Hot and moist "hothouse" climates occurred in Earth's past and are expected in Earth's far future climate, driven by increasing solar luminosity. In hothouse climate regimes, precipitation transitions from a quasi-steady state, as in present-day tropical convection, to an "episodic deluge" or relaxation-oscillator (RO) regime where precipitation occurs in intense bursts separated by multi-day dry spells. Recent studies suggest that the transition to RO convection regimes is radiatively driven. However, the transition from steady state to RO convection has only been studied with radiative convective equilibrium (RCE) simulations with constant insolation, excluding the diurnal cycle. Precipitation and convection are strongly linked to the diurnal cycle in Earth's present climate over both land and ocean. We explore the impact of the diurnal cycle on the transition from steady state to RO convection using two sets of small-domain RCE simulations with ocean and swamp-like surface boundary conditions. Our RCE simulations with ocean boundary conditions show convection transitions to an episodic deluge regime at 322 K and the diurnal cycle modulates precipitation to occur during late-night or near dawn, when convective inhibition is the weakest. Our RCE simulations with swamp-like boundary conditions, which allow for mean surface temperature variations, show that as RO states emerge, the diurnal cycle modulates precipitation to primarily occur during the late-afternoon to about dusk; but as the mean SST increases, precipitation occurs during the late-night to dawn. These results show that the diurnal cycle strongly influences the timing of convection and precipitation patterns in extreme climates.

Climate models and paleoclimate proxies have temperature variability that diverge from each other locally and at long timescales. It is unknown to what extent these divergences also apply to hydroclimate and whether long-term hydroclimate variability is fundamentally different than temperature variability. Here we evaluate the long-term variability of near surface air temperature (tas) and hydroclimate (Palmer Drought Severity Index [PDSI]) using a climate model (the Community Earth System Model-Last Millennium Ensemble [CESM-LME]) and a paleoclimate reconstruction based on this model (the Paleo Hydrodynamics Data Assimilation product [PHYDA]); this framework allows us to see how a model's long-term climate variability is affected by informing it with proxy data. Using power-scaling exponents, we find universally higher scaling values in PHYDA (except for global mean tas) compared to the CESM-LME model. Thus, PHYDA's global PDSI, local PDSI, and local tas are more dominated by low-frequency variability than CESM-LME's. Additionally, PDSI is spectrally flatter than tas in CESM-LME, whereas scaling values of tas and PDSI are comparable in PHYDA. These results indicate that the paleoclimate reconstruction process adds low-frequency variability that CESM-LME otherwise would not have. Based on a range of null reconstruction experiments, we attribute the origin of low-frequency variability in PHYDA to proxy information and not the mathematical properties of the data assimilation methodology. This implies that long-term variability in PHYDA is dependent on the selection of assimilated proxy data.

Reconstructions of past climates in both time and space provide important insight into the range and rate of change within the climate system. However, producing a coherent global picture of past climates is difficult because indicators of past environmental changes (proxy data) are unevenly distributed and uncertain. In recent years, paleoclimate data assimilation (paleoDA), which statistically combines model simulations with proxy data, has become an increasingly popular reconstruction method. Here, we describe advances in paleoDA to date, with a focus on the offline ensemble Kalman filter and the insights into climate change that this method affords. PaleoDA has considerable strengths in that it can blend multiple types of information while also propagating uncertainty. Drawbacks of the methodology include an overreliance on the climate model and variance loss. We conclude with an outlook on possible expansions and improvements in paleoDA that can be made in the upcoming years. ▪ Paleoclimate data assimilation blends model and proxy information to enable spatiotemporal reconstructions of past climate change. ▪ This method has advanced our understanding of global temperature change, Earth's climate sensitivity, and past climate dynamics. ▪ Future innovations could improve the method by implementing online paleoclimate data assimilation and smoothers.

The North American Southwest (NASW) and South American Southwest (SASW) are regions susceptible to prolonged and intense droughts that can span a decade or more (i.e., megadroughts). Although the drivers and impacts of megadroughts in each region and their co-occurrence have been examined in paleoclimate reconstructions, it is not known whether climate models simulate co-occurring megadroughts in these regions with characteristics and drivers that are similar to the real world. We compare the temporal characteristics of concurrent megadroughts and the Pacific Ocean conditions associated with these events in the Paleo Hydrodynamics Data Assimilation (PHYDA) product and the Community Earth System Model Last Millennium Ensemble (CESM-LME). We find that concurrent megadroughts in PHYDA and CESM-LME have similar temporal characteristics, but the relationship between hydroclimate conditions in the NASW and SASW is different between proxy-based estimates and the climate model. Further analyses reveal that changes in the tropical Pacific Ocean are weaker during concurrent megadroughts in the CESM-LME compared to those in PHYDA and that their teleconnection patterns and strengths are different. Reconstruction methodology is also found to be a factor in how the relationship between the tropical Pacific and each region is characterized. These results together indicate that while the CESM-LME simulates concurrent megadroughts with temporal characteristics similar to PHYDA, it does so for different reasons; this result leaves open the question of whether climate models used for future projections can accurately capture the risk of concurrent megadroughts in future projections.

In this investigation, we reassess the hypothesis that volcanic eruptions lead to surface warming in Eurasia during winter. This reevaluation is grounded in contemporary modeling studies that propose internal climatic variations might dominate over the volcanic-forced responses. Our analysis is centered on the Last Millennium (LM), where we combine model output, instrumental observations, tree-ring records, and ice cores, and build a new temperature reconstruction that specifically targets the boreal winter season. Utilizing the latest advancements in volcanic forcing reconstructions, we pinpoint 20 volcanic events over the LM with volcanic stratospheric sulfur injections (VSSI) exceeding those of the 1991 Pinatubo eruption. Our analysis indicates that among the 20 major volcanic events identified, only seven resulted in warmer surface temperature anomalies in Eurasia during the initial winter following the eruption. In scrutinizing the 13 occurrences that exhibit cold post-eruption anomalies, we observe no direct correlation between the extent of winter cooling and the mass of volcanic stratospheric sulfur injections (VSSI), suggesting that significant internal climatic variability is the probable driver of these cold anomalies. Moreover, we compare our new temperature reconstruction with two independent reconstructions, and successfully harmonize our results with those of prior research. Moving beyond the observational uncertainties and the conflation of eruptions from different latitudes and different post-eruption winters, our study challenges previous assertions of post-eruption winter warming that largely stemmed from the superposed epoch analysis, which involved averaging the effects of smaller eruptions with larger ones. Our comprehensive observational findings, encompassing the entire LM and corroborating many recent climate modeling studies, suggest that substantial low-latitude volcanic eruptions, such as the 1991 Mount Pinatubo eruption, do not lead to any notable surface warming during the winter months in Eurasia.

Historical documentary accounts from the Indian subcontinent document several decade-to-multidecade clusters of severe Indian summer monsoon (ISM) droughts over the past millennium. Many of these putative droughts have no counterparts in the instrumental period. An objective assessment of the severity and frequency of these droughts and their teleconnections to other parts of the climate system remains uncertain. Here, we use the Paleo Hydrodynamics Data Assimilation (PHYDA) product to address this gap. PHYDA reproduces historical intervals of increased drought frequency with high fidelity and reveals multiple instances of multi-year “black swan” droughts— rare, severe events with significant societal impacts that are consistent with historical accounts. We find that droughts, as well as extended periods of dryness, occurred under both El Niño and non-El Niño conditions, with El Niño explaining ~ 49% of all drought instances. A large number (~42%) of non-El Niño type droughts were forced by cooler extratropical SST anomalies in the North Atlantic region. While El Niño was an important driver, its association with droughts varied considerably, accounting for between 15-80% of droughts depending on the century. The PHYDA’s millennial-length perspective supports expanding the El Niño-centric paradigm of droughts into a framework that includes extratropical teleconnections.

The relatively short observational record limits our ability to understand the long-term variability of key climate factors like temperature and hydroclimate. Climate models and paleoclimate proxies appear to have long-term temperature variabilities that diverge from each other at local and long time scales. But it is unclear whether these divergences also apply to hydroclimate and whether long-term hydroclimate variability is fundamentally different than temperature variability.Here we evaluate the long-term variability over the Common Era of temperature and hydroclimate using a climate model (the Community Earth System Model-Last Millennium Ensemble, CESM-LME) and a paleoclimate reconstruction based on this model (the Paleo Hydrodynamics Data Assimilation product, PHYDA); this framework allows us to see how a model’s long-term climate variability is affected by informing it with proxy data. We specifically focus our analyses on the continuum of temperature (tas) and the Palmer Drought Severity Index (PDSI) in four regions of low reconstruction uncertainty: the Western USA, the Eastern USA, Central Europe, and Scandinavia.Using the power-scaling exponents β from the relationship S(τ) ∼ τβ, where S denotes the power spectral density (PSD) and τ the period, we find universally higher values of β in PHYDA (except for tas globally); in these four regions PHYDA’s β values are 0.30 to 0.63 higher than CESM-LME. Thus, long range dependence behavior is more pronounced in PHYDA than in the CESM-LME model. We find that PHYDA has different spatial distributions of β than CESM-LME. We also find that hydroclimate is spectrally flatter than temperature in CESM-LME, whereas temperature and hydroclimate β-values are comparable in PHYDA. These results show that CESM-LME’s hydroclimate and temperature is less dominated by long timescales compared to PHYDA’s. The robustness of the low-frequency variability signal in PHYDA was verified by performing pseudoproxy experiments. Furthermore, preliminary results of other temperature DA reconstructions over the Holocene and since the Last Glacial Maximum also reveal spectral divergencies with model data. In particular, for the PSD of the global mean temperatures, higher beta values were obtained for the reconstructions compared to the model data, indicating a deficit in simulated low-frequency.

Data assimilation techniques, such as the Kalman Filter, have enabled the development of complete climate field reconstructions over the last millennium, commonly referred to as paleoclimate reanalysis. These techniques effectively integrate paleoclimate data, facilitating the understanding and attribution of past climate events. The resulting spatio-temporal fields are invaluable for studying teleconnections and exploring dynamical links between variables and locations in the past. However, when the observation network is sparse, or proxies exhibit high levels of non-climatic noise, the Kalman Filter tends to revert to the prior. These limitations often result in paleoclimate data assimilation products underestimating variability in earlier periods and overestimating spatial coherence compared to modern observations, reducing their reliability. We thus investigate the timescale-dependent variance and the spatio-temporal covariance of different paleoclimate data assimilation products: ModE-RA, LMR, and PHYDA, and relate differences primarily to the methodology and prior assumptions. The results from the data assimilation products were further assessed against instrumental data and CMIP6 pre-industrial control and fully forced simulations.

Observations show that the teleconnection between the El Nino-Southern Oscillation (ENSO) and the Asian summer monsoon (ASM) is non-stationary. However, the underlying mechanisms are poorly understood due to inadequate availability of reliable, long-term observations. This study uses two state-of-the-art data assimilation-based reconstructions of last millennium climate to examine changes in the ENSO-ASM teleconnection; we investigate how modes of (multi-)decadal climate variability (namely, the Pacific Decadal Oscillation, PDO, and the Atlantic Multidecadal Oscillation, AMO) modulate the ENSO-ASM relationship. Our analyses reveal that the PDO exerts a more pronounced impact on ASM variability than the AMO. By comparing different linear regression models, we find that including the PDO in addition to ENSO cycles can improve prediction of the ASM, especially for the Indian summer monsoon. In particular, dry (wet) anomalies caused by El Nino (La Nina) over India become enhanced during the positive (negative) PDO phases due to a compounding effect. However, composite differences in the ENSO-ASM relationship between positive and negative phases of the PDO and AMO are not statistically significant. A significant influence of the PDO/AMO on the ENSO-ASM relationship occurred only over a limited period within the last millennium. By leveraging the long-term paleoclimate reconstructions, we document and interrogate the non-stationary nature of the PDO and AMO in modulating the ENSO-ASM relationship. Sea surface temperatures in the tropical Pacific oscillate between warmer and cooler conditions every 2-7 years. These oscillations are called "The El Nino-Southern Oscillation (ENSO)" and have been shown to affect weather and climate in remote locations. For example, ENSO has been shown to alter rainfall of the Asian summer monsoon (ASM). However, the connection between ENSO and the ASM is not dependable, making accurate ASM prediction a challenge, especially in a changing climate. Here, we use a new technique that combines geological archives of past climates like ice cores, corals, or lake sediments with climate models to examine alterations in the ENSO-ASM relationship over the past thousand years. In particular, we focus on how other oscillatory ocean temperature patterns, the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO), might affect the ENSO-ASM relationship. In the context of the last millennium, we find the differences in the ENSO-ASM relationship between all positive and negative PDO/AMO phases are not statistically significant, as the PDO/AMO modulation on the ENSO-ASM relationship evolves over long time scales. Nevertheless, the PDO itself strongly regulates the Indian summer monsoon, and the consideration of PDO in addition to ENSO enhances monsoon prediction. This information is useful for anticipating decadal-scale changes in the ASM in our changing climate. We investigate how the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO) modulate the relationship between El Nino-Southern Oscillation (ENSO) and the Asian summer monsoon (ASM) using paleo-data assimilation productsWe find that the PDO impacts ASM variability more than the AMO, and its consideration yields improved Indian summer monsoon predictionsNotably, the influence of the PDO and AMO on the ENSO-ASM relationship is highly non-stationary across the last millennium

We critically reexamine the question of whether volcanic eruptions cause surface warming over Eurasia in winter, in the light of recent modeling studies that have suggested internal variability may overwhelm any forced volcanic response, even for the very largest eruptions during the Common Era. Focusing on the last millennium, we combine model output, instrumental observations, tree-ring records, and ice cores to build a new temperature reconstruction that specifi- fi- cally targets the boreal winter season. We focus on 20 eruptions over the last millennium with volcanic stratospheric sulfur injections (VSSIs) larger than the 1991 Pinatubo eruption. We fi nd that only 7 of these 20 large events are followed by warm surface temperature anomalies over Eurasia in the fi rst posteruption winter. Examining the 13 events that show cold posteruption anomalies, we fi nd no correlation between the amplitude of winter cooling and VSSI mass. We also fi nd no evidence that the North Atlantic Oscillation is correlated with VSSI in winter, a key element of the proposed mechanism through which large, low-latitude eruptions might cause winter warming over Eurasia. Furthermore, by inspecting individual eruptions rather than combining events into a superposed epoch analysis, we are able to reconcile our fi ndings with those of previous studies. Analysis of two additional paleoclimatic datasets corroborates the lack of posteruption Eurasian winter warming. Our fi ndings, covering the entire last millennium, confirm fi rm the fi ndings of most recent modeling studies and offer important new evidence that large, low-latitude eruptions are not, in general, followed by significant fi cant surface wintertime warming over Eurasia.

Paleoclimatological field reconstructions are valuable for understanding past hydroclimatic variability, which is crucial for assessing potential future hydroclimate changes. Despite being as impactful on societies as temperature variability, hydroclimatic variability - particularly beyond the instrumental record - has received less attention. The reconstruction of globally complete fields of climate variables lacks adequate proxy data from tropical regions like South America, limiting our understanding of past hydroclimatic changes in these areas. This study addresses this gap using low-resolution climate archives, including speleothems, previously omitted from reconstructions. Speleothems record climate variations on decadal to centennial timescales and provide a rich dataset for the otherwise proxy-data-scarce region of tropical South America. By employing a multi-timescale paleoclimate data assimilation approach, we synthesize climate proxy records and climate model simulations capable of simulating water isotopologs in the atmosphere to reconstruct 2000 years of South American climate. This includes surface air temperature, precipitation amount, drought index, isotopic composition of precipitation amount and the intensity of the South American Summer Monsoon. The reconstruction reveals anomalous climate periods: a wetter and colder phase during the Little Ice Age (similar to 1500-1850 CE) and a drier, warmer period corresponding to the early Medieval Climate Anomaly (similar to 600-900 CE). However, these patterns are not uniform across the continent, with climate trends in northeastern Brazil and the Southern Cone not following the patterns of the rest of the continent, indicating regional variability. The anomalies are more pronounced than in previous reconstructions but match trends found in local proxy record studies, thus highlighting the importance of including speleothem proxies. The multi-timescale approach is essential for reconstructing multi-decadal and centennial climate variability. Despite methodological uncertainties regarding climate model biases and proxy record interpretations, this study marks a crucial first step in incorporating low-resolution proxy records such as speleothems into climate field reconstructions using a multi-timescale approach. Adequately extracting and using the information from speleothems potentially enhances insights into past hydroclimatic variability and hydroclimate projections.

*Dec 2023 Proxy Database Update: This database has been updated based on a more stringent proxy screening procedure. All screening calculations and decisions are documented in the accompanying Julia code Pluto notebook file (see also the HTML file preview of the code). This screening has resulted in the removal of 183 proxy time series from the original file.* Original Data Descriptor: This collection of paleoclimate proxy data currently includes 2591 tree ring chronologies, 197 coral and sclerosponge records, 153 ice core isotope records, 26 speleothem isotope records, 10 lake sediment records, and 1 marine sediment record, for a total of 2,978 records. The proxy records have been collected with a focus on the past 2000 years. This dataset has been collated through collaborative efforts with the Last Millennium Reanalysis project (Hakim et al. 2016) and provides the basis for the reconstructions presented in Steiger et al. (2018). Though the majority of data records are culled from PAGES2k Consortium (2017) and Breitenmoser et al. (2014), some data was taken from the NOAA NCEI's World Data Center for Paleoclimatology archive. Additionally, data was solicited from multiple investigators such as Eric Steig, Stephanie Hayman, Sylke Draschba, Henning Kuhnert, Andy Baker, and others amounting to approximately 60 coral, ice core, speleothem, and lake sediment datasets, though all files in this archive can be freely shared. Datasets were selected whose resolution was at least 25 years, temporal duration was greater than 40 years, and consisted of proxies that had established proxy system models (forward models). The data files are in Matlab format and the variables here include the proxy names ('lmr2k_names'), the proxy data ('lmr2k_data'), the proxy type ('archive'), the proxy measurement ('msrmt'), the proxy latitudes and longitudes ('p_lat' and 'p_lon'), and the years of the proxies ('year'). Seasonally resolved proxies have been averaged from April to the following calendar year March. Updates will be made to this proxy collection as more proxy data become available. Breitenmoser, P., et al. "Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies." Climate of the Past 10.2 (2014): 437. PAGES2k Consortium. "A global multiproxy database for temperature reconstructions of the common era." Scientific Data 4, 170088 (2017). Hakim, Gregory J., et al. "The last millennium climate reanalysis project: Framework and first results." Journal of Geophysical Research: Atmospheres 121.12 (2016): 6745-6764. Steiger, N. J. et al. "A reconstruction of global hydroclimate and dynamical variables over the Common Era." Scientific Data 5:180086 (2018).

Data Assimilation in paleoclimatology (PaleoDA) is a method that has been used in several climate reconstructions for the last millennium. By fusing information from both climate proxies and general circulation models (GCMs), PaleoDA provides statistical estimates of climate fields that are dynamically consistent. However, existing reconstructions mostly rely on calibrated tree ring data and assimilate proxy records on a single, annual time scale. Ice cores and speleothems, which record past variations in the oxygen isotope ratio of precipitation, often have a lower and irregular time resolution, but reliably record climate variations on decadal to centennial time scales. Here, we implemented a computationally efficient DA algorithm that enables the assimilation of proxy records on multiple timescales. The algorithm has been applied to speleothem and ice core records from the SISALv2 and Iso2k database and five isotope-enabled GCMs. Reconstructions of global mean temperature changes during the last millennium compare well in both amplitude and uncertainty to recent studies. The potential of incorporating speleothems is shown with a reconstruction of hydroclimatic changes in tropical South America, where speleothems represent the most abundant type of hydroclimate archive. The experiments performed suggest an increased reconstructed decadal to centennial variability by using proxy records on multiple timescales. Making use of different climate models shows the influence of model biases on the reconstructions. Future PaleoDA reconstructions could be improved from more proxy records and the multiple time scale approach to provide a globally complete picture of past climate changes.

In a "hothouse" climate, warm temperatures lead to a high tropospheric water vapor concentration. Sufficiently high water vapor levels lead to the closing of the water vapor infrared window, which prevents radiative cooling of the lower troposphere. Because water vapor also weakly absorbs solar radiation, hothouse climates feature radiative heating of the lower troposphere. In recent work, this radiative heating was shown to trigger a shift into a novel "episodic deluge" precipitation regime, where rainfall occurs in short, intense outbursts separated by multi-day dry spells. Here, we further examine the role of the lower tropospheric radiative heating (LTRH) in the transition into the "episodic deluge" regime. We demonstrate that under high sea-surface temperature the "episodic deluge" regime could be formed even before the LTRH turns positive. In addition, we examine whether these oscillations operate on larger scales and how these oscillations, which represent "temporal" convective self-organization, would manifest in the presence of traditional "spatial" self- or forced-aggregation in large-domain convection-permitting simulations. We find that the temporal oscillations become much less synchronized throughout a large domain ( O 1,000 km) because gravity waves cannot propagate fast enough to synchronize convection. We also show that temporal oscillations still dominate the rainfall distribution even when there is tropical convective self-aggregation or a large-scale overturning circulation. These results could have important implications for extreme precipitation events under a warming climate.

Climate field reconstructions (CFRs) combine modern observational data with paleoclimatic proxies to estimate climate variables over spatiotemporal grids during time periods when widespread observations of climatic conditions do not exist. The Common Era (CE) has been a period over which many seasonally‐ and annually‐resolved CFRs have been produced on regional to global scales. CFRs over the CE were first produced in the 1970s using dendroclimatic records and linear regression‐based approaches. Since that time, many new CFRs have been produced using a wide range of proxy data sets and reconstruction techniques. We assess the early history of research on CFRs for the CE, which provides context for our review of advances in CFR research over the last two decades. We review efforts to derive gridded hydroclimatic CFRs over continental regions using networks of tree‐ring proxies. We subsequently explore work to produce hemispheric‐ and global‐scale CFRs of surface temperature using multi‐proxy data sets, before specifically reviewing recently‐developed data assimilation techniques and how they have been used to produce simultaneous reconstructions of multiple climatic fields globally. We then review efforts to develop standardized and digitized databases of proxy networks for use in CFR research, before concluding with some thoughts on important next steps for CFR development.

Mississippi River basin floods impart large socioeconomic impacts over the central United States. Improving flood predictability depends on our understanding of the dynamical controls on Mississippi basin hydroclimate. However, short instrumental records make it difficult to constrain the connections between flooding and climate variability. Here, we use the Paleo Hydrodynamics Data Assimilation product, spanning the Last Millennium, to investigate the impacts of tropical Pacific and North Atlantic sea surface temperature (SST) variability on hydrological extremes across the Mississippi River and its major tributaries. Wet extremes are associated with strong El Nino-like warming over the tropical Pacific, but specific SST patterns matter: dry (wet) conditions occur during Central Pacific (Eastern Pacific) El Nino events. The influence of North Atlantic SSTs is less clear, but cool SSTs contribute to Ohio basin wet extremes. These results are relevant for seasonal-to-interannual flood hazard prediction on the fourth largest river basin in the world.

The history of the Polynesian civilization on Rapa Nui (Easter Island) over the Common Era has come to exemplify the fragile relationship humans have with their environment. Social dynamics, deforestation, land degradation, and climatic shifts have all been proposed as important parts of the settlement history and societal transformations on Rapa Nui. Furthermore, climate dynamics of the Southeast Pacific have major global implications. While the wetlands of Rapa Nui contain critical sedimentological archives for reconstructing past hydrological change on the island, connections between the island’s hydroclimate and fundamental aspects of regional climatology are poorly understood. Here we present a hydroclimatology of Rapa Nui showing that there is a clear seasonal cycle of precipitation, with wet months receiving almost twice as much precipitation as dry months. This seasonal cycle can be explained by the seasonal shifts in the location and strength of the climatological south Pacific subtropical anticyclone. For interannual precipitation variability, we find that the occurrence of infrequent, large rain events explains 92% of the variance of the observed annual mean precipitation time series. Approximately one third (33%) of these events are associated with atmospheric rivers, 21% are associated with classic cold-front synoptic systems, and the remainder are characterized by cut-off lows and other synoptic-scale storm systems. As a group, these large rain events are most strongly controlled by the longitudinal position of the south Pacific subtropical anticyclone. The longitudinal location of this anticyclone explains 21% of the variance in the frequency of large rain events, while the remaining variance is left unexplained by any other major atmosphere-ocean dynamics. We find that over the observational era there appears to be no linear relationship between the number of large rain events and any other major climate phenomena. With the south Pacific subtropical anticyclone projected to strengthen and expand westward under global warming, our results imply that Rapa Nui will experience an increase in the number of dry years in the future.

A winter, Eurasian-focused paleoclimate temperature reconstruction over the past 1000 years. The reconstruction is over a seasonal average of December to February. The reconstruction includes Eurasia and Greenland paleoclimate data that have a correlation with winter temperature (p < 0.05, accounting for proxy autocorrelation). The reconstruction also includes long observational temperature records from the Northern Hemisphere.

El Niño‐Southern Oscillation (ENSO) variability affects year‐to‐year changes in North American hydroclimate. Extra‐tropical teleconnections are not always consistent between El Niño events due to stochastic atmospheric variability and diverse sea surface temperature anomalies, making it difficult to quantify teleconnections using only instrumentally‐based records. Here we use two paleoclimate data assimilation (DA) products spanning the Last Millennium (LM) to compare changes in amplitudes and frequencies of diverse El Niño events during the pre‐industrial period and 20th century, and to assess the stationarity of their North American hydroclimate impacts on multi‐decadal to centennial timescales. Using several definitions for Central Pacific (CP) and Eastern Pacific (EP) El Niño, we find a marked increase in 20th century EP El Niño intensity, but no significant changes in CP or EP El Niño frequencies in response to anthropogenic forcing. The associated hydroclimate anomalies indicate (a) dry conditions across the eastern‐central and northwestern U.S. during CP El Niño and wetter conditions in the same regions during EP El Niño; (b) wet conditions over the southwestern U.S. for both El Niño types. The magnitude of regional hydroclimate teleconnections also shows large natural variability on multi‐decadal to centennial timescales. However, when the entire LM is considered, mean hydroclimate anomalies in North America during CP or EP El Niño are consistent in terms of sign (wet vs. dry). Results are sensitive to proxy data and model priors used in DA products. Inconsistencies between El Niño classification methods underscore the need for improved ENSO diversity classification when assessing precipitation teleconnections.