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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.

 

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. The response of the hydrological cycle to anthropogenic climatechange, especially across the tropical oceans, remains poorly understood due to the scarcity of long instrumental temperature and hydrological records. Massive shallow-water corals are ideally suited to reconstructing past oceanic variability as they are widely distributed across the tropics,rapidly deposit calcium carbonate skeletons that continuously record ambient environmental conditions, and can be sampled at monthly to annualresolution. Climate reconstructions based on corals primarily use the stable oxygen isotope composition (δ18O), which acts as a proxy for sea surface temperature (SST), and the oxygen isotope composition ofseawater (δ18Osw), a measure of hydrological variability. Increasingly, coral δ18O time series are paired with time series of strontium-to-calcium ratios (Sr/Ca), a proxy for SST, from the same coral to quantify temperature and δ18Osw variabilitythrough time. To increase the utility of such reconstructions, we presentthe CoralHydro2k database, a compilation of published, peer-reviewed coral Sr/Ca and δ18O records from the Common Era (CE). The database contains 54 paired Sr/Ca–δ18O records and 125 unpaired Sr/Ca or δ18O records, with 88 % of these records providing data coverage from 1800 CE to the present. A quality-controlled set of metadata with standardized vocabulary and units accompanies each record, informing the useof the database. The CoralHydro2k database tracks large-scale temperatureand hydrological variability. As such, it is well-suited for investigationsof past climate variability, comparisons with climate model simulationsincluding isotope-enabled models, and application in paleodata-assimilation projects. The CoralHydro2k database is available in Linked Paleo Data (LiPD) format with serializations in MATLAB, R, and Python and can be downloaded from the NOAA National Center for Environmental Information's Paleoclimate Data Archive at https://doi.org/10.25921/yp94-v135 (Walter et al., 2022). 

Abstract We use theNorthern Hemisphere Tree-RingNetwork Development (NTREND) tree-ring database to examine the effects of using a small, highly-sensitive proxy network for paleotemperature data assimilation over the last millennium. We first evaluate our methods using pseudo-proxy experiments. These indicate that spatial assimilations using this network are skillful in the extratropical Northern Hemisphere and improve on previous NTREND reconstructions based on Point-by-Point regression. We also find our method is sensitive to climate model biases when the number of sites becomes small. Based on these experiments, we then assimilate the real NTREND network. To quantify model prior uncertainty, we produce 10 separate reconstructions, each assimilating a different climate model. These reconstructions are most dissimilar prior to 1100 CE, when the network becomes sparse, but show greater consistency as the network grows. Temporal variability is also underestimated before 1100 CE. Our assimilation method produces spatial uncertainty estimates and these identify treeline North America and eastern Siberia as regions that would most benefit from development of new millennial-length temperature-sensitive tree-ring records. We compare our multi-model mean reconstruction to five existing paleo-temperature products to examine the range of reconstructed responses to radiative forcing. We find substantial differences in the spatial patterns and magnitudes of reconstructed responses to volcanic eruptions and in the transition between the Medieval epoch and Little Ice Age. These extant uncertainties call for the development of a paleoclimate reconstruction intercomparison framework for systematically examining the consequences of proxy network composition and reconstruction methodology and for continued expansion of tree-ring proxy networks. 

Abstract In the past 40 years, the global annual mean surface temperature has experienced a nonuniform warming, differing from the spatially uniform warming simulated by the forced responses of large multimodel ensembles to anthropogenic forcing. Rather, it exhibits significant asymmetry between the Arctic and Antarctic, with intermittent and spatially varying warming trends along the Northern Hemisphere (NH) midlatitudes and a slight cooling in the tropical eastern Pacific. In particular, this “wavy” pattern of temperature changes over the NH midlatitudes features strong cooling over Eurasia in boreal winter. Here, we show that these nonuniform features of surface temperature changes are likely tied together by tropical eastern Pacific sea surface temperatures (SSTs), via a global atmospheric teleconnection. Using six reanalyses, we find that this teleconnection can be consistently obtained as a leading circulation mode in the past century. This tropically driven teleconnection is associated with a Pacific SST pattern resembling the interdecadal Pacific oscillation (IPO), and hereafter referred to as the IPO-related bipolar teleconnection (IPO-BT). Further, two paleo-reanalysis reconstruction datasets show that the IPO-BT is a robust recurrent mode over the past 400 and 2000 years. The IPO-BT mode may thus serve as an important internal mode that regulates high-latitude climate variability on multidecadal time scales, favoring a warming (cooling) episode in the Arctic accompanied by cooling (warming) over Eurasia and the Southern Ocean (SO). Thus, the spatial nonuniformity of recent surface temperature trends may be partially explained by the enhanced appearance of the IPO-BT mode by a transition of the IPO toward a cooling phase in the eastern Pacific in the past decades. 

We present a Python package geared toward the intuitive analysis and visualization of paleoclimate timeseries,Pyleoclim. The code is open‐source, object‐oriented, and built upon the standard scientific Python stack, allowing users to take advantage of a large collection of existing and emerging techniques. We describe the code's philosophy, structure, and base functionalities and apply it to three paleoclimate problems: (a) orbital‐scale climate variability in a deep‐sea core, illustrating spectral, wavelet, and coherency analysis in the presence of age uncertainties; (b) correlating a high‐resolution speleothem to a climate field, illustrating correlation analysis in the presence of various statistical pitfalls (including age uncertainties); (c) model‐data confrontations in the frequency domain, illustrating the characterization of scaling behavior. We show how the package may be used for transparent and reproducible analysis of paleoclimate and paleoceanographic datasets, supporting Findable, Accessible, Interoperable, and Reusable software and an open science ethos. The package is supported by an extensive documentation and a growing library of tutorials shared publicly as videos and cloud‐executable Jupyter notebooks, to encourage adoption by new users.

 

Decadal climate variability and change affects nearly every aspect of our world, including weather, agriculture, ecosystems, and the economy. Predicting its expression is thus of critical importance on multiple fronts. Poweret al. review what is known about tropical Pacific decadal climate variability and change, the degree to which it can be simulated and predicted, and how we might improve our understanding of it. More accurate projections will require longer and more detailed instrumental and paleoclimate records, improved climate models, and better data assimilation methods. —HJS

 

Abstract. The Last Millennium Reanalysis (LMR) utilizes an ensemble methodology to assimilate paleoclimate data for the production of annually resolved climate field reconstructions of the Common Era. Two key elements are the focus of this work: the set of assimilated proxy records and the forward models that map climate variables to proxy measurements. Results based on an updated proxy database and seasonal regression-based forward models are compared to the LMR prototype, which was based on a smaller set of proxy records and simpler proxy models formulated as univariate linear regressions against annual temperature. Validation against various instrumental-era gridded analyses shows that the new reconstructions of surface air temperature and 500 hPa geopotential height are significantly improved (from 10 % to more than 100 %), while improvements in reconstruction of the Palmer Drought Severity Index are more modest. Additional experiments designed to isolate the sources of improvement reveal the importance of the updated proxy records, including coral records for improving tropical reconstructions, and tree-ring density records for temperature reconstructions, particularly in high northern latitudes. Proxy forward models that account for seasonal responses, and dependence on both temperature and moisture for tree-ring width, also contribute to improvements in reconstructed thermodynamic and hydroclimate variables in midlatitudes. The variability of temperature at multidecadal to centennial scales is also shown to be sensitive to the set of assimilated proxies, especially to the inclusion of primarily moisture-sensitive tree-ring-width records. 

The El Niño–Southern Oscillation (ENSO) shapes global climate patterns yet its sensitivity to external climate forcing remains uncertain. Modeling studies suggest that ENSO is sensitive to sulfate aerosol forcing associated with explosive volcanism but observational support for this effect remains ambiguous. Here, we used absolutely dated fossil corals from the central tropical Pacific to gauge ENSO’s response to large volcanic eruptions of the last millennium. Superposed epoch analysis reveals a weak tendency for an El Niño–like response in the year after an eruption, but this response is not statistically significant, nor does it appear after the outsized 1257 Samalas eruption. Our results suggest that those models showing a strong ENSO response to volcanic forcing may overestimate the size of the forced response relative to natural ENSO variability.