Search

Understanding the mechanisms behind any changes in the climate system often requires establishing the timing of events imprinted on the geological record. However, these proxy records are prone to large uncertainties, which may preclude meaningful conclusions about the relative timing of events. In this study, we put forth a framework to estimate the uncertainty in phase relationships inferred from marine sedimentary records. The novelty of our method lies in the accounting of the various sources of uncertainty inherent to paleoclimate reconstruction and timing analysis. Specifically, we use a Monte-Carlo process allowing sampling of possible realizations of the time series as functions of uncertainties in time, the climate proxy, and the identification of the termination timing. We then apply this technique to 15 published sea surface temperature records from the equatorial Pacific to evaluate whether we observed any significant changes in the termination timing between the East and the West. We find that the uncertainty on the relative timing estimates is on the order of several thousand years, and mainly stems from age model uncertainty (90%). However, even small differences in mean termination timings can be detected with a sufficiently large number of samples. Improvements in the dating of sediment records provide an opportunity to reduce uncertainty in studies of this kind.

The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches. ©2019. American Geophysical Union. All Rights Reserved., Code and data to reproduce the figures of this article are available on GitHub and released on Zenodo (doi:10.5281/zenodo.3165019). Definition of properties and recommendations are summarized here: http://wiki.linked.earth/PaCTS_v1.0 . This work was supported by the National Science Foundation through the EarthCube Program with Grant ICER‐1541029. Feedback solicitation on the standard was facilitated by the Past Global Changes (PAGES) organization. The 2016 workshop on Paleoclimate Data Standards was hosted by the World Data Service for Paleoclimatology (WDS/NOAA‐Paleo), and the participation of international attendees was made possible by a PAGES travel grant. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Oxygen minimum zones (OMZs), located below highly productive marine regions, are sites of microbially mediated denitrification and biogeochemical cycling that have global significance. The intensity of OMZs fluctuates naturally; however, the degree of these fluctuations and a comprehensive understanding of the factors that drive these fluctuations on decadal to centennial time scales is lacking. Our high-resolution (near-annual) record of δ15Nsed from laminated sediments at the Pescadero Slope in the Gulf of California (eastern tropical North Pacific) fluctuates between maximum values of 10.5‰ and minimum values of 8.0‰ over the past 1200 years. An analysis of the relationship between δ15NO3− and [O2] in the water column suggests that the observed range of δ15Nsed values is equivalent to an approximately 8 µM fluctuation in O2 content and that these changes can occur in less than 25 years. Our findings show that the OMZ typically intensifies quickly and contracts gradually; the average rate of OMZ intensification (−0.24 µM O2/yr) is twice as fast as the rate of OMZ reoxygenation. Spectral analyses of the δ15Nsed record and Br/Cl counts, with the latter are used as a proxy for organic carbon preservation, suggest that the Pacific Decadal Oscillation and the Suess (deVries) solar cycle (solar irradiance) may influence the intensity of the OMZ and carbon production/export during the late Holocene. Coherence between δ15Nsed and weight percent organic carbon also suggests that similar mechanisms influence both OMZ fluctuations and variation in organic carbon production/export.

The assessment of age uncertainty in stratigraphically aligned records is a pressing need in paleoceanographic research. The alignment of ocean sediment cores is used to develop mutually consistent age models for climate proxies and is often based on the δ18O of calcite from benthic foraminifera, which records a global ice volume and deep water temperature signal. To date, δ18O alignment has been performed by manual, qualitative comparison or by deterministic algorithms. Here we present a hidden Markov model (HMM) probabilistic algorithm to find 95% confidence bands for δ18O alignment. This model considers the probability of every possible alignment based on its fit to the δ18O data and transition probabilities for sedimentation rate changes obtained from radiocarbon-based estimates for 37 cores. Uncertainty is assessed using a stochastic back trace recursion to sample alignments in exact proportion to their probability. We applied the algorithm to align 35 late Pleistocene records to a global benthic δ18O stack and found that the mean width of 95% confidence intervals varies between 3 and 23 kyr depending on the resolution and noisiness of the record's δ18O signal. Confidence bands within individual cores also vary greatly, ranging from ~0 to >40 kyr. These alignment uncertainty estimates will allow researchers to examine the robustness of their conclusions, including the statistical evaluation of lead-lag relationships between events observed in different cores. Key Points Hidden Markov model estimates uncertainty in benthic oxygen isotope alignmentsRadiocarbon-based estimates of sedimentation rate variabilityBayesian statistics: alignment confidence band, tests of lead-lag relationships

evaluate the relative strength/frequency of El Nino and La Nina events. In contrast to previous studies, we use robust and resistant statistics to quantify the spread and symmetry of the d 18 O distributions; an approach motivated by the relatively small sample size and the presence of outliers. Furthermore, we use a pseudo‐proxy approach to investigate the effects of the different paleo‐environmental factors on the statistics of the d 18 O distributions, which could bias the paleo‐ENSO reconstruction. We find no systematic difference in the magnitude/strength of ENSO during the Northern Hemisphere MCA or LIA. However, our results suggest that ENSO during the MCA was skewed toward stronger/more frequent La Nina than El Nino, an observation consistent with the medieval megadroughts documented from sites in western North America.

[1] An absolute dated speleothem oxygen isotope (δ 18 O) record from northeastern Peru documents monsoon precipitation variability over northern South America during the past that 1000 years and indicates the annual precipitation in the 15th through the 18th centuries, the so-called Little Ice Age (LIA), was on average ∼10% higher than during the 20th century. Over the 20th century recurrent modes of seasonal rainfall variability across northern South America were associated with discrete sea surface temperature anomaly patterns within the Atlantic and Pacific Oceans. Calling upon these SST-rainfall teleconnectivity patterns, and paleo-SST reconstructions that span the past 8 centuries, higher annual rainfall across northern South America during the LIA is attributed to cooler boreal spring SSTs in the tropical North Atlantic. Weaker co-variance between north Atlantic SSTs and the South American Monsoon System (SAMS) rainfall during the 20th century suggests that ENSO has become a more dominant influence than it was during the LIA.