Beschreibung: Climate reconstructions based on proxy records recovered from marine sediments, such as alkenone records or geochemical parameters measured on foraminifera, play an important role in our understanding of the climate system. They provide information about the state of the ocean ranging back hundreds to millions of years and form the backbone of paleo-oceanography. However, there are many sources of uncertainty associated with the signal recovered from sediment archived proxies. These include seasonal or depth habitat biases in the recorded signal, a frequency dependent reduction in the amplitude of the recorded signal due to bioturbation of the sediment, aliasing of high frequency climate variation onto a nominally annual, decadal or centennial resolution signal, and additional sample processing and measurement error introduced when the proxy signal is recovered. Here we present a forward model for sediment archived proxies that jointly models the above processes, so that the magnitude of their separate and combined effects can be investigated. Applications include the interpretation and analysis of uncertainty in existing proxy records, parameter sensitivity analysis to optimize future studies, and the generation of pseudo-proxy records that can be used to test reconstruction methods. We provide examples, such as the simulation of individual foraminifera records, that demonstrate the usefulness of the forward model for paleoclimate studies. The model is implemented as a user-friendly R package, sedproxy, the use of which we hope will contribute to a better understanding of both the limitations and potential of marine sediment proxies to inform about past climate.

Beschreibung: Due to mixing processes, sediment samples taken from a single depth can contain particles (e.g. foraminifera) with a wide range of ages. When radiocarbon measurements are made on samples containing many of these individual particles, the resulting values can hide a lot of internal age variation. Furthermore, if the measured samples contain a material from only a small number of individual particles, the resulting 14C ages will be noisy estimates of the true mean age of material from that depth. Similarly, for proxies such as Mg/Ca, or d18O, the range of ages contained in a single sample results in measurements that represent average values for an extended time period. Again, these values will be noisy if the number of particles per sample is small, but even with large samples, the resulting proxy records are “smoothed out” and the reconstructed amplitude of climate transitions is reduced. The advent of ultra-small-sample 14C dating means that samples consisting of very small numbers of foraminiferal shells now can be dated. This poses both a problem, as individual 14C ages will be less representative of their layer, but also an opportunity as it allows for a direct estimate of the heterogeneity in the age of material at a given depth. We used 14C measurements on samples of 3-30 foraminifera to estimate the underlying standard deviation in the age of individuals picked from the same depth. We repeated this for cores with sedimentation rates ranging from 3-30 cm/kyr and found age-variances consistent with simple sediment mixing models and typical bioturbation depths. These direct estimates of age-variance allow for more realistic estimates of age uncertainty and have already proven useful to use in reconciling apparently inconsistent age-depth profiles from adjacent sediment cores. They also allow for a better-informed interpretation of proxy records, both in terms of the relative timing of events and in terms of the amount of amplitude reduction of the climate signal to be expected at different timescales. Knowing the length of time represented in a single sediment sample also allows us to more clearly interpret changes in the statistics of individual foraminifera variation, whether they can be interpreted as changes to the amplitude of the seasonal cycle, the strength of ENSO variations, or multidecadal climate variation.

Beschreibung: 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.

Beschreibung: Here we show how the frequency scaling of a climate reconstruction from sediment proxy records is affected by various sources of uncertainty. Specifically, analytic expressions are derived and illustrated for the power spectral density of a climate reconstruction, based on a simple model that takes into account: the spectral structure of the true climate, uneven recording throughout the year, precession-like orbital modulations of the seasonal cycle, bioturbation, sampling of a finite number of signal carriers from discontinuous slices of sediment material, uncorrelated measurement noise; and that includes the effects of spectral aliasing and leakage. The basic behaviour and the properties of the model are demonstrated, and the implications for the interpretation of climate reconstructions are discussed.

Beschreibung: The statistical properties of climate variability are often reconstructed and interpreted from single proxy records. However, variation in the proxy record is influenced by both climate and non-climate factors, and these must be understood for climate inferences to be reliable.

Beschreibung: Climate reconstructions based on proxy records recovered from marine sediments, such as alkenone records or geochemical parameters measured on foraminifera, play an important role in our understanding of the climate system. They provide information about the state of the ocean ranging back hundreds to millions of years and form the backbone of paleo-oceanography. However, there are many sources of uncertainty associated with the signal recovered from sediment-archived proxies. These include seasonal or depth-habitat biases in the recorded signal; a frequency-dependent reduction in the amplitude of the recorded signal due to bioturbation of the sediment; aliasing of high-frequency climate variation onto a nominally annual, decadal, or centennial resolution signal; and additional sample processing and measurement error introduced when the proxy signal is recovered. Here we present a forward model for sediment-archived proxies that jointly models the above processes so that the magnitude of their separate and combined effects can be investigated. Applications include the interpretation and analysis of uncertainty in existing proxy records, parameter sensitivity analysis to optimize future studies, and the generation of pseudo-proxy records that can be used to test reconstruction methods. We provide examples, such as the simulation of individual foraminifera records, that demonstrate the usefulness of the forward model for paleoclimate studies. The model is implemented as an open-source R package, sedproxy, to which we welcome collaborative contributions. We hope that use of sedproxy will contribute to a better understanding of both the limitations and potential of marine sediment proxies to inform researchers about earth's past climate.

Beschreibung: Understanding the uncertainties associated with proxy-based reconstructions of past climate is critical if they are to be used to validate climate models and contribute to a comprehensive understanding of the climate system. Here we present two related and complementary approaches to quantifying proxy uncertainty. The proxy forward model (PFM) “sedproxy” bitbucket.org/ecus/sedproxy numerically simulates the creation, archiving and observation of marine sediment archived proxies such as Mg/Ca in foraminiferal shells and the alkenone unsaturation index UK’37. It includes the effects of bioturbation, bias due to seasonality in the rate of proxy creation, aliasing of the seasonal temperature cycle into lower frequencies, and error due to cleaning, processing and measurement of samples. Numerical PFMs have the advantage of being very flexible, allowing many processes to be modelled and assessed for their importance. However, as more and more proxy-climate data become available, their use in advanced data products necessitates rapid estimates of uncertainties for both the raw reconstructions, and their smoothed/derived products, where individual measurements have been aggregated to coarser time scales or time-slices. To address this, we derive closed-form expressions for power spectral density of the various error sources. The power spectra describe both the magnitude and autocorrelation structure of the error, allowing timescale dependent proxy uncertainty to be estimated from a small number of parameters describing the nature of the proxy, and some simple assumptions about the variance of the true climate signal. We demonstrate and compare both approaches for time-series of the last millennia, Holocene, and the deglaciation. While the numerical forward model can create pseudoproxy records driven by climate model simulations, the analytical model of proxy error allows for a comprehensive exploration of parameter space and mapping of climate signal re-constructability, conditional on the climate and sampling conditions.