ALBERT

Description: Holocene temperature proxy records are commonly used in quantitative synthesis and model-data comparisons. However, comparing correlations between time series from records collected in proximity to one another with the expected correlations based on climate model simulations indicates either regional or noisy climate signals in Holocene temperature proxy records. In this study, we evaluate the consistency of spatial correlations present in Holocene proxy records with those found in data from the Last Glacial Maximum (LGM). Specifically, we predict correlations expected in LGM proxy records if the only difference to Holocene correlations would be due to more time uncertainty and more climate variability in the LGM. We compare this simple prediction to the actual correlation structure in the LGM proxy records. We found that time series data of ice-core stable isotope records and planktonic foraminifera Mg/Ca ratios were consistent between the Holocene and LGM periods, while time series of Uk'37 proxy records were not as we found no correlation between nearby LGM records. Our results support the finding of highly regional or noisy marine proxy records in the compilation analysed here and suggest the need for further studies on the role of climate proxies and the processes of climate signal recording and preservation.

Description: Time series derived from paleoclimate archives are often irregularly sampled in time and thus not analysable using standard statistical methods such as correlation analyses. Although measures for the similarity between time series have been proposed for irregular time series, they do not account for the time scale dependency of the relationship. Stochastically distributed temporal sampling irregularities act qualitatively as a low-pass filter reducing the influence of fast variations from frequencies higher than about 0.5 (Δtmax) − 1, where Δtmax is the maximum time interval between observations. This may lead to overestimated correlations if the true correlation increases with time scale. Typically, correlations are underestimated due to a non-simultaneous sampling of time series. Here, we investigated different techniques to estimate time scale dependent correlations of weakly irregularly sampled time series, with a particular focus on different resampling methods and filters of varying complexity. The methods were tested on ensembles of synthetic time series that mimic the characteristics of Holocene marine sediment temperature proxy records. We found that a linear interpolation of the irregular time series onto a regular grid, followed by a simple Gaussian filter was the best approach to deal with the irregularity and account for the time scale dependence. This approach had both, minimal filter artefacts, particularly on short time scales, and a minimal loss of information due to filter length.

Description: Proxy records from climate archives provide evidence about past climate changes, but the recorded signal is affected by non-climate-related effects as well as time uncertainty. As proxy-based climate reconstructions are frequently used to test climate models and to quantitatively infer past climate, we need to improve our understanding of the proxy record signal content as well as the uncertainties involved. In this study, we empirically estimate signal-to-noise ratios (SNRs) of temperature proxy records used in global compilations of the middle to late Holocene (last 6000 years). This is achieved through a comparison of the correlation of proxy time series from nearby sites of three compilations and model time series extracted at the proxy sites from two transient climate model simulations: a Holocene simulation of the ECHAM5/MPIOM model and the Holocene part of the TraCE-21ka simulation. In all comparisons, we found the mean correlations of the proxy time series on centennial to millennial timescales to be low (R 〈 0.2), even for nearby sites, which resulted in low SNR estimates. The estimated SNRs depend on the as- sumed time uncertainty of the proxy records, the timescale analysed, and the model simulation used. Using the spatial correlation structure of the ECHAM5/MPI-OM simulation, the estimated SNRs on centennial timescales ranged from 0.05 – assuming no time uncertainty – to 0.5 for a time uncer- tainty of 400 years. On millennial timescales, the estimated SNRs were generally higher. Use of the TraCE-21ka correla- tion structure generally resulted in lower SNR estimates than for ECHAM5/MPI-OM. As the number of available high-resolution proxy records continues to grow, a more detailed analysis of the signal content of specific proxy types should become feasible in the near future. The estimated low signal content of Holocene temperature compilations should caution against over-interpretation of these multi-proxy and multisite synthe- ses until further studies are able to facilitate a better characterisation of the signal content in paleoclimate records.

Description: As the availability of high-resolution proxy records increases, the number of large-scale compilations that are built and analyzed continues to grow. Such datasets allow us to disentangle regional and global climate changes from local and proxy specific effects, to better bridge the spatial scales of local proxy recorders vs. global climate models and they support more objective statistical analyses. However, compilations also often combine data for multiple proxy types and which may record different climate variables (e.g. different seasonal or atmospheric vs. water temperatures). Datasets may also vary in quality, and compilations often ignore the expert knowledge of the authors of the original individual paleoclimate datasets as well as site-specific and proxy-specific effects. Here I review current and recent studies that have used global compilations of temperature related proxy data to infer the glacial and Holocene climate evolution and the temporal and spatial structures of climate variability. I demonstrate how the analysis of large-scale compilations can not only improve our knowledge of the evolution of past climate but also provide insight into the potential and limitations of specific paleoclimate proxies and emphasize the importance of realistic uncertainty estimates.