Optimizing sampling strategies in high-resolution paleoclimate records

Abstract

Abstract. The aim of paleoclimate studies resolving climate variability from noisy proxy records can in essence be reduced to a statistical problem. The challenge is to extract meaningful information about climate variability from these records by reducing measurement uncertainty through combining measurements for proxies while retaining the temporal resolution needed to assess the timing and duration of variations in climate parameters. In this study, we explore the limits of this compromise by testing different methods for combining proxy data (smoothing, binning, and sample size optimization) on a particularly challenging paleoclimate problem: resolving seasonal variability in stable isotope records. We test and evaluate the effects of changes in the seasonal temperature and the hydrological cycle as well as changes in the accretion rate of the archive and parameters such as sampling resolution and age model uncertainty in the reliability of seasonality reconstructions based on clumped and oxygen isotope analyses in 33 real and virtual datasets. Our results show that strategic combinations of clumped isotope analyses can significantly improve the accuracy of seasonality reconstructions compared to conventional stable oxygen isotope analyses, especially in settings in which the isotopic composition of the water is poorly constrained. Smoothing data using a moving average often leads to an apparent dampening of the seasonal cycle, significantly reducing the accuracy of reconstructions. A statistical sample size optimization protocol yields more precise results than smoothing. However, the most accurate results are obtained through monthly binning of proxy data, especially in cases in which growth rate or water composition cycles obscure the seasonal temperature cycle. Our analysis of a wide range of natural situations reveals that the effect of temperature seasonality on oxygen isotope records almost invariably exceeds that of changes in water composition. Thus, in most cases, oxygen isotope records allow reliable identification of growth seasonality as a basis for age modeling in the absence of independent chronological markers in the record. These specific findings allow us to formulate general recommendations for sampling and combining data in paleoclimate research and have implications beyond the reconstruction of seasonality. We briefly discuss the implications of our results for solving common problems in paleoclimatology and stratigraphy.

What we talk about when we talk about seasonality – A transdisciplinary review

“…This includes both sampling resolution (i.e., the amount of time integrated in a single sample and spacing between them) and temporal resolution of the tested profile (often the archaeological record). West et al [604] comprehensively summarize the current state of sclerochronology, with emphasis on archaeological applications, [608] focuses on optimising sampling strategies. Here, we take a focused approach to the role of marine records in reconstructing past climatological patterns and seasonality.…”

“…Growth pauses (hiatuses) might also occur. Proxy variation may result from seasonal variability associated with SST changes [116,608] or because of other, less predictable stresses [8,339]. An example of these complexities relates to isotopic analyses of the infaunal mangrove bivalve Geloina expansa, a common component of archaeological assemblages across the Indo-West Pacific.…”

“…Obstacles for retrieving seasonality include (among others) limited temporal resolution and lacking reproducibility [608]. Frequently, standard methods (e.g., periodograms) must be adapted before they can be used to extract seasonality from irregularly sampled time series [387].…”

Amplified seasonality in western Europe in a warmer world

“…S20 to S32). The fact that these 3-monthly bins do not always line up with the minima and maxima in the stable oxygen isotope profiles through the shells shows that the common assumption that these extreme stable oxygen isotope values represent summer and winter seasons does not always hold true [see ( 76 )]. Mean seasonal Δ 47 values were obtained through weighted averages of seasonal means and uncertainties considering uncertainty within and variability between specimens.…”

Ultradian rhythms in shell composition of photosymbiotic and non-photosymbiotic mollusks

“…important information about climate and ambient water chemistry on the seasonal scale. Thereby, reconstructions from mollusk shells are highly complementary to other, less highly resolved but longer-term, climate and environmental reconstructions like sedimentary records, tree rings and ice cores (Black, 2009;Bougeois et al, 2014;Petersen et al, 2016;Tierney et al, 2020;de Winter et al, 2021b).…”