Centennial to millennial climate variability across climate states; proxy reconstructions vs. transient model simulations.

In previous model-data comparisons, the centennial to millennial scale variance of local climate (e.g., SST) reconstructed from proxies was significantly higher than that simulated by climate models. One possible explanation is the lack of long-term feedback mechanisms, e.g. from the representation of changes in ice-sheets in models. Additionally, proxy records are short, and sparse, and the climate signal is significantly modified during the processes of encoding, archiving, and recovery.

Here we introduce new methods to infer the climate variability of the past from proxy data and compare them to new transient model simulations of the last deglaciation. This will allow us to estimate the amplitude of climate variability and to evaluate whether climate models are capable of capturing changes in climate variability between different climate states (e.g. glacial vs. interglacial periods), which is also relevant for the accuracy of future projections. We compare the variability of marine d¹⁸O reconstructed from proxies with that simulated by a state-of-the-art Earth System Model.

From the proxy side, our analysis is based on a new dataset of marine oxygen isotope data from planktonic foraminifera compiled for the PALMOD project. We use new methods to first calculate power-spectra for the LGM, transition and Holocene and then to correct these spectra by fitting a Bayesian model describing the effects of bioturbation and measurement error on the reconstructed climate signal. From the model side we use marine d¹⁸O variability calculated using temperature and salinity from transient model simulations of the last deglaciation, performed within the PALMOD project, that include changes in the ice sheets.

This combination of new data and methods will allow us to investigate the effect of different ice-sheet configurations and physical parametrizations in the model on their ability to characterise long-timescale climate variability and its dependence on climate state.