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The recent proliferation of broadband ocean bottom seismometer (BBOBS) deployments has generated datasets from diverse marine environments, improving our understanding of tectonics and earthquake processes. In turn, the community of scientists using this data has expanded. This growth in BBOBS data collection is likely to persist with the arrival of new seismic seafloor technologies, and continued scientific interest in marine and amphibious targets. However, the noise inherent in OBS data poses a challenge that is markedly different from that of terrestrial data. As a step towards improved understanding of the sources of variability in this noise, we present a new compilation and analysis of BBOBS noise properties from 15 years of US-led seismic deployments. We find evidence for similarity of noise properties when grouped across a variety of parameters, with groupings by seismometer type and deployment water depth yielding the most significant and interpretable results. Instrument design, that is the entire deployed package, also plays an important role, although it strongly covaries with seismometer and water depth. We find that the presence of tilt noise is primarily dependent on the type of seismometer used (covariant with a particular subset of instrument design), that compliance noise follows anticipated relationships with water depth, and that shallow, oceanic shelf environments have systematically different microseism noise properties (which are, in turn, different from instruments deployed in shallow lake environments). We discuss implications for the viability of commonly used seismic analysis techniques, and future directions for improvements in the efficiency of analysis of BBOBS data., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Characterizing variability in the global water cycle is fundamental to predicting impacts of future climate change; understanding the role of the Pacific Walker circulation (PWC) in the regional expression of global water cycle changes is critical to understanding this variability. Water isotopes are ideal tracers of the role of the PWC in global water cycling because they retain information about circulation-dependent processes including moisture source, transport, and delivery. We collated publicly available measurements of precipitationδ18O (δ18OP) and used novel data processing techniques to synthesize long (34 yr), globally distributed composite records from temporally discontinuousδ18OPmeasurements. We investigated relationships between global-scaleδ18OPvariability and PWC strength, as well as other possible drivers of globalδ18OPvariability—including El Niño–Southern Oscillation (ENSO) and global mean temperature—and used isotope-enabled climate model simulations to assess potential biases arising from uneven geographical distribution of the observations or our data processing methodology. Covariability underlying theδ18OPcomposites is more strongly correlated with the PWC (r= 0.74) than any other index of climate variability tested. We propose that the PWC imprint in globalδ18OParises from multiple complementary processes, including PWC-related changes in moisture source and transport length, and a PWC- or ENSO-driven “amount effect” in tropical regions. The clear PWC imprint in globalδ18OPimplies a strong PWC influence on the regional expression of global water cycle variability on interannual to decadal time scales, and hence that uncertainty in the future state of the PWC translates to uncertainties in future changes in the global water cycle.

Thirty years of satellite-altimeter data and longer tide-gauge records show that rates of coastal sea-level rise are increasing across parts of the global ocean. Such sea-level acceleration is particularly pronounced along the U.S. Gulf of Mexico coastline. Here, we use model output and observational data to investigate the mechanisms underlying these enhanced regional rates of change. Interrogating the Estimating the Circulation and Climate of the Ocean (ECCO) Version 5 ocean state estimate, we find that interannual-to-decadal coastal sea-level changes in the Gulf of Mexico largely reflect local changes in ocean mass. Based on model diagnostics, we determine that important contributions to coastal ocean-mass changes are made by: 1) net mass flux into the Gulf and 2) mass redistribution related to ocean warming within the Gulf. The redistribution of mass within the Gulf can be understood as an isostatic ocean response to warming of the Gulf of Mexico below the seasonal mixed layer. Observations of ocean bottom pressure from the Gravity Recovery and Climate Experiment (GRACE/GRACE-FO) similarly reveal trend patterns suggestive of redistribution of mass from deeper regions in the Gulf onto the shelf. This redistribution is driven by subsurface warming observed in Argo measurements of temperature. Since ~2008, rates of subsurface Gulf warming have increased, driving an increase in sea-level trends at the coast. Together, the mass flux into the Gulf and warming-driven redistribution of mass onto the shelf explain a dominant fraction of coastal sea level trends observed at tide gauge stations throughout the Gulf, particularly along the west Florida shelf. The mechanism identified here, relating offshore subsurface warming to coastal sea level, reveals the importance of open-ocean effects on the coast and also bathymetric geometry in shaping an observed response to warming. Results highlight the ability of ocean bottom pressure measurements from GRACE to capture the spatially varying redistribution of mass driven by oceanic uptake of heat.

The majority of future projections in the Coupled Model Intercomparison Project (CMIP5) show more frequent exceedances of the 5 mm day−1 rainfall threshold in the eastern equatorial Pacific rainfall during El Niño, previously described in the literature as an increase in “extreme El Niño events”; however, these exceedance frequencies vary widely across models, and in some projections actually decrease. Here we combine single-model large ensemble simulations with phase 5 of the Coupled Model Intercomparison Project (CMIP5) to diagnose the mechanisms for these differences. The sensitivity of precipitation to local SST anomalies increases consistently across CMIP-class models, tending to amplify extreme El Niño occurrence; however, changes to the magnitude of ENSO-related SST variability can drastically influence the results, indicating that understanding changes to SST variability remains imperative. Future El Niño rainfall intensifies most in models with 1) larger historical cold SST biases in the central equatorial Pacific, which inhibit future increases in local convective cloud shading, enabling more local warming; and 2) smaller historical warm SST biases in the far eastern equatorial Pacific, which enhance future reductions in stratus cloud, enabling more local warming. These competing mechanisms complicate efforts to determine whether CMIP5 models under- or overestimate the future impacts of climate change on El Niño rainfall and its global impacts. However, the relation between future projections and historical biases suggests the possibility of using observable metrics as “emergent constraints” on future extreme El Niño, and a proof of concept using SSTA variance, precipitation sensitivity to SST, and regional SST trends is presented.

We present a new compilation and analysis of broadband ocean bottom seismometer noise properties from 15 years of seismic deployments. We compile a comprehensive dataset of representative four-component (seismometer and pressure gauge) noise spectra and cross-spectral properties (coherence, phase, and admittance) for 551 unique stations spanning 18 US-led experiments. This is matched with a comprehensive compilation of metadata parameters related to instrumentation and environmental properties for each station. We systematically investigate the similarity of noise spectra by grouping them according to these metadata parameters to determine which factors are the most important in determining noise characteristics. We find evidence for improvements in similarity of noise properties when grouped across parameters, with groupings by seismometer type and deployment water depth yielding the most significant and interpretable results. Instrument design, that is the entire deployed package, also plays an important role, although it strongly covaries with seismometer and water depth. We assess the presence of traditional sources of tilt, compliance, and microseismic noise to characterize their relative role across a variety of commonly used seismic frequency bands. We find that the presence of tilt noise is primarily dependent on the type of seismometer used (covariant with a particular subset of instrument design), that compliance noise follows anticipated relationships with water depth, and that shallow, oceanic shelf environments have systematically different microseism noise properties (which are, in turn, different from instruments deployed in shallow lake environments). These observations have important implications for the viability of commonly used seismic analysis techniques. Finally, we compare spectra and coherences before and after vertical channel tilt and compliance noise removal to evaluate the efficacy and limitations of these now standard processing techniques. These findings may assist in future experiment planning and instrument development, and our newly compiled noise dataset serves as a building block for more targeted future investigations by the marine seismology community.

Machine-learning-based methods that identify drought in three-dimensional space–time are applied to climate model simulations and tree-ring-based reconstructions of hydroclimate over the Northern Hemisphere extratropics for the past 1000 years, as well as twenty-first-century projections. Analyzing reconstructed and simulated drought in this context provides a paleoclimate constraint on the spatiotemporal characteristics of simulated droughts. Climate models project that there will be large increases in the persistence and severity of droughts over the coming century, but with little change in their spatial extent. Nevertheless, climate models exhibit biases in the spatiotemporal characteristics of persistent and severe droughts over parts of the Northern Hemisphere. We use the paleoclimate record and results from a linear inverse modeling-based framework to conclude that climate models underestimate the range of potential future hydroclimate states. Complicating this picture, however, are divergent changes in the characteristics of persistent and severe droughts when quantified using different hydroclimate metrics. Collectively our results imply that these divergent responses and the aforementioned biases must be better understood if we are to increase confidence in future hydroclimate projections. Importantly, the novel framework presented herein can be applied to other climate features to robustly describe their spatiotemporal characteristics and provide constraints on future changes to those characteristics.

Global climate model projections suggest that 21st century climate change will bring significant drying in the terrestrial midlatitudes. Recent glacier modeling suggests that runoff from glaciers will continue to provide substantial freshwater in many drainage basins, though the supply will generally diminish throughout the century. In the absence of dynamic glacier ice within global climate models (GCMs), a comprehensive picture of future drought conditions in glaciated regions has been elusive. We evaluate glacial buffering of droughts in the Standardized Precipitation-Evapotranspiration Index (SPEI), which we calculate by combining CMIP5 climate model output with glacial runoff projections from GloGEM.We find that accounting for glacial runoff tends to increase multi-model ensemble mean SPEI (wetter baseline) and reduce drought frequency and severity, even in basins with glacier cover of

SignificanceTwenty-first century trends in hydroclimate are so large that future average conditions will, in most cases, fall into the range of what we would today consider extreme drought or pluvial states. Using large climate model ensembles, we remove the background trend and find that the risk of droughts and pluvials relative to that (changing) baseline is fairly similar to the 20th century risk. By continually adapting to long-term background changes, these risks could therefore perhaps be minimized. However, increases in the frequency of extremely wet and dry years are still present even after removing the trend, indicating that sustainably managing hydroclimate-driven risks in a warmer world will face increasingly difficult challenges., Proceedings of the National Academy of Sciences of the United States of America, 119 (12), ISSN:0027-8424, ISSN:1091-6490

*This article is now published, and freely available from Journal of Climate at https://doi.org/10.1175/JCLI-D-21-0190.1*Characterising variability in the global water cycle is fundamental to predicting impacts of future climate change; understanding the role of the Pacific Walker circulation (PWC) in the regional expression of global water cycle changes is critical to understanding this variability. Water isotopes are ideal tracers of the role of the PWC in global water cycling, because they retain information about circulation-dependent processes including moisture source, transport, and delivery. We collated publicly-available measurements of precipitation δ18O (δ18OP), and used novel data processing techniques to synthesise long (34-year), globally-distributed composite records from temporally discontinuous δ18OP measurements. We investigated relationships between global-scale δ18OP variability and PWC strength, as well as other possible drivers of global δ18OP variability—including the El Niño Southern Oscillation (ENSO) and global mean temperature—and used isotope-enabled climate model simulations to assess potential biases arising from uneven geographical distribution of the observations or our data processing methodology. Co-variability underlying the δ18OP composites is more strongly correlated with the PWC (r = 0.74) than any other index of climate variability tested. We propose that the PWC imprint in global δ18OP arises from multiple complementary processes, including PWC-related changes in moisture source and transport length, and a PWC- or ENSO-driven ‘amount effect’ in tropical regions. The clear PWC imprint in global δ18OP implies a strong PWC influence on the regional expression of global water cycle variability on interannual to decadal timescales, and hence that uncertainty in the future state of the PWC translates to uncertainties in future changes in the global water cycle.

Thirty years of satellite-altimeter measurements show that rates of sea level rise are increasing across much of the global ocean. Such sea-level acceleration is particularly pronounced along the U.S. Gulf of Mexico coastline. Here we use model and observational data to identify the underlying mechanisms responsible for the enhanced rates of coastal sea-level rise in this region. Specifically, we quantify that subsurface warming in the Gulf of Mexico contributes importantly to sea-level rise at the coast. Using the Estimating the Circulation and Climate of the Ocean (ECCO) state estimate, we find changes in ocean bottom pressure are the main contributor to coastal sea-level changes in this region on inter-annual to decadal timescales.These ocean bottom pressure changes reflect both a net mass flux into the Gulf, but more importantly a redistribution of mass within the Gulf, which can be understood as an isostatic ocean response to warming of the Gulf of Mexico below the seasonal mixed layer. The nature of this response is shaped by basin geometry and the depth of warming. This relationship, between ocean bottom pressure at the coast and subsurface warming over the deep Gulf of Mexico, is then tested using observations of ocean bottom pressure from the Gravity Recovery and Climate Experiment (GRACE), coastal relative sea level from tide gauge measurements, sea-surface height from altimetry, and Argo profiles of upper ocean temperature and salinity. Results show that changes in coastal ocean bottom pressure predicted from observed subsurface warming explain a dominant fraction of observed coastal sea-level changes. For example, at St. Petersburg, Florida over the 2008-2017 period, we find subsurface-warming-driven ocean-mass-redistribution effects account for ~50% of the observed coastal sea-level trend — a greater fraction than that due to mass flux into the Gulf. This analysis identifies a physical mechanism by which coastal sea level responds to open-ocean subsurface warming. It motivates future studies of the open-ocean influence on coastal sea level in other regions.

Global climate model projections suggest that 21st century climate change will bring significant drying in the terrestrial midlatitudes. Recent glacier modeling suggests that runoff from glaciers will continue to provide substantial freshwater in many drainage basins, though the supply will generally diminish throughout the century. In the absence of dynamic glacier ice within global climate models (GCMs), a comprehensive picture of future hydrological drought conditions in glaciated regions has been elusive. Here, we leverage the results of existing GCM simulations and a global glacier model to evaluate glacial buffering of droughts in the Standardized Precipitation-Evapotranspiration Index (SPEI). We compute one baseline version of the SPEI and one version modified to account for glacial runoff changing over time, and we compare the two for each of 56 large-scale glaciated basins worldwide. We find that accounting for glacial runoff tends to increase the multi-model ensemble mean SPEI and reduce drought frequency and severity, even in basins with relatively little ( %) glacier cover. When glacial runoff is included in the SPEI, the number of droughts is reduced in 40 of 56 basins and the average drought severity is reduced in 53 of 56 basins, with similar counts in each time period we study. Glacial drought buffering persists even as glacial runoff is projected to decline through the 21st century. Results are similar under representative concentration pathway (RCP) 4.5 and 8.5 emissions scenarios, though results for the higher-emissions RCP 8.5 scenario show wider multi-model spread (uncertainty) and greater incidence of decreasing buffering later in the century. A k-means clustering analysis shows that glacial drought buffering is strongest in moderately glaciated, arid basins.

Reconstruction of the North Atlantic jet stream (NAJ) presents a critical, albeit largely unconstrained, paleoclimatic target. Models suggest northward migration and changing variance of the NAJ under 21st-century warming scenarios, but assessing the significance of such projections is hindered by a lack of long-term observations. Here, we incorporate insights from an ensemble of last-millennium water isotope–enabled climate model simulations and a wide array of mean annual water isotope ([Formula: see text] O) and annually accumulated snowfall records from Greenland ice cores to reconstruct North Atlantic zonal-mean zonal winds back to the 8th century CE. Using this reconstruction we provide preobservational constraints on both annual mean NAJ position and intensity to show that late 20th- and early 21st-century NAJ variations were likely not unique relative to natural variability. Rather, insights from our 1,250 year reconstruction highlight the overwhelming role of natural variability in thus far masking the response of midlatitude atmospheric dynamics to anthropogenic forcing, consistent with recent large-ensemble transient modeling experiments. This masking is not projected to persist under high greenhouse gas emissions scenarios, however, with model projected annual mean NAJ position emerging as distinct from the range of reconstructed natural variability by as early as 2060 CE.

Atmospheric rivers (ARs) effect inland hydrological impacts related to extreme precipitation. However, little is known about the possible coastal hazards associated with these events. Here we eluci...

The hydroclimate of the southwest United States (SWUS) is influenced by the tropical Pacific Ocean, particularly the phase of the El Nino/Southern Oscillation (ENSO), via teleconnections, wh...

Changes in the strength of the Pacific Walker circulation (PWC) can have a significant impact on global mean surface temperatures, as well as regional temperature, precipitation, and extreme weather events far beyond the tropical Pacific. Understanding PWC variability is therefore important for constraining future climate. But observational records of the PWC are short, and single-site proxy records for changes in the strength of the PWC during the last millennium offer contrasting interpretations. This leaves a critical gap in our understanding of PWC variability on the decadal to centennial timescales relevant to future climate change.Falster et al. (in prep.) demonstrated that the PWC is strongly imprinted in modern global precipitation δ18O (δ18OP). This relationship arises via multiple complementary mechanisms, including but not limited to ENSO dynamics. We exploit this relationship to reconstruct changes in the strength of the PWC over the past millennium, using six different statistical and machine learning reconstruction methods in conjunction with a globally-distributed network of palaeo-δ18OP records (Konecky et al. 2020). Although δ18OP from a relatively small number of locations explains a large proportion of PWC variance in the calibration interval, we use a larger network of sites because larger networks are less susceptible to non-stationary teleconnections or non-signal biases than individual sites or smaller networks. Preliminary results indicate that reconstructed PWC variability is coherent across methods, particularly for the past 400 years. Our reconstructions are also robust to both the calibration window used, and the particular palaeo-δ18OP records included in the reconstruction. This provides confidence that our network comprises sufficient proxy timeseries i.e. that we successfully extracted the common underlying climate signal (the PWC) from site-specific information inherent in individual palaeo-δ18OP records. Thus, we are confident that our reconstruction of changes in the strength of the PWC through the last millennium is robust, and it will therefore help to constrain the PWC’s long-term internal variability and sensitivity to external forcing.References:Falster, G. M., B. Konecky, M. Madhavan, S. Coats, S. Stevenson. 2021. “Imprint of the Pacific Walker circulation in global precipitation δ18O”. In preparation for Journal of Climate. Konecky, B. L., N. P. McKay, O. V. Churakova (Sidorova), L. Comas-Bru, E. P. Dassié, K. L. DeLong, G. M. Falster, et al. 2020. “The Iso2k Database: A Global Compilation of Paleo-δ18O and δ2H Records to Aid Understanding of Common Era Climate.” ESSD. https://doi.org/10.5194/essd-2020-5.

Attribution studies have identified a robust anthropogenic fingerprint in increased 21st century wildfire risk. However, the risks associated with individual aspects of anthropogenic aerosol and greenhouse gases (GHG) emissions, biomass burning and land use/land cover change remain unknown. Here, we use new climate model large ensembles isolating these influences to show that GHG-driven increases in extreme fire weather conditions have been balanced by aerosol-driven cooling throughout the 20th century. This compensation is projected to disappear due to future reductions in aerosol emissions, causing unprecedented increases in extreme fire weather risk in the 21st century as GHGs continue to rise. Changes to temperature and relative humidity drive the largest shifts in extreme fire weather conditions; this is particularly apparent over the Amazon, where GHGs cause a seven-fold increase by 2080. Our results allow increased understanding of the interacting roles of anthropogenic stressors in altering the regional expression of future wildfire risk., Nature Communications, 12 (1), ISSN:2041-1723

The origins of uncertainty in climate projections have major consequences for the scientific and policy decisions made in response to climate change. Internal climate variability, for example, is an inherent uncertainty in the climate system that is undersampled by the multimodel ensembles used in most climate impacts research. Because of this, decision makers are left with the question of whether the range of climate projections across models is due to structural model choices, thus requiring more scientific investment to constrain, or instead is a set of equally plausible outcomes consistent with the same warming world. Similarly, many questions faced by scientists require a clear separation of model uncertainty and that arising from internal variability. With this as motivation and the renewed attention to large ensembles given planning for Phase 7 of the Coupled Model Intercomparison Project (CMIP7), we illustrate the scientific and policy value of the attribution and quantification of uncertainty from initial condition large ensembles, particularly when analyzed in conjunction with multimodel ensembles. We focus on how large ensembles can support regional‐scale robust adaptation decision‐making in ways multimodel ensembles alone cannot. We also acknowledge several recently identified problems associated with large ensembles, namely, that they are (1) resource intensive, (2) redundant, and (3) biased. Despite these challenges, we show, using examples from hydroclimate, how large ensembles provide unique information for the scientific and policy communities and can be analyzed appropriately for regional‐scale climate impacts research to help inform risk management in a warming world., Earth's Future, 8 (10), ISSN:2328-4277

Global climate model projections suggest that 21st century climate change will bring significant drying in the midlatitudes. Recent glacier modeling suggests that runoff from glaciers will continue...

Global climate model projections suggest that 21st century climate change will bring significant drying in the midlatitudes. Recent glacier modeling suggests that runoff from glaciers will continue...

Global climate model projections suggest that 21st century climate change will bring significant drying in the midlatitudes. Recent glacier modeling suggests that runoff from glaciers will continue...

Drought has severe consequences for humans and their environment, yet we have a limited understanding of the drivers of drought across the full range of time scales on which it occurs. Here, the atmosphere and ocean conditions that drive this continuum of drought variability in southwestern North America (SWNA) are studied using the latest observationally based products, paleoclimate reconstructions, and state-of-the-art Earth system model simulations of the last millennium. A novel application of the self-organizing maps (SOM) methodology allows for a visualization of the continuum of climate states coinciding with thousands of droughts of varying lengths in last millennium simulations from the Community Earth System Model (CESM), the Goddard Institute for Space Studies Model E2-R (GISS E2-R), and eight other members from phase 5 of the Coupled Model Intercomparison Project (CMIP5). It is found that most droughts are associated with a cool Pacific decadal oscillation (PDO) pattern, but persistent droughts can coincide with a variety of ocean–atmosphere states, including time periods showing a warm PDO or weak ocean–atmosphere anomalies. Many CMIP5 models simulate similar SWNA teleconnection patterns, but the SOM analysis demonstrates that models simulate different continuums of ocean–atmosphere states coinciding with droughts of different lengths, suggesting fundamental differences in their drought dynamics. These findings have important implications for our understanding and simulation of the drivers of persistent drought, and for their potential predictability.

Reconstructions of sea surface temperature (SST) based on instrumental observations suggest that the equatorial Pacific zonal SST gradient has increased over the twentieth century. While this increase is suggestive of the ocean dynamical thermostat mechanism of Clement et al., observations of a concurrent weakening of the zonal atmospheric (Walker) circulation are not. Here we show, using heat and momentum budget calculations on an ocean reanalysis dataset, that a seasonal weakening of the zonal atmospheric circulation is in fact consistent with cooling in the eastern equatorial Pacific (EEP) and thus an increase in the zonal SST gradient. This cooling is driven by a strengthening Equatorial Undercurrent (EUC) in response to decreased upper-ocean westward momentum associated with weakening equatorial zonal wind stress. This process can help to reconcile the seemingly contradictory twentieth-century trends in the tropical Pacific atmosphere and ocean. Moreover, it is shown that coupled general circulation models (CGCMs) do not correctly simulate this process; we identify a systematic bias in the relationship between changes in equatorial surface zonal wind stress in the EEP and EUC strength that may help to explain why observations and CGCMs have opposing trends in the zonal SST gradient over the twentieth century.

Multidecadal hydroclimate variability has been expressed as “megadroughts” (dry periods more severe and prolonged than observed over the twentieth century) and corresponding “megapluvial” wet periods in many regions around the world. The risk of such events is strongly affected by modes of coupled atmosphere–ocean variability and by external impacts on climate. Accurately assessing the mechanisms for these interactions is difficult, since it requires large ensembles of millennial simulations as well as long proxy time series. Here, the Community Earth System Model (CESM) Last Millennium Ensemble is used to examine statistical associations among megaevents, coupled climate modes, and forcing from major volcanic eruptions. El Niño–Southern Oscillation (ENSO) strongly affects hydroclimate extremes: larger ENSO amplitude reduces megadrought risk and persistence in the southwestern United States, the Sahel, monsoon Asia, and Australia, with corresponding increases in Mexico and the Amazon. The Atlantic multidecadal oscillation (AMO) also alters megadrought risk, primarily in the Caribbean and the Amazon. Volcanic influences are felt primarily through enhancing AMO amplitude, as well as alterations in the structure of both ENSO and AMO teleconnections, which lead to differing manifestations of megadrought. These results indicate that characterizing hydroclimate variability requires an improved understanding of both volcanic climate impacts and variations in ENSO/AMO teleconnections.

The western United States was affected by several megadroughts during the last 1200 years, most prominently during the Medieval Climate Anomaly (MCA; 800 to 1300 CE). A null hypothesis is developed to test the possibility that, given a sufficiently long period of time, these events are inevitable and occur purely as a consequence of internal climate variability. The null distribution of this hypothesis is populated by a linear inverse model (LIM) constructed from global sea surface temperature anomalies and self-calibrated Palmer drought severity index data for North America. Despite being trained only on seasonal data from the late twentieth century, the LIM produces megadroughts that are comparable in their duration, spatial scale, and magnitude to the most severe events of the last 12 centuries. The null hypothesis therefore cannot be rejected with much confidence when considering these features of megadrought, meaning that similar events are possible today, even without any changes to boundary conditions. In contrast, the observed clustering of megadroughts in the MCA, as well as the change in mean hydroclimate between the MCA and the 1500–2000 period, are more likely to have been caused by either external forcing or by internal climate variability not well sampled during the latter half of the twentieth century. Finally, the results demonstrate that the LIM is a viable tool for determining whether paleoclimate reconstructions events should be ascribed to external forcings or to “out of sample” climate mechanisms, or if they are consistent with the variability observed during the recent period.

Historical trends in the tropical Pacific zonal sea surface temperature gradient (SST gradient) are analyzed herein using 41 climate models (83 simulations) and 5 observational datasets. A linear inverse model is trained on each simulation and observational dataset to assess if trends in the SST gradient are significant relative to the stationary statistics of internal variability, as would suggest an important role for external forcings such as anthropogenic greenhouse gasses. None of the 83 simulations have a positive trend in the SST gradient, a strengthening of the climatological SST gradient with more warming in the western than eastern tropical Pacific, as large as the mean trend across the 5 observational datasets. If the observed trends are anthropogenically forced, this discrepancy suggests that state-of-the-art climate models are not capturing the observed response of the tropical Pacific to anthropogenic forcing, with serious implications for confidence in future climate projections. There are caveats to this interpretation, however, as some climate models have a significant strengthening of the SST gradient between 1900-2013 C.E., though smaller in magnitude than the observational datasets, and the strengthening in 3 out of 5 observational datasets is insignificant. When combined with observational uncertainties and the possibility of centennial timescale internal variability not sampled by the LIM this suggests that confident validation of anthropogenic SST gradient trends in climate models will require further emergence of anthropogenic trends. Regardless, the differences in SST gradient trends between climate models and observational datasets are concerning and motivate the need for process-level validation of the atmosphere-ocean dynamics potentially relevant to climate change in the tropical Pacific.

Past cold climates are often thought to have been drier than today on land, which appears to conflict with certain recent studies projecting widespread terrestrial drying with near-future warming. However, other work has found that, over large portions of the continents, the conclusion of future drying versus wetting strongly depends on the physical property of interest. Here, it is shown that this also holds in simulations of the Last Glacial Maximum (LGM): the continents have generally wetter topsoils and higher values of common climate wetness metrics than in the preindustrial, as well as generally lower precipitation and ubiquitously lower photosynthesis (likely driven by the low CO2), with streamflow responses falling in between. Using a large existing global pollen and plant fossil compilation, it is also confirmed that LGM grasslands and open woodlands grew at many sites of present-day forest, seasonal forests at many sites of present-day rain forest, and so forth (116–144 sites out of 302), while changes in the opposite sense were very few (9–17 sites out of 302) and spatially confined. These vegetation changes resemble the model photosynthesis responses but not the hydroclimate responses, while published lake-level changes resemble the latter but not the former. Thus, confidence in both the model hydrologic and photosynthesis projections is increased, and there is no significant conflict. Instead, paleo- and modern climate researchers must carefully define “wetting” and “drying” and, in particular, should not assume hydrologic drying on the basis of vegetation decline alone or assume vegetation stress on the basis of declines in hydroclimatic indicators.

American Southwest (ASW) megadroughts represent decadal-scale periods of dry conditions, the near-term risks of which arise from natural low-frequency hydroclimate variability and anthropogenic forcing. A large single-climate-model ensemble indicates anthropogenic forcing increases near-term ASW megadrought risk by a factor of 100, however, accurate risk assessment remains a challenge. At the global-scale we find that anthropogenic forcing may alter the variability driving megadroughts over 55% of land-areas, undermining accurate assessments of their risk. For the remaining areas, current ensembles are too small to characterize megadroughts' driving variability. For example, constraining uncertainty in near-term ASW megadrought risk to 5 percentage points with high confidence requires 287 simulations. Such ensemble sizes are beyond current computational and storage resources and these limitations suggest that constraining errors in near-term megadrought risk projections with high confidence-even in places where underlying variability is stationary-is not currently possible.

During the Medieval Climate Anomaly (MCA), Western North America experienced episodes of intense aridity that persisted for multiple decades or longer. These megadroughts are well documented in many proxy records, but the causal mechanisms are poorly understood. General circulation models (GCMs) simulate megadroughts, but do not reproduce the temporal clustering of events during the MCA, suggesting they are not caused by the time history of volcanic or solar forcing. Instead, GCMs generate megadroughts through (1) internal atmospheric variability, (2) sea-surface temperatures, and (3) land surface and dust aerosol feedbacks. While no hypothesis has been definitively rejected, and no GCM has accurately reproduced all features (e.g., timing, duration, and extent) of any specific megadrought, their persistence suggests a role for processes that impart memory to the climate system (land surface and ocean dynamics). Over the 21st century, GCMs project an increase in the risk of megadrought occurrence through greenhouse gas forced reductions in precipitation and increases in evaporative demand. This drying is robust across models and multiple drought indicators, but major uncertainties still need to be resolved. These include the potential moderation of vegetation evaporative losses at higher atmospheric [CO2], variations in land surface model complexity, and decadal to multidecadal modes of natural climate variability that could delay or advance onset of aridification over the the next several decades. Because future droughts will arise from both natural variability and greenhouse gas forced trends in hydroclimate, improving our understanding of the natural drivers of persistent multidecadal megadroughts should be a major research priority.

Plant wax hydrogen isotopic composition is commonly used to reconstruct the hydrogen isotopic composition of precipitation used by terrestrial vegetation. However, mangroves growing in coastal environments take up a mixture of freshwater and seawater. Biosynthetic fractionation (between source water and plant wax) differs between plant types and as a function of salinity, potentially complicating interpretations of past precipitation in coastal environments. In order to reconstruct Holocene hydrologic and ecologic changes archived within sediments from Blackwood Sinkhole on Abaco Island in The Bahamas, we adopt a multi-proxy approach using plant wax hydrogen isotopic composition (δ2H) to reconstruct paleohydrology, together with plant wax carbon isotopic composition (δ13Cwax), sterol biomarkers and pollen abundances to identify vegetation change. When pollen indicates a stable terrestrial plant community (2950–850 cal yrs BP), variations of δ2H values measured on the plant wax C28 n-alkanoic acid are interpreted in terms of precipitation isotope (δ2Hprecip) changes, with 2H-depletion from 2950 to ∼2100 cal yrs BP and ∼1700 to 1000 cal yrs BP. However, interpretation is complicated at 850 cal yrs BP, when δ2H values decrease (−50‰) concurrent with increased Laguncularia racemosa (white mangrove) and Conocarpus erectus (buttonwood mangrove), and the mangrove-derived biomarker, taraxerol. We develop a pollen-based correction for mangrove inputs, yielding reconstructed precipitation isotope estimates (δ2Hprecip-corr). Low δ2Hprecip-corr values are synchronous with increased abundance of pine pollen, both of which may indicate wetter conditions from 850 cal yrs BP to present. This study provides additional evidence that mangroves can complicate hydrologic reconstructions from n-alkyl terrestrial plant wax biomarkers, and that such complication can be removed by pollen-based correction. After correcting for mangrove inputs, we obtain estimates of δ2Hprecip-corr from −33 to +25‰ throughout the last 2950 years, with uncertainties on the order of 10–20‰.

The Caribbean islands are expected to see more frequent and severe droughts from reduced precipitation and increased evaporative demand due to anthropogenic climate change. Between 2013 and 2016, the Caribbean experienced a widespread drought due in part to El Niño in 2015–2016, but it is unknown whether its severity was exacerbated by anthropogenic warming. This work examines the role of recent warming on this drought, using a recently developed high‐resolution self‐calibrating Palmer Drought Severity Index data set. The resulting analysis suggest that anthropogenic warming accounted for ~15–17% of the drought's severity and ~7% of its spatial extent. These findings strongly suggest that climate model projected anthropogenic drying in the Caribbean is already underway, with major implications for the more than 43 million people currently living in this region., Key Points In 2013–2016, the Caribbean experienced its worst drought since 1950, which we named the Pan‐Caribbean droughtEnhanced evaporative demand due to anthropogenic warming contributed to 15–17% of Pan‐Caribbean drought severityAnthropogenic climate change has likely already enhanced drought risk in the Caribbean