A depth‐derived Pleistocene age model: Uncertainty estimates, sedimentation variability, and nonlinear climate change

Abstract

The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters [1] A new chronology of glaciation, spanning the last 780,000 years, is estimated from 21 marine sediment cores using depth as a proxy for time. To avoid biasing this ''depth-derived'' age estimate, the depth scale is first corrected for the effects of sediment compaction. To provide age uncertainty estimates, the spatial and temporal variability of marine sediment accumulation rates are estimated and modeled as an autocorrelated stochastic process. Depth-derived ages are estimated to be accurate to within ±9000 years, and within this uncertainty are consistent with the orbitally tuned age estimates. Nonetheless, the remaining differences between the depth and orbitally tuned chronologies produce important differences in the spectral domain. From the d 18 O record, using the depth-derived ages, we infer that there are weak nonlinearities involving the 100 kyr and obliquity frequency bands which generate interaction bands at sum and difference frequencies. If an orbitally tuned age model is instead applied, these interactions are suppressed, with the system appearing more nearly linear.

The Role of Oceans and Sea Ice in Abrupt Transitions between Multiple Climate States

“…The shift from the Last Glacial Maximum to present climate is estimated at 58C (Braconnot et al 2007) and major changes in sea ice extent (de Vernal and Hillaire-Marcel 2000). Glacial cycles, like our simulations, are paced by well-defined oscillatory radiative drivers (e.g., Roe 2006;Huybers 2011), although Milankovich forcing primarily affects seasonal and meridional distribution of insolation rather than global annual-mean S 0 . In both cases the response to the forcing is nonlinear.…”

Links between annual, Milankovitch and continuum temperature variability

“…Uncertainties directly influencing the shape of the spectra include rectification and aliasing 29 -potentially first order effects, considering that most proxies are affected by but do not resolve the annual variability. Spectral estimates are also subject to errors or assumptions built into the age model 30 . All records use their published age models except for ODP677 and ODP927 where a depth-derived age-model 30 is used, not making orbital assumptions.…”

The middle Pleistocene transition: characteristics, mechanisms, and implications for long-term changes in atmospheric pCO2

“…The first has to do with age models, with the convention being to tune a d 18 O record to orbital parameters (Imbrie et al, 1984;Shackleton et al, 1990), thus introducing a potential systematic bias in the distribution of spectral power for a given climate record. Huybers and Wunsch (2004) have developed new strategies for constructing age models independent of such tuning procedures, but nearly all of the records evaluated herein are based on orbitally tuned age models, and the potential bias in spectral power must be kept in mind. The second caveat has to do with interpreting phase relations between d 18 O b and other proxies measured in the same core.…”