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The paleogeosciences are becoming more and more interdisciplinary, and studies increasingly rely on large collections of data derived from multiple data repositories. Integrating diverse datasets from multiple sources into complex workflows increases the challenge of creating reproducible and open science, as data formats and tools are often noninteroperable, requiring manual manipulation of data into standardized formats, resulting in a disconnect in data provenance and confounding reproducibility. Here we present a notebook that demonstrates how the Linked PaleoData (LiPD) framework is used as an interchange format to allow data from multiple data sources to be integrated in a complex workflow using emerging packages in R for geochronological uncertainty quantification and abrupt change detection. Specifically, in this notebook, we use the neotoma2 and lipdR packages to access paleoecological data from the Neotoma Database, and paleoclimate data from compilations hosted on Lipdverse. Age uncertainties for datasets from both sources are then quantified using the geoChronR package, and those data, and their associated age uncertainties, are then investigated for abrupt changes using the actR package, with accompanying visualizations. The result is an integrated, reproducible workflow in R that demonstrates how this complex series of multisource data integration, analysis and visualization can be integrated into an efficient, open scientific narrative. 

Abstract Despite decades of effort to constrain equilibrium climate sensitivity (ECS), current best estimates still exhibit a large spread. Past studies have sought to reduce ECS uncertainty through a variety of methods including emergent constraints. One example uses global temperature variability over the past century to constrain ECS. While this method shows promise, it has been criticized for its susceptibility to the influence of anthropogenic forcing and the limited length of the instrumental record used to compute temperature variability. Here, we investigate the emergent relationship between ECS and two metrics of global temperature variability using model simulations and paleoclimate reconstructions over the last millennium (850–1999). We find empirical evidence in support of these emergent relationships. Observational constraints suggest a central ECS estimate of 2.5–2.7 K, consistent with the Intergovernmental Panel on Climate Change's consensus estimate of 3K. Moreover, they suggest ECS “likely” ranges of 1.7–3.3 K and 1.9–3.5 K. 

The American West exemplifies drought-sensitive regions with growing populations. Paleoclimate investigations have documented severe droughts in this region before European settling, with major implications for water management and planning. Here, we leverage paleoclimate data assimilation to reconstruct past climate states, enabling a large-scale multivariate investigation of U.S. drought dynamics over the last millennium. These results confirm that La Niña conditions significantly influence southwest U.S. drought over the past millennium but only account for, by one metric, ~13% of interannual drought variability in that region. Atlantic sea surface temperatures may also contribute a small influence, but unexplained variability suggests a substantial role for internal atmospheric variability. This conclusion is buttressed by analysis of simulations from the Community Earth System Model Last Millennium Ensemble. While greenhouse gases will increase future drought risk, as shown in other work, interannual U.S. drought variations will also be widely influenced by processes internal to the atmosphere.