays a role in the Bahamas, where LIG RSL rose rapidly due to the collapsing peripheral bulge associated with Laurentide Ice Sheet retreat. Despite the coral model's simplicity, our study highlights the utility of process-based RSL reconstructions. 

ABSTRACT The 11-yr solar cycle is associated with a roughly 1 W m⁻²trough-to-peak variation in total solar irradiance and is expected to produce a global temperature response. The sensitivity of this response is, however, contentious. Empirical best estimates of global surface temperature sensitivity to solar forcing range from 0.08 to 0.18 K (W m⁻²)⁻¹. In comparison, best estimates from general circulation models forced by solar variability range between 0.03 and 0.07 K (W m⁻²)⁻¹, prompting speculation that physical mechanisms not included in general circulation models may amplify responses to solar variability. Using a lagged multiple linear regression method, we find a sensitivity of global-average surface temperature ranging between 0.02 and 0.09 K (W m⁻²)⁻¹, depending on which predictor and temperature datasets are used. On the basis of likelihood maximization, we give a best estimate of the sensitivity to solar variability of 0.05 K (W m⁻²)⁻¹(0.03–0.09 K; 95% confidence interval). Furthermore, through updating a widely used compositing approach to incorporate recent observations, we revise prior global temperature sensitivity best estimates of 0.12–0.18 K (W m⁻²)⁻¹downward to 0.07–0.10 K (W m⁻²)⁻¹. The finding of a most likely global temperature response of 0.05 K (W m⁻²)⁻¹supports a relatively modest role for solar cycle variability in driving global surface temperature variations over the twentieth century and removes the need to invoke processes that amplify the response relative to that exhibited in general circulation models.