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This paper outlines a strategy to teach scientific analysis using Python, integrated with open science publishing concepts. 

DAMP21ka.nc: NetCDF file containing the model prior, proxy values, and DAMP21ka reconstruction for lake status, precipitation, and temperature variables.\n\nclhancock/DAMP21ka-v1.0.0.zip: Notebooks used to generate figures for Hancock et al. (2024)\n\nHolocene-code_development_hydroclimate.zip: Code used to generate the DAMP21ka reconstruction \n\n \n\nHancock, C. L., Erb, M. P., McKay, N. P., Dee, S. G., and Ivanovic, R.: A global Data Assimilation of Moisture Patterns from 21,000–0 BP (DAMP-21ka) using lake level proxy records" 

Global hydroclimate significantly differed from modern climate during the mid-Holocene (6 ka) and Last Glacial Maximum (21 ka). Consequently, both periods have been described as either a partial or reverse analogue for current climate change. To reconstruct past hydroclimate, an offline paleoclimate data assimilation methodology is applied to a dataset of 216 lake status records which provide relative estimates of water level change. The proxy observations are integrated with the climate dynamics of two transient simulations (TraCE-21ka and HadCM3) using a multivariate proxy system model (PSM) which estimates relative lake status from available climate simulation variables. The resulting DAMP-21ka (Data Assimilation of Moisture Patterns 21 000–0 BP) reanalysis reconstructs annual lake status and precipitation values at 500-year resolution and represents the first application of the methodology to global hydroclimate on timescales spanning the Holocene and longer. Validation using Pearson's correlation coefficients indicates that the reconstruction (0.24) is more skillful, on average, than model simulations (0.09), particularly in portions of North America and east Africa, where data density is high and proxy–model disagreement is prominent during the Holocene. Results of the PSM and assimilation are used to evaluate climatic controls on lake status, spatiotemporal patterns of moisture variability, and proxy–model disagreement. During the mid-Holocene, wetter conditions are reconstructed for northern and eastern Africa, Asia, and southern Australia, but in contrast to the model prior, negative anomalies are observed in North America, resulting in drier-than-modern conditions throughout the Northern Hemisphere midlatitudes. Proxy–model disagreement in western North America may reflect a bias in model simulations to stronger sea level pressure gradients in the North Pacific during the mid-Holocene. The data assimilation framework is able to reconcile these differences by integrating the constraints of proxy observations with the dynamics of the model prior to produce a more robust estimation of hydroclimate variability during the past 21 000 years. 

Three natural exposures near Healy, Alaska (Dry Creek, Panguingue Creek, and Healy Spur) and transects of shallow cores from three hillslopes near Eight Mile Lake were analyzed for particle-size distribution, loss-on-ignition for organic matter content, and radiocarbon dating. This study is part of a Master’s thesis research project by Walker at Northern Arizona University (https://www.proquest.com/openview/80b94829f88d5c8e0d0d678581079273/1?pq-origsite=gscholar&cbl=18750&diss=y). It builds on work of Marshall et al. (2023; doi: 10.1029/2022JG007290) who reported data from additional sediment cores taken along one of the hillslopes in this study, namely Hillslope A (https://arcticdata.io/catalog/view/doi:10.18739/A2F76683D). The motivation was to compare datasets of eolian material between different depositional settings, as well as identify trends in eolian thickness and particle size across the Healy landscape to reconstruct Holocene eolian deposition and identify the factors influencing depositon. 

Abstract Paleoclimate reconstructions are now integral to climate assessments, yet the consequences of using different methodologies and proxy data require rigorous benchmarking. Pseudoproxy experiments (PPEs) provide a tractable and transparent test bed for evaluating climate reconstruction methods and their sensitivity to aspects of real-world proxy networks. Here we develop a dataset that leverages proxy system models (PSMs) for this purpose, which emulates the essential physical, chemical, biological, and geological processes that translate climate signals into proxy records, making these synthetic proxies more relevant to the real world. We apply a suite of PSMs to emulate the widely-used PAGES 2k dataset, including realistic spatiotemporal sampling and error structure. A hierarchical approach allows us to produce many variants of this base dataset, isolating the impact of sampling bias in time and space, representation error, sampling error, and other assumptions. Combining these various experiments produces a rich dataset (“pseudoPAGES2k”) for many applications. As an illustration, we show how to conduct a PPE with this dataset based on emerging climate field reconstruction techniques. 

The quantity and preservation of carbon-rich organic matter (OM) underlying permafrost uplands, and the evolution of carbon accumulation with millennial climate change, are large sources of uncertainty in carbon cycle feedbacks on climate change. We investigated permafrost OM accumulation and degradation over the Holocene using a transect of sediment cores dating back to at least c. 6-8 ka, from a hillslope in the Eight Mile Lake watershed, central Alaska. This dataset collected from four permafrost sediment cores includes a variety of biogeochemical datasets including radiocarbon, carbon, nitrogen, particle size, amino acids (concentrations and D:L), bulk density and water content. 

Abstract. In 2013, the Intergovernmental Panel on Climate Changeconcluded that Northern Hemisphere temperatures had reached levelsunprecedented in at least 1400 years. The 2021 report now sees global meantemperatures rising to levels unprecedented in over 100 000 years. ThisTechnical Note briefly explains the reasons behind this major change.Namely, the new assessment reflects additional global warming that occurredbetween the two reports and improved paleotemperature reconstructions thatextend further back in time. In addition to past and recent warming, theconclusion also considers multi-century future warming, which therebyenables a direct comparison with paleotemperature reconstructions onmulti-century time scales. 

Abstract Studying past climate variability is fundamental to our understanding of current changes. In the era of Big Data, the value of paleoclimate information critically depends on our ability to analyze large volume of data, which itself hinges on standardization. Standardization also ensures that these datasets are more Findable, Accessible, Interoperable, and Reusable. Building upon efforts from the paleoclimate community to standardize the format, terminology, and reporting of paleoclimate data, this article describes PaleoRec, a recommender system for the annotation of such datasets. The goal is to assist scientists in the annotation task by reducing and ranking relevant entries in a drop-down menu. Scientists can either choose the best option for their metadata or enter the appropriate information manually. PaleoRec aims to reduce the time to science while ensuring adherence to community standards. PaleoRec is a type of sequential recommender system based on a recurrent neural network that takes into consideration the short-term interest of a user in a particular dataset. The model was developed using 1996 expert-annotated datasets, resulting in 6,512 sequences. The performance of the algorithm, as measured by the Hit Ratio, varies between 0.7 and 1.0. PaleoRec is currently deployed on a web interface used for the annotation of paleoclimate datasets using emerging community standards. 

Abstract. Annually laminated lake sediment can track paleoenvironmental change at high resolution where alternative archives are often not available. However,information about the chronology is often affected by indistinct and intermittent laminations. Traditional chronology building struggles with thesekinds of laminations, typically failing to adequately estimate uncertainty or discarding the information recorded in the laminations entirely,despite their potential to improve chronologies. We present an approach that overcomes the challenge of indistinct or intermediate laminations andother obstacles by using a quantitative lamination quality index combined with a multi-core, multi-observer Bayesian lamination sedimentation modelthat quantifies realistic under- and over-counting uncertainties while integrating information from radiometric measurements (210Pb,137Cs, and 14C) into the chronology. We demonstrate this approach on sediment of indistinct and intermittently laminatedsequences from alpine Columbine Lake, Colorado. The integrated model indicates 3137 (95 % highest probability density range: 2753–3375) varveyears with a cumulative posterior distribution of counting uncertainties of −13 % to +7 %, indicative of systematic observerunder-counting. Our novel approach provides a realistic constraint on sedimentation rates and quantifies uncertainty in the varve chronology byquantifying over- and under-counting uncertainties related to observer bias as well as the quality and variability of the sediment appearance. The approachpermits the construction of a chronology and sedimentation rates for sites with intermittent or indistinct laminations, which are likely moreprevalent than sequences with distinct laminations, especially when considering non-lacustrine sequences, and thus expands the possibilities ofreconstructing past environmental change with high resolution.