Estimation of sedimentary proxy records together with associated uncertainty

Abstract

Abstract. Sedimentary proxy records constitute a significant portion of the recorded evidence that allows us to investigate paleoclimatic conditions and variability. However, uncertainties in the dating of proxy archives limit our ability to fix the timing of past events and interpret proxy record intercomparisons. While there are various age-modeling approaches to improve the estimation of the age-depth relations of archives, relatively little focus has been placed on the propagation of the age (and radiocarbon calibration) uncertainties into the final proxy record.We present a generic Bayesian framework to estimate proxy records along with their associated uncertainty, starting with the radiometric age-depth and proxy-depth measurements, and a radiometric calibration curve if required. We provide analytical expressions for the posterior proxy probability distributions at any given calendar age, from which the expected proxy values and their uncertainty can be estimated. We illustrate our method using two synthetic data sets and then use it to construct the proxy records for groundwater inflow and surface erosion from Lonar lake in central India.Our analysis reveals interrelations between the uncertainty of the proxy record over time and the variance of proxies along the depth of the archive. For the Lonar lake proxies, we show that, rather than the age uncertainties, it is the proxy variance combined with calibration uncertainty that accounts for most of the final uncertainty. We represent the proxy records as probability distributions on a precise, error-free timescale that makes further time series analyses and intercomparisons of proxies relatively simple and clear. Our approach provides a coherent understanding of age uncertainties within sedimentary proxy records that involve radiometric dating. It can be potentially used within existing age modeling structures to bring forth a reliable and consistent framework for proxy record estimation.

Simple noise estimates and pseudoproxies for the last 21 000 years

“…Such correlations between locations are probably relevant for some noise terms while they are probably less important for others. We focused on the time series approach and did not choose a probabilistic approach like, for example, Breitenbach et al (2012) or Goswami et al (2014). Neither does our approach as of now explicitly link to probabilistic age modelling approaches as described by Haslett and Parnell (2008), Blaauw and Christen (2011), or Trachsel and Telford (2017).…”

“…There are a number of approaches to transfer the dating uncertainty towards the proxy record error (e.g. Breitenbach et al, 2012;Goswami et al, 2014;Boers et al, 2017). Ensemble and Bayesian age-depth modelling approaches also allow us to infer an additional error term (e.g.…”

“…Breitenbach et al, 2012;Carré et al, 2012;Anchukaitis and Tierney, 2013;Comboul et al, 2014;Goswami et al, 2014;Brierley and Rehfeld, 2014;Rehfeld and Kurths, 2014;Kopp et al, 2016;Boers et al, 2017) of which a number try to transfer the dating uncertainty towards the proxy record uncertainty (e.g. Breitenbach et al, 2012;Goswami et al, 2014;Boers et al, 2017). Our interest explicitly is to include the uncertainty from the dating in a statistical noise term for a pseudoproxy time series.…”

Simple noise estimates and pseudoproxies for the last 21k years

“…There are a number of approaches to transfer the dating uncertainty towards the proxy-record-uncertainty (e.g., Breitenbach et al, 2012;Goswami et al, 2014;Boers et al, 2017). We want to capture the error in a time-series.…”

Correction to Figure 2C

“…The 14 C series of the Suigetsu sediments, shown here in Fig. 5a, has been used as a comparison curve to fit radiometrically dated archives -such as speleothem data (Hoffmann et al, 2010;Southon et al, 2012) -onto the Suigetsu varve chronology. As done in the previous section for NGRIP, we represent in Fig.…”