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Abstract 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. 

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. 

Abstract 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. 

Abstract. Paleoclimatic records provide valuable information about Holocene climate, revealing aspects of climate variability for a multitude of sites around the world. However, such data also possess limitations. Proxy networks are spatially uneven, seasonally biased, uncertain in time, and present a variety of challenges when used in concert to illustrate the complex variations of past climate. Paleoclimatic data assimilation provides one approach to reconstructing past climate that can account for the diversenature of proxy records while maintaining the physics-based covariancestructures simulated by climate models. Here, we use paleoclimate dataassimilation to create a spatially complete reconstruction of temperatureover the past 12 000 years using proxy data from the Temperature 12k database and output from transient climate model simulations. Following the last glacial period, the reconstruction shows Holocene temperatures warming to a peak near 6400 years ago followed by a slow cooling toward the present day, supporting a mid-Holocene which is at least as warm as the preindustrial. Sensitivity tests show that if proxies have an overlooked summer bias, some apparent mid-Holocene warmth could actually represent summer trends rather than annual mean trends. Regardless, the potential effects of proxy seasonal biases are insufficient to align the reconstructed global mean temperature with the warming trends seen in transient model simulations. 

Abstract 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. 

Abstract Observations show that the teleconnection between the El Niño‐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 Niño (La Niña) 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. 

Large tropical volcanic eruptions can affect the climate of many regions on Earth, yet it is uncertain how the largest eruptions over the past millennium may have altered Earth’s hydroclimate. Here, we analyze the global hydroclimatic response to all the tropical volcanic eruptions over the past millennium that were larger than the Mount Pinatubo eruption of 1991. Using the Paleo Hydrodynamics Data Assimilation product (PHYDA), we find that these large volcanic eruptions tended to produce dry conditions over tropical Africa, Central Asia and the Middle East and wet conditions over much of Oceania and the South American monsoon region. These anomalies are statistically significant, and they persisted for more than a decade in some regions. The persistence of the anomalies is associated with southward shifts in the Intertropical Convergence Zone and sea surface temperature changes in the Pacific and Atlantic oceans. We compare the PHYDA results with the stand-alone model response of the Community Earth System Model (CESM)-Last Millennium Ensemble. We find that the proxy-constrained PHYDA estimates are larger and more persistent than the responses simulated by CESM. Understanding which of these estimates is more realistic is critical for accurately characterizing the hydroclimate risks of future volcanic eruptions.