Consistent multi-decadal variability in global temperature reconstructions and simulations over the Common Era

Limited waterpower contributed to rise of steam power in British "Cottonopolis"

The Industrial Revolution precipitated a pivotal shift from waterpower to coal-fueled steam power in British textile mills. Although it is now widely accepted that steam was chosen to power factories despite the availability of sufficient waterpower resources across most of Britain, the location and suitability of that waterpower during the early 19th century remain underexplored. Here, we employ quantitative fluvial geomorphology alongside historical climate data, factory records, and a catalog of over 26,000 mill sites to reveal that waterpower was abundant for most of early 19th century Britain, except in the central hub of British cotton production: Greater Manchester in the Mersey Basin. Our findings show that surging factory mechanization and overcrowding on key waterways in the Mersey Basin compounded waterpower scarcity arising from a drier 19th century climate. Widespread adoption of coal-fueled steam engines in certain key industrial centers of Britain was a strategy aimed at ameliorating some of the reduced reliability of waterpower. The fact that steam engines were frequently used in water-powered factories in many industrial regions until the third quarter of the 19th century to recirculate water to provide that power, or as a power supplement when waterpower availability was restricted, adds further weight to our argument. Rapid adoption of coal-powered steam engines reshaped the social and structural landscape of industrial work, firmly established Britain's prominence as an industrial powerhouse, and had lasting global industrial and environmental impacts.

Dual carbon and oxygen isotopes in Siberian tree rings as indicator of millennia sunshine duration changes

The current lack of information on past summer sunshine duration variability from annually resolved palaeoclimatological archives is hindering progress in the understanding and modelling of the earth climate system. We show that a combination of tree-ring carbon and oxygen isotopes from Siberia provides robust information on summer sunshine duration, which we use for an annual 1505-year reconstruction of July sunshine duration variability (1,5K-SIB-JSDR). We found that the Medieval maximum is 56 % higher than the average over 1505 years. Rapid and drastic decreases in sunshine duration up to 60 % correspond to major stratospheric volcanic eruptions. Grand Solar Minima and total sunspot numbers are also well preserved in the 1,5K-SIB-JSDR. Coherency with a global air temperature composite and spring Arctic Oscillation indicate that a large-scale climate signal is retained in our sunshine reconstruction.

Climate change triggered synchronous woody plants recruitment in the last two centuries in the treeline ecotone of the Northern Hemisphere

Climate change triggers several ecosystem responses, including woody plant encroachment. We analyse woody plant recruitment across the treeline ecotone (the forest-tundra ecotone) of the Northern Hemisphere (NH) over an extended period (1801-2010) and its relation with atmospheric CO2 and air temperature. We detected a synchronous trend of woody plant recruitment across the NH, indicating a major climatic and environmental change, triggered by a combination of CO2 fertilization and air temperature changes. The drivers of woody plant recruitment changed with time: CO2 fertilization was the main driver in the period 1801-1950, while air temperature was the main driver after 1950, despite the drastic acceleration of CO2 increase in the last decades. These data support the hypothesis that we are shifting from a fertilization-dominated to a warming-dominated period. The temporal patterns of woody plant recruitment are consistent with the occurrence of the 1980 regime shift, a major change occurred in the Earth's biophysical systems. Indeed, the recruitment drop promoted by the 1960s-1980s air cooling, was followed by an intensive recruitment increase triggered by the restart of air warming in the last decades. The largest sensitivity and fastest resilience of evergreen and Pinaceae to the restart of air warming allows to hypothesize that, among the woody plant functional and taxonomic groups, they could perform the largest expansion also in future decades.

Paleoclimate data assimilation with CLIMBER-X: An ensemble Kalman filter for the last deglaciation

Using the climate model CLIMBER-X, we present an efficient method for assimilating the temporal evolution of surface temperatures for the last deglaciation covering the period 22000 to 6500 years before the present. The data assimilation methodology combines the data and the underlying dynamical principles governing the climate system to provide a state estimate of the system, which is better than that which could be obtained using just the data or the model alone. In applying an ensemble Kalman filter approach, we make use of the advances in the parallel data assimilation framework (PDAF), which provides parallel data assimilation functionality with a relatively small increase in computation time. We find that the data assimilation solution depends strongly on the background evolution of the decaying ice sheets rather than the assimilated temperatures. Two different ice sheet reconstructions result in a different deglacial meltwater history, affecting the large-scale ocean circulation and, consequently, the surface temperature. We find that the influence of data assimilation is more pronounced on regional scales than on the global mean. In particular, data assimilation has a stronger effect during millennial warming and cooling phases, such as the Bølling-Allerød and Younger Dryas, especially at high latitudes with heterogeneous temperature patterns. Our approach is a step toward a comprehensive paleo-reanalysis on multi-millennial time scales, including incorporating available paleoclimate data and accounting for their uncertainties in representing regional climates.

Surface climate signals transmitted rapidly to deep North Atlantic throughout last millennium

Instrumental observations of subsurface ocean warming imply that ocean heat uptake has slowed 20th-century surface warming. We present high-resolution records from subpolar North Atlantic sediments that are consistent with instrumental observations of surface and deep warming/freshening and in addition reconstruct the surface-deep relation of the last 1200 years. Sites from ~1300 meters and deeper suggest an ~0.5 degrees celsius cooling across the Medieval Climate Anomaly to Little Ice Age transition that began ~1350 ± 50 common era (CE), whereas surface records suggest asynchronous cooling onset spanning ~600 years. These data suggest that ocean circulation integrates surface variability that is transmitted rapidly to depth by the Atlantic Meridional Ocean Circulation, implying that the ocean moderated Earth's surface temperature throughout the last millennium as it does today.

Forced changes in the Pacific Walker circulation over the past millennium

The Pacific Walker circulation (PWC) has an outsized influence on weather and climate worldwide. Yet the PWC response to external forcings is unclear1,2, with empirical data and model simulations often disagreeing on the magnitude and sign of these responses3. Most climate models predict that the PWC will ultimately weaken in response to global warming4. However, the PWC strengthened from 1992 to 2011, suggesting a significant role for anthropogenic and/or volcanic aerosol forcing5, or internal variability. Here we use a new annually resolved, multi-method, palaeoproxy-derived PWC reconstruction ensemble (1200-2000) to show that the 1992-2011 PWC strengthening is anomalous but not unprecedented in the context of the past 800 years. The 1992-2011 PWC strengthening was unlikely to have been a consequence of volcanic forcing and may therefore have resulted from anthropogenic aerosol forcing or natural variability. We find no significant industrial-era (1850-2000) PWC trend, contrasting the PWC weakening simulated by most climate models3. However, an industrial-era shift to lower-frequency variability suggests a subtle anthropogenic influence. The reconstruction also suggests that volcanic eruptions trigger El Niño-like PWC weakening, similar to the response simulated by climate models.

KAI2 Can Do: Karrikin Receptor Function in Plant Development and Response to Abiotic and Biotic Factors

The α/β hydrolase KARRIKIN INSENSITIVE 2 (KAI2) functions as a receptor for a yet undiscovered phytohormone, provisionally termed KAI2 ligand (KL). In addition, it perceives karrikin, a butenolide compound found in the smoke of burnt plant material. KAI2-mediated signaling is involved in regulating seed germination and in shaping seedling and adult plant morphology, both above and below ground. It also governs responses to various abiotic stimuli and stresses and shapes biotic interactions. KAI2-mediated signaling is being linked to an elaborate cross-talk with other phytohormone pathways such as auxin, gibberellin, abscisic acid, ethylene and salicylic acid signaling, in addition to light and nutrient starvation signaling. Further connections will likely be revealed in the future. This article summarizes recent advances in unraveling the function of KAI2-mediated signaling and its interaction with other signaling pathways.

A pseudoproxy emulation of the PAGES 2k database using a hierarchy of proxy system models

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.

Fennoscandian tree-ring anatomy shows a warmer modern than medieval climate

Earth system models and various climate proxy sources indicate global warming is unprecedented during at least the Common Era1. However, tree-ring proxies often estimate temperatures during the Medieval Climate Anomaly (950-1250 CE) that are similar to, or exceed, those recorded for the past century2,3, in contrast to simulation experiments at regional scales4. This not only calls into question the reliability of models and proxies but also contributes to uncertainty in future climate projections5. Here we show that the current climate of the Fennoscandian Peninsula is substantially warmer than that of the medieval period. This highlights the dominant role of anthropogenic forcing in climate warming even at the regional scale, thereby reconciling inconsistencies between reconstructions and model simulations. We used an annually resolved 1,170-year-long tree-ring record that relies exclusively on tracheid anatomical measurements from Pinus sylvestris trees, providing high-fidelity measurements of instrumental temperature variability during the warm season. We therefore call for the construction of more such millennia-long records to further improve our understanding and reduce uncertainties around historical and future climate change at inter-regional and eventually global scales.

Artificial intelligence achieves easy-to-adapt nonlinear global temperature reconstructions using minimal local data

Understanding monthly-to-annual climate variability is essential for adapting to future climate extremes. Key ways to do this are through analysing climate field reconstructions and reanalyses. However, producing such reconstructions can be limited by high production costs, unrealistic linearity assumptions, or uneven distribution of local climate records. Here, we present a machine learning-based non-linear climate variability reconstruction method using a Recurrent Neural Network that is able to learn from existing model outputs and reanalysis data. As a proof-of-concept, we reconstructed more than 400 years of global, monthly temperature anomalies based on sparse, realistically distributed pseudo-station data and show the impact of different training data sets. Our reconstructions show realistic temperature patterns and magnitude reproduction costing about 1 hour on a middle-class laptop. We highlight the method's capability in terms of mean statistics compared to more established methods and find that it is also suited to reconstruct specific climate events. This approach can easily be adapted for a wide range of regions, periods and variables.

Does climate change affect economic data?

This paper derives the seasonal factors from the US temperature, gasoline price, and fresh food price data sets using the Kalman state smoother and the principal component analysis. Seasonality in this paper is modeled by the autoregressive process and added to the random component of the time series. The derived seasonal factors show a common feature: their volatilities have increased over the last four decades. Climate change is undoubtedly reflected in the temperature data. The three data sets' similar patterns from the 1990s suggest that climate change may have affected the prices' volatility behavior.

Plutonium-based radiometric dating of rapidly accumulated sediments in the Sanyuan sinkhole, southern Chinese Loess Plateau

Radionuclides, such as ²¹⁰Pb, ¹³⁷Cs and ^239,240Pu, have been widely used for dating recent sediments in terrestrial and marine environments, while ¹²⁹I, as an important artificial radionuclide in the environment, is also a potential tracer for sediment dating and environmental process studies. However, they were not always successfully applied to sediment dating because of their different sources, half-lives, environmental behaviour and measurement techniques. The dating applicability of these nuclides in a sedimentary environment with rapid accumulation on land was investigated for sinkhole sediment from the southern Chinese Loess Plateau. Our results showed that ²¹⁰Pb and ¹³⁷Cs could not be adequately used for dating the sediments due to the difficulties in accurately measuring ¹³⁷Cs and excess ²¹⁰Pb (²¹⁰Pb_ex) signals caused by the dilution effect of rapid accumulation. ¹²⁹I is not an ideal dating tracer because of its multisource feature causing no remarkable peak value in the sediment cores. The depth distribution of ^239,240Pu in the sediment core showed a single peak corresponding to its maximum fallout in 1963 from the atmospheric nuclear weapons test, suggesting that Pu isotopes have significant advantages in dating recent sediments. The sensitive inductively coupled plasma-mass spectrometry (ICP-MS) measurement technique enables the determination of very low levels of ²³⁹Pu and ²⁴⁰Pu and makes ^239,240Pu a suitable tracer for dating the rapidly accumulated sediment. Based on the ^239,240Pu mass balance equation estimation and field observations, we proposed the water-eroded input from soil surrounding the sinkhole as another vital source of the sediments in addition to the aeolian contribution.

Revisiting the Holocene global temperature conundrum

Recent global temperature reconstructions for the current interglacial period (the Holocene, beginning 11,700 years ago) have generated contrasting trends. This Review examines evidence from indicators and drivers of global change, as inferred from proxy records and simulated by climate models, to evaluate whether anthropogenic global warming was preceded by a long-term warming trend or by global cooling. Multimillennial-scale cooling before industrialization requires extra climate forcing and major climate feedbacks that are not well represented in most climate models at present. Conversely, global warming before industrialization challenges proxy-based reconstructions of past climate. The resolution of this conundrum has implications for contextualizing post-industrial warming and for understanding climate sensitivity to several forcings and their attendant feedbacks, including greenhouse gases. From a large variety of available evidence, we find support for a relatively mild millennial-scale global thermal maximum during the mid-Holocene, but more research is needed to firmly resolve the conundrum and to advance our understanding of slow-moving climate variability.

Is there a link between the length of the solar cycle and Earth’s temperature?

The Sun provides most of external energy to Earth’s system and thus has the potential of influencing it. Various studies reported a correlation between the solar cycle length and the northern hemisphere temperatures on Earth. Here, we reassess the cycle length record by incorporating the newly revised and updated sunspot number series as well as plage area composite, before comparing it to Earth temperature records. We find that cycle length series constructed from sunspot and plage data exhibit the same behaviour, both showing a downward trend after 1940. Our results suggest that the agreement between solar cycle lengths and temperatures found earlier is an artefact of (1) some arbitrary choices made by those studies when constructing the cycle length series as well as (2) a rather short time interval, to which the analyses were restricted. When considering the entire period of reliable sunspot and temperature data, these records diverge before about 1870 and after 1960. We also find a poor agreement between Earth temperatures and cycle length when using plage areas instead of sunspot data to derive cycle lengths. Our result of the divergence between cycle length series and Earth’s temperature after 1960 implies that the cycle length cannot be used to support a solar origin for the warming on Earth over the last 5 decades.

Emerging biological archives can reveal ecological and climatic change in Antarctica

Anthropogenic climate change is causing observable changes in Antarctica and the Southern Ocean including increased air and ocean temperatures, glacial melt leading to sea-level rise and a reduction in salinity, and changes to freshwater water availability on land. These changes impact local Antarctic ecosystems and the Earth's climate system. The Antarctic has experienced significant past environmental change, including cycles of glaciation over the Quaternary Period (the past ~2.6 million years). Understanding Antarctica's paleoecosystems, and the corresponding paleoenvironments and climates that have shaped them, provides insight into present day ecosystem change, and importantly, helps constrain model projections of future change. Biological archives such as extant moss beds and peat profiles, biological proxies in lake and marine sediments, vertebrate animal colonies, and extant terrestrial and benthic marine invertebrates, complement other Antarctic paleoclimate archives by recording the nature and rate of past ecological change, the paleoenvironmental drivers of that change, and constrain current ecosystem and climate models. These archives provide invaluable information about terrestrial ice-free areas, a key location for Antarctic biodiversity, and the continental margin which is important for understanding ice sheet dynamics. Recent significant advances in analytical techniques (e.g., genomics, biogeochemical analyses) have led to new applications and greater power in elucidating the environmental records contained within biological archives. Paleoecological and paleoclimate discoveries derived from biological archives, and integration with existing data from other paleoclimate data sources, will significantly expand our understanding of past, present, and future ecological change, alongside climate change, in a unique, globally significant region.

Separating internal and externally forced contributions to global temperature variability using a Bayesian stochastic energy balance framework

Earth's temperature variability can be partitioned into internal and externally forced components. Yet, underlying mechanisms and their relative contributions remain insufficiently understood, especially on decadal to centennial timescales. Important reasons for this are difficulties in isolating internal and externally forced variability. Here, we provide a physically motivated emulation of global mean surface temperature (GMST) variability, which allows for the separation of internal and external variations. To this end, we introduce the "ClimBayes" software package, which infers climate parameters from a stochastic energy balance model (EBM) with a Bayesian approach. We apply our method to GMST data from temperature observations and 20 last millennium simulations from climate models of intermediate to high complexity. This yields the best estimates of the EBM's forced and forced + internal response, which we refer to as emulated variability. The timescale-dependent variance is obtained from spectral analysis. In particular, we contrast the emulated forced and forced + internal variance on interannual to centennial timescales with that of the GMST target. Our findings show that a stochastic EBM closely approximates the power spectrum and timescale-dependent variance of GMST as simulated by modern climate models. Small deviations at interannual timescales can be attributed to the simplified representation of internal variability and, in particular, the absence of (pseudo-)oscillatory modes in the stochastic EBM. Altogether, we demonstrate the potential of combining Bayesian inference with conceptual climate models to emulate statistics of climate variables across timescales.

Tropical volcanoes synchronize eastern Canada with Northern Hemisphere millennial temperature variability

Although global and Northern Hemisphere temperature reconstructions are coherent with climate model simulations over the last millennium, reconstructed temperatures tend to diverge from simulations at smaller spatial scales. Yet, it remains unclear to what extent these regional peculiarities reflect region-specific internal climate variability or inadequate proxy coverage and quality. Here, we present a high-quality, millennial-long summer temperature reconstruction for northeastern North America, based on maximum latewood density, the most temperature-sensitive tree-ring proxy. Our reconstruction shows that a large majority (31 out of 44) of the coldest extremes can be attributed to explosive volcanic eruptions, with more persistent cooling following large tropical than extratropical events. These forced climate variations synchronize regional summer temperatures with hemispheric reconstructions and simulations at the multidecadal time scale. Our study highlights that tropical volcanism is the major driver of multidecadal temperature variations across spatial scales.

A maximum latewood density based summer temperature reconstruction from eastern Canada shows recent warming is unprecedented over 1246 years, and tropical volcanism synchronizes regional and hemispheric summer temperatures at the multidecadal time scale.

Drivers of Last Millennium Antarctic Climate Evolution in an Ensemble of Community Earth System Model Simulations

Improved understanding of the drivers of climate variability, particularly over the last millennium, and its influence on Antarctic ice melt have important implications for projecting ice sheet resilience in a changing climate. Here, we investigated the variability in Antarctic climate and sea ice extent during the last millennium (850–1850 CE) by comparing paleoenvironmental reconstructions with simulations from the Community Earth System Model Last Millennium Ensemble (CESM-LME). Atmospheric and oceanic response to external forcing in CESM-LME simulations typically take the form of an Antarctic dipole: cooling over most of Antarctica and warming east of the Antarctic Peninsula. This configuration is also observed in ice core records. Unforced variability and a dipole response to large volcanic eruptions contribute to weaker cooling in the Antarctic than the Arctic, consistent with the absence of a strong volcanic signal in Antarctic ice core records. The ensemble does not support a clear link between the dipole pattern and baseline shifts in the Southern Annular Mode and El Niño-Southern Oscillation proposed by some paleoclimate reconstructions. Our analysis provides a point of comparison for paleoclimate reconstructions and highlights the role of internal climate variability in driving modeled last millennium climate evolution in the Antarctic.

Towards the Third Millennium Changes in Siberian Triple Tree-Ring Stable Isotopes

Significant air temperature and precipitation changes have occurred since the 2000s in vulnerable Siberian subarctic regions and urged updates of available chronologies towards the third millennium. It is important to better understand recent climatic changes compared to the past decades, centuries and even millennia. In this study, we present the first annually resolved triple tree-ring isotope dataset (δ13C, δ18O and δ2H) for the eastern part of the Taimyr Peninsula (TAY) and northeastern Yakutia (YAK) from 1900 to 2021. We found that the novel and largely unexplored δ2H of larch tree-ring cellulose was linked significantly with δ18O for the YAK site, which was affected by averaged April–June air temperatures and evaporation. Simulated by the Land Surface Processes and Exchanges (LPX-Bern 1.0) model, the water fraction per year for soil depths at 0–20 and 20–30 cm was significantly linked with the new eco-hydrological tree-ring δ2H data. Our results suggest increasing evapotranspiration and response of trees’ water relation to rising thaw water uptake from lower (20–30 cm) soil depth. A positive effect of July air temperature on tree-ring δ18O and a negative impact of July precipitation were found, indicating dry conditions. The δ13C in larch tree-ring cellulose for both sites showed negative correlations with July precipitation and relative humidity, confirming dry environmental conditions towards the third millennium.

Modern aridity in the Altai-Sayan mountain range derived from multiple millennial proxies

Temperature and precipitation changes are crucial for larch trees growing at high-elevation sites covered by permafrost in the Altai-Sayan mountain range (ASMR). To contextualize the amplitude of recent climate fluctuations, we have to look into the past by analyzing millennial paleoclimatic archives recording both temperature and precipitation. We developed annually resolved 1500-year tree-ring cellulose chronologies (δ¹³C_cell, δ¹⁸O_cell), and used these new records to reconstruct the variability in local summer precipitation and air temperature. We combined our new local reconstructions with existing paleoclimatic archives available for the Altai. The data show a strong decreasing trend by ca. 49% in regional summer precipitation, along with a regional summer temperature increase towards the twenty-first century, relative to the preceding 1500 years. Modern dry conditions (1966–2016 CE) in the ASMR are the result of simultaneous summer warming and decreased precipitation. Our new reconstructions also demonstrate that climate change in the ASMR is much stronger compared to the global average.

A decade of cold Eurasian winters reconstructed for the early 19th century

Annual-to-decadal variability in northern midlatitude temperature is dominated by the cold season. However, climate field reconstructions are often based on tree rings that represent the growing season. Here we present cold-season (October-to-May average) temperature field reconstructions for the northern midlatitudes, 1701-1905, based on extensive phenological data (freezing and thawing dates of rivers, plant observations). Northern midlatitude land temperatures exceeded the variability range of the 18th and 19th centuries by the 1940s, to which recent warming has added another 1.5 °C. A sequences of cold winters 1808/9-1815/6 can be explained by two volcanic eruptions and unusual atmospheric flow. Weak southwesterlies over Western Europe in early winter caused low Eurasian temperatures, which persisted into spring even though the flow pattern did not. Twentieth century data and model simulations confirm this persistence and point to increased snow cover as a cause, consistent with sparse information on Eurasian snow in the early 19th century.

A cold season climate reconstruction for the northern midlatitudes based on freezing and thawing dates of rivers shows a cold spell 1808/9-1815/6 affecting Eurasia. In addition to two volcanic eruptions, increased snow cover played an important role.

495-Year Wood Anatomical Record of Siberian Stone Pine (Pinus sibirica Du Tour) As Climatic Proxy on the Timberline

The application of quantitative wood anatomy (QWA) in dendroclimatic analysis offers deep insight into the climatic effect on tree-ring formation, which is crucial in understanding the forests’ response to climate change. However, interrelations between tree-ring traits should be accounted to separate climatic signals recorded during subsequent stages of cell differentiation. The study was conducted in the South Siberian alpine timberline on Pinus sibirica Du Tour, a species considered unpromising in dendroclimatology. Relationships between tree-ring width, cell number N, mean and maximum values of radial diameter D, and cell wall thickness (CWT) were quantified to obtain indexed anatomical chronologies. Exponential functions with saturation D(N) and CWT(N) were proposed, which explained 14–69% and 3–61% of their variability, respectively. Indexation unabated significance of the climatic signals but separated them within a season. Analysis of pointer years and climatic extremes revealed predominantly long-term climatogenic changes of P. sibirica radial growth and QWA and allowed to obtain QWA-based 11-year filtered reconstructions of vegetative season climatic characteristics (R2adj = 0.32–0.66). The revealed prevalence of low-frequency climatic reactions is probably explained by a strategy of slow accumulation and utilization of resources implemented by P. sibirica. It makes this species’ QWA a promising proxy for decadal climatic variations in various intra-seasonal timeframes.

Large-scale emergence of regional changes in year-to-year temperature variability by the end of the 21st century

Global warming is expected to not only impact mean temperatures but also temperature variability, substantially altering climate extremes. Here we show that human-caused changes in internal year-to-year temperature variability are expected to emerge from the unforced range by the end of the 21^st century across climate model initial-condition large ensembles forced with a strong global warming scenario. Different simulated changes in globally averaged regional temperature variability between models can be explained by a trade-off between strong increases in variability on tropical land and substantial decreases in high latitudes, both shown by most models. This latitudinal pattern of temperature variability change is consistent with loss of sea ice in high latitudes and changes in vegetation cover in the tropics. Instrumental records are broadly in line with this emerging pattern, but have data gaps in key regions. Paleoclimate proxy reconstructions support the simulated magnitude and distribution of temperature variability. Our findings strengthen the need for urgent mitigation to avoid unprecedented changes in temperature variability.

Probing the timescale dependency of local and global variations in surface air temperature from climate simulations and reconstructions of the last millennia

Earth's climate can be understood as a dynamical system that changes due to external forcing and internal couplings. Essential climate variables, such as surface air temperature, describe this dynamics. Our current interglacial, the Holocene (11 700 yr ago to today), has been characterized by small variations in global mean temperature prior to anthropogenic warming. However, the mechanisms and spatiotemporal patterns of fluctuations around this mean, called temperature variability, are poorly understood despite their socioeconomic relevance for climate change mitigation and adaptation. Here we examine discrepancies between temperature variability from model simulations and paleoclimate reconstructions by categorizing the scaling behavior of local and global surface air temperature on the timescale of years to centuries. To this end, we contrast power spectral densities (PSD) and their power-law scaling using simulated and observation-based temperature series of the last 6000 yr. We further introduce the spectral gain to disentangle the externally forced and internally generated variability as a function of timescale. It is based on our estimate of the joint PSD of radiative forcing, which exhibits a scale break around the period of 7 yr. We find that local temperature series from paleoclimate reconstructions show a different scaling behavior than simulated ones, with a tendency towards stronger persistence (i.e., correlation between successive values within a time series) on periods of 10 to 200 yr. Conversely, the PSD and spectral gain of global mean temperature are consistent across data sets. Our results point to the limitation of climate models to fully represent local temperature statistics over decades to centuries. By highlighting the key characteristics of temperature variability, we pave a way to better constrain possible changes in temperature variability with global warming and assess future climate risks.

A palaeoclimate proxy database for water security planning in Queensland Australia

Palaeoclimate data relating to hydroclimate variability over the past millennia have a vital contribution to make to the water sector globally. The water industry faces considerable challenges accessing climate data sets that extend beyond that of historical gauging stations. Without this, variability around the extremes of floods and droughts is unknown and stress-testing infrastructure design and water demands is challenging. User-friendly access to relevant palaeoclimate data is now essential, and importantly, an efficient process to determine which proxies are most relevant to a planning scenario, and geographic area of interest. This paper presents PalaeoWISE (Palaeoclimate Data for Water Industry and Security Planning) a fully integrated, and quality-assured database of proxy data extracted from data repositories and publications collated in Linked Paleo Data (LiPD) format. We demonstrate the application of the database in Queensland, one of Australia’s most hydrologically extreme states. The database and resultant hydroclimate correlations provides both the scientific community, and water resource managers, with a valuable resource to better manage for future climate changes.

Measurement(s)	climate
Technology Type(s)	digital curation
Factor Type(s)	proxy type • geographic location • temporal interval • environmental material
Sample Characteristic - Environment	climate system
Sample Characteristic - Location	Earth (planet)

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16607162

Robust detection of forced warming in the presence of potentially large climate variability

Climate warming is unequivocal and exceeds internal climate variability. However, estimates of the magnitude of decadal-scale variability from models and observations are uncertain, limiting determination of the fraction of warming attributable to external forcing. Here, we use statistical learning to extract a fingerprint of climate change that is robust to different model representations and magnitudes of internal variability. We find a best estimate forced warming trend of 0.8°C over the past 40 years, slightly larger than observed. It is extremely likely that at least 85% is attributable to external forcing based on the median variability across climate models. Detection remains robust even when evaluated against models with high variability and if decadal-scale variability were doubled. This work addresses a long-standing limitation in attributing warming to external forcing and opens up opportunities even in the case of large model differences in decadal-scale variability, model structural uncertainty, and limited observational records.

Increased risk of near term global warming due to a recent AMOC weakening

Some of the new generation CMIP6 models are characterised by a strong temperature increase in response to increasing greenhouse gases concentration¹. At first glance, these models seem less consistent with the temperature warming observed over the last decades. Here, we investigate this issue through the prism of low-frequency internal variability by comparing with observations an ensemble of 32 historical simulations performed with the IPSL-CM6A-LR model, characterized by a rather large climate sensitivity. We show that members with the smallest rates of global warming over the past 6-7 decades are also those with a large internally-driven weakening of the Atlantic Meridional Overturning Circulation (AMOC). This subset of members also matches several AMOC observational fingerprints, which are in line with such a weakening. This suggests that internal variability from the Atlantic Ocean may have dampened the magnitude of global warming over the historical era. Taking into account this AMOC weakening over the past decades means that it will be harder to avoid crossing the 2 °C warming threshold.

New climate models show a stronger warming with greenhouse gas emissions than is suggested by observations. Here, the authors argue that internal variability of the Atlantic Ocean may have dampened some of the recent warming, which could explain part of the disagreement between the newer models and observations.

Beyond the hockey stick: Climate lessons from the Common Era

I review the significant developments, current challenges, and prospective future directions in the subfield of paleoclimatology of the Common Era since the publication of the now iconic “hockey stick” curve by the author and collaborators more than two decades ago, with a focus on how paleoclimate information can inform our understanding of the impact of human-caused climate change.

More than two decades ago, my coauthors, Raymond Bradley and Malcolm Hughes, and I published the now iconic “hockey stick” curve. It was a simple graph, derived from large-scale networks of diverse climate proxy (“multiproxy”) data such as tree rings, ice cores, corals, and lake sediments, that captured the unprecedented nature of the warming taking place today. It became a focal point in the debate over human-caused climate change and what to do about it. Yet, the apparent simplicity of the hockey stick curve betrays the dynamicism and complexity of the climate history of past centuries and how it can inform our understanding of human-caused climate change and its impacts. In this article, I discuss the lessons we can learn from studying paleoclimate records and climate model simulations of the “Common Era,” the period of the past two millennia during which the “signal” of human-caused warming has risen dramatically from the background of natural variability.

Cleaner air reveals growing influence of climate on dissolved organic carbon trends in northern headwaters

Surface water browning, the result of increasing concentrations of dissolved organic matter (DOM), has been widespread in northern ecosystems in recent decades. Here, we assess a database of 426 undisturbed headwater lakes and streams in Europe and North America for evidence of trends in DOM between 1990 and 2016. We describe contrasting changes in DOM trends in Europe (decelerating) and North America (accelerating), which are consistent with organic matter solubility responses to declines in sulfate deposition. While earlier trends (1990-2004) were almost entirely related to changes in atmospheric chemistry, climatic and chemical drivers were equally important in explaining recent DOM trends (2002-2016). We estimate that riverine DOM export from northern ecosystems increased by 27% during the study period. Increased summer precipitation strengthened upward dissolved organic carbon trends while warming apparently damped browning. Our results suggest strong but changing influences of air quality and climate on the terrestrial carbon cycle, and on the magnitude of carbon export from land to water.

Extreme rainfall deficits were not the cause of recurring colonial era famines of southern Indian semi-arid regions

Using information contained in the eighteenth to twentieth century British administrative documents, preserved in the National Archives of India (NAI), we present a 218-year (1729–1947 AD) record of socioeconomic disruptions and human impacts (famines) associated with ‘rain failures’ that affected the semi-arid regions (SARs) of southern India. By mapping the southern Indian famine record onto long-term spatiotemporal measures of regional rainfall variability, we demonstrate that the SARs of southern India repeatedly experienced famines when annual rainfall reduced by ~ one standard deviation (1 SD), or more, from long-term averages. In other words, ‘rain failures’ listed in the colonial documents as causes of extreme socioeconomic disruptions, food shortages and human distress (famines) in the southern Indian SARs were fluctuations in precipitation well within the normal range of regional rainfall variability and not extreme rainfall deficits (≥ 3 SD). Our study demonstrates that extreme climate events were not necessary conditions for extreme socioeconomic disruptions and human impacts rendered by the colonial era famines in peninsular India. Based on our findings, we suggest that climate change risk assessement should consider the potential impacts of more frequent low-level anomalies (e.g. 1 SD) in drought prone semi-arid regions.

GPS-Based Multi-Temporal Variation in Precipitable Water over the Territory of Poland

An increase in temperature causes higher evaporation of water from water bodies; consequently, the water content in the atmosphere also increases. The precipitable water (PW), as the water content in the atmospheric air column, is therefore an important parameter to consider when studying climate change. The aim of this study was to analyse multi-annual precipitable water data derived from a dense Global Navigational Satellite Systems (GNSS) network. Twelve years of observations from over a hundred ASG-EUPOS stations were used to estimate changes in precipitation water values over Poland. The data were validated by comparison with the available radio-sounding data. The analysis of the GPS-based PW values showed an upward trend in the PW value of 0.078 mm/year. The spatio-temporal distribution of the mean PW values and their fluctuations over the years were studied and visualised in the form of maps. The results are congruent with the fact that Poland lies on the border of influence of both continental and oceanic climates. Our results are also consistent with other climate research concerning this region.

The influence of decision-making in tree ring-based climate reconstructions

Tree-ring chronologies underpin the majority of annually-resolved reconstructions of Common Era climate. However, they are derived using different datasets and techniques, the ramifications of which have hitherto been little explored. Here, we report the results of a double-blind experiment that yielded 15 Northern Hemisphere summer temperature reconstructions from a common network of regional tree-ring width datasets. Taken together as an ensemble, the Common Era reconstruction mean correlates with instrumental temperatures from 1794-2016 CE at 0.79 (p < 0.001), reveals summer cooling in the years following large volcanic eruptions, and exhibits strong warming since the 1980s. Differing in their mean, variance, amplitude, sensitivity, and persistence, the ensemble members demonstrate the influence of subjectivity in the reconstruction process. We therefore recommend the routine use of ensemble reconstruction approaches to provide a more consensual picture of past climate variability.

Common Era sea-level budgets along the U.S. Atlantic coast

Sea-level budgets account for the contributions of processes driving sea-level change, but are predominantly focused on global-mean sea level and limited to the 20th and 21st centuries. Here we estimate site-specific sea-level budgets along the U.S. Atlantic coast during the Common Era (0-2000 CE) by separating relative sea-level (RSL) records into process-related signals on different spatial scales. Regional-scale, temporally linear processes driven by glacial isostatic adjustment dominate RSL change and exhibit a spatial gradient, with fastest rates of rise in southern New Jersey (1.6 ± 0.02 mm yr-1). Regional and local, temporally non-linear processes, such as ocean/atmosphere dynamics and groundwater withdrawal, contributed between -0.3 and 0.4 mm yr-1 over centennial timescales. The most significant change in the budgets is the increasing influence of the common global signal due to ice melt and thermal expansion since 1800 CE, which became a dominant contributor to RSL with a 20th century rate of 1.3 ± 0.1 mm yr-1.

Towards a rigorous understanding of societal responses to climate change

A large scholarship currently holds that before the onset of anthropogenic global warming, natural climatic changes long provoked subsistence crises and, occasionally, civilizational collapses among human societies. This scholarship, which we term the 'history of climate and society' (HCS), is pursued by researchers from a wide range of disciplines, including archaeologists, economists, geneticists, geographers, historians, linguists and palaeoclimatologists. We argue that, despite the wide interest in HCS, the field suffers from numerous biases, and often does not account for the local effects and spatiotemporal heterogeneity of past climate changes or the challenges of interpreting historical sources. Here we propose an interdisciplinary framework for uncovering climate-society interactions that emphasizes the mechanics by which climate change has influenced human history, and the uncertainties inherent in discerning that influence across different spatiotemporal scales. Although we acknowledge that climate change has sometimes had destructive effects on past societies, the application of our framework to numerous case studies uncovers five pathways by which populations survived-and often thrived-in the face of climatic pressures.

Seasonal origin of the thermal maxima at the Holocene and the last interglacial

Proxy reconstructions from marine sediment cores indicate peak temperatures in the first half of the last and current interglacial periods (the thermal maxima of the Holocene epoch, 10,000 to 6,000 years ago, and the last interglacial period, 128,000 to 123,000 years ago) that arguably exceed modern warmth^1-3. By contrast, climate models simulate monotonic warming throughout both periods^4-7. This substantial model-data discrepancy undermines confidence in both proxy reconstructions and climate models, and inhibits a mechanistic understanding of recent climate change. Here we show that previous global reconstructions of temperature in the Holocene^1-3 and the last interglacial period⁸ reflect the evolution of seasonal, rather than annual, temperatures and we develop a method of transforming them to mean annual temperatures. We further demonstrate that global mean annual sea surface temperatures have been steadily increasing since the start of the Holocene (about 12,000 years ago), first in response to retreating ice sheets (12 to 6.5 thousand years ago), and then as a result of rising greenhouse gas concentrations (0.25 ± 0.21 degrees Celsius over the past 6,500 years or so). However, mean annual temperatures during the last interglacial period were stable and warmer than estimates of temperatures during the Holocene, and we attribute this to the near-constant greenhouse gas levels and the reduced extent of ice sheets. We therefore argue that the climate of the Holocene differed from that of the last interglacial period in two ways: first, larger remnant glacial ice sheets acted to cool the early Holocene, and second, rising greenhouse gas levels in the late Holocene warmed the planet. Furthermore, our reconstructions demonstrate that the modern global temperature has exceeded annual levels over the past 12,000 years and probably approaches the warmth of the last interglacial period (128,000 to 115,000 years ago).

Changing nutrient cycling in Lake Baikal, the world's oldest lake

Lake Baikal (Siberia) is the world’s oldest and deepest lake and a UNESCO World Heritage Site. Containing an exceptionally high level of biodiversity and endemism, in addition to a fifth of global freshwater not stored in ice sheets, the lake has been cited by UNESCO as the “most outstanding example of a freshwater ecosystem.” Using geochemical and climate data, we demonstrate that rates of nutrient supply to the lake’s photic zone have risen to unprecedented levels in the last 2,000 y through the 20th and 21st centuries. Linked to increases in wind speed enhancing deep ventilation, we show that these changes are capable of altering lake primary production and community dynamics, including the balance between endemic and cosmopolitan species.

Lake Baikal, lying in a rift zone in southeastern Siberia, is the world's oldest, deepest, and most voluminous lake that began to form over 30 million years ago. Cited as the “most outstanding example of a freshwater ecosystem” and designated a World Heritage Site in 1996 due to its high level of endemicity, the lake and its ecosystem have become increasingly threatened by both climate change and anthropogenic disturbance. Here, we present a record of nutrient cycling in the lake, derived from the silicon isotope composition of diatoms, which dominate aquatic primary productivity. Using historical records from the region, we assess the extent to which natural and anthropogenic factors have altered biogeochemical cycling in the lake over the last 2,000 y. We show that rates of nutrient supply from deep waters to the photic zone have dramatically increased since the mid-19th century in response to changing wind dynamics, reduced ice cover, and their associated impact on limnological processes in the lake. With stressors linked to untreated sewage and catchment development also now impacting the near-shore region of Lake Baikal, the resilience of the lake’s highly endemic ecosystem to ongoing and future disturbance is increasingly uncertain.

Evidence of unprecedented rise in growth synchrony from global tree ring records

Changes in the temporal coherence between populations, which can influence their stability, resilience and persistence, remain a critical uncertainty of climate change. Recent studies have documented increasing spatial synchrony between populations at continental scales and linked it to anthropogenic climate change. However, the lack of long-term and global baseline perspectives on spatial synchrony presents a challenge to understanding the importance of these trends. Here, we show a steady rise in the spatial synchrony of annual tree growth from a global tree ring database over the past 50 years that is consistent across continents, species and environmental conditions and is unprecedented for the past millennium. Increasing growth synchrony coincided with warming trends and potentially rising synchrony in the temperature records. We discuss the potential driving mechanisms and the limitations in the interpretation of this trend, and we propose that increasing mutual dependency on external factors (also known as Moran's effect) linked to rising global temperatures is the most likely driver of more homogeneous global growth dynamics.

Control Scheme of a Bidirectional Inductive Power Transfer System for Electric Vehicles Integrated into the Grid

Inductive power transfer (IPT) systems have become a very effective technology when charging the batteries of electric vehicles (EVs), with numerous research works devoted to this field in recent years. In the battery charging process, the EV consumes energy from the grid, and this concept is called Grid-to-Vehicle (G2V). Nevertheless, the EV can also be used to inject part of the energy stored in the battery into the grid, according to the so-called Vehicle-to-Grid (V2G) scheme. This bidirectional feature can be applied to a better development of distributed generation systems, thus improving the integration of EVs into the grid (including IPT-powered EVs). Over the past few years, some works have begun to pay attention to bidirectional IPT systems applied to EVs, focusing on aspects such as the compensation topology, the design of the magnetic coupler or the power electronic configuration. Nevertheless, the design of the control system has not been extensively studied. This paper is focused on the design of a control system applied to a bidirectional IPT charger, which can operate in both the G2V and V2G modes. The procedure design of the control system is thoroughly explained and classical control techniques are applied to tailor the control scheme. One of the advantages of the proposed control scheme is the robustness when there is a mismatch between the coupling factor used in the model and the real value. Moreover, the control system can be used to limit the peak value of the primary side current when this value increases, thus protecting the IPT system. Simulation results obtained with PSCADTM/EMTDCTM show the good performance of the overall system when working in both G2V and V2G modes, while experimental results validate the control system behavior in the G2V mode.

Evaluation of Historical CMIP6 Model Simulations of Seasonal Mean Temperature over Pakistan during 1970–2014

This work employed recent model outputs from coupled model intercomparison project phase six to simulate surface mean temperature during the June–July–August (JJA) and December–January–February (DJF) seasons for 1970–2014 over Pakistan. The climatic research unit (CRU TS4.03) dataset was utilized as benchmark data to analyze models’ performance. The JJA season exhibited the highest mean temperature, whilst DJF displayed the lowest mean temperature in the whole study period. The JJA monthly empirical cumulative distribution frequency (ECDF) range (26 to 28 °C) was less than that of DJF (7 to 10 °C) since JJA matched closely to CRU. The JJA and DJF seasons are warming, with higher warming trends in winters than in summers. On temporal scale, models performed better in JJA with overall low bias, low RMSE (root mean square error), and higher positive CC (correlation coefficient) values. DJF performance was undermined with higher bias and RMSE with weak positive correlation estimates. Overall, CanESM5, CESM2, CESM2-WACCM, GFDL-CM4, HadGEM-GC31-LL, MPI-ESM1-2-LR, MPI-ESM1-2-HR, and MRI-ESM-0 performed better for JJA and DJF.

Recent atmospheric drying in Siberia is not unprecedented over the last 1,500 years

Newly developed millennial δ¹³C larch tree-ring chronology from Siberia allows reconstruction of summer (July) vapor pressure deficit (VPD) changes in a temperature-limited environment. VPD increased recently, but does not yet exceed the maximum values reconstructed during the Medieval Warm Anomaly. The most humid conditions in the Siberian North were recorded in the Early Medieval Period and during the Little Ice Age. Increasing VPD under elevated air temperature affects the hydrology of these sensitive ecosystems by greater evapotranspiration rates. Further VPD increases will significantly affect Siberian forests most likely leading to drought and forest mortality even under additional access of thawed permafrost water. Adaptation strategies are needed for Siberian forest ecosystems to protect them in a warming world.

Holocene global mean surface temperature, a multi-method reconstruction approach

An extensive new multi-proxy database of paleo-temperature time series (Temperature 12k) enables a more robust analysis of global mean surface temperature (GMST) and associated uncertainties than was previously available. We applied five different statistical methods to reconstruct the GMST of the past 12,000 years (Holocene). Each method used different approaches to averaging the globally distributed time series and to characterizing various sources of uncertainty, including proxy temperature, chronology and methodological choices. The results were aggregated to generate a multi-method ensemble of plausible GMST and latitudinal-zone temperature reconstructions with a realistic range of uncertainties. The warmest 200-year-long interval took place around 6500 years ago when GMST was 0.7 °C (0.3, 1.8) warmer than the 19th Century (median, 5th, 95th percentiles). Following the Holocene global thermal maximum, GMST cooled at an average rate -0.08 °C per 1000 years (-0.24, -0.05). The multi-method ensembles and the code used to generate them highlight the utility of the Temperature 12k database, and they are now available for future use by studies aimed at understanding Holocene evolution of the Earth system.

Persistent warm Mediterranean surface waters during the Roman period

Reconstruction of last millennia Sea Surface Temperature (SST) evolution is challenging due to the difficulty retrieving good resolution marine records and to the several uncertainties in the available proxy tools. In this regard, the Roman Period (1 CE to 500 CE) was particularly relevant in the socio-cultural development of the Mediterranean region while its climatic characteristics remain uncertain. Here we present a new SST reconstruction from the Sicily Channel based in Mg/Ca ratios measured on the planktonic foraminifer Globigerinoides ruber. This new record is framed in the context of other previously published Mediterranean SST records from the Alboran Sea, Minorca Basin and Aegean Sea and also compared to a north Hemisphere temperature reconstruction. The most solid image that emerges of this trans-Mediterranean comparison is the persistent regional occurrence of a distinct warm phase during the Roman Period. This record comparison consistently shows the Roman as the warmest period of the last 2 kyr, about 2 °C warmer than average values for the late centuries for the Sicily and Western Mediterranean regions. After the Roman Period a general cooling trend developed in the region with several minor oscillations. We hypothesis the potential link between this Roman Climatic Optimum and the expansion and subsequent decline of the Roman Empire.

Selection of optimal proxy locations for temperature field reconstructions using evolutionary algorithms

In the Era of exponential data generation, increasing the number of paleoclimate records to improve climate field reconstructions might not always be the best strategy. By using pseudo-proxies from different model ensembles, we show how biologically-inspired artificial intelligence can be coupled with different reconstruction methods to minimize the spatial bias induced by the non-homogeneous distribution of available proxies. The results indicate that small subsets of records situated over representative locations can outperform the reconstruction skill of the full proxy network, even in more realistic pseudo-proxy experiments and observational datasets. These locations highlight the importance of high-latitude regions and major teleconnection areas to reconstruct annual global temperature fields and their responses to external forcings and internal variability. However, low frequency temperature variations such as the transition between the Medieval Climate Anomaly and the Little Ice Age are better resolved by records situated at lower latitudes. According to our idealized experiments a careful selection of proxy locations should be performed depending on the targeted time scale of the reconstructed field.

A global database of Holocene paleotemperature records

A comprehensive database of paleoclimate records is needed to place recent warming into the longer-term context of natural climate variability. We present a global compilation of quality-controlled, published, temperature-sensitive proxy records extending back 12,000 years through the Holocene. Data were compiled from 679 sites where time series cover at least 4000 years, are resolved at sub-millennial scale (median spacing of 400 years or finer) and have at least one age control point every 3000 years, with cut-off values slackened in data-sparse regions. The data derive from lake sediment (51%), marine sediment (31%), peat (11%), glacier ice (3%), and other natural archives. The database contains 1319 records, including 157 from the Southern Hemisphere. The multi-proxy database comprises paleotemperature time series based on ecological assemblages, as well as biophysical and geochemical indicators that reflect mean annual or seasonal temperatures, as encoded in the database. This database can be used to reconstruct the spatiotemporal evolution of Holocene temperature at global to regional scales, and is publicly available in Linked Paleo Data (LiPD) format.

How Much Human-Caused Global Warming Should We Expect with Business-As-Usual (BAU) Climate Policies? A Semi-Empirical Assessment

In order to assess the merits of national climate change mitigation policies, it is important to have a reasonable benchmark for how much human-caused global warming would occur over the coming century with “Business-As-Usual” (BAU) conditions. However, currently, policymakers are limited to making assessments by comparing the Global Climate Model (GCM) projections of future climate change under various different “scenarios”, none of which are explicitly defined as BAU. Moreover, all of these estimates are ab initio computer model projections, and policymakers do not currently have equivalent empirically derived estimates for comparison. Therefore, estimates of the total future human-caused global warming from the three main greenhouse gases of concern (CO2, CH4, and N2O) up to 2100 are here derived for BAU conditions. A semi-empirical approach is used that allows direct comparisons between GCM-based estimates and empirically derived estimates. If the climate sensitivity to greenhouse gases implies a Transient Climate Response (TCR) of ≥ 2.5 °C or an Equilibrium Climate Sensitivity (ECS) of ≥ 5.0 °C then the 2015 Paris Agreement’s target of keeping human-caused global warming below 2.0 °C will have been broken by the middle of the century under BAU. However, for a TCR < 1.5 °C or ECS < 2.0 °C, the target would not be broken under BAU until the 22nd century or later. Therefore, the current Intergovernmental Panel on Climate Change (IPCC) “likely” range estimates for TCR of 1.0 to 2.5 °C and ECS of 1.5 to 4.5 °C have not yet established if human-caused global warming is a 21st century problem.

Coupling of Indo-Pacific climate variability over the last millennium

The Indian Ocean Dipole (IOD) affects climate and rainfall across the world, and most severely in nations surrounding the Indian Ocean^1-4. The frequency and intensity of positive IOD events increased during the twentieth century⁵ and may continue to intensify in a warming world⁶. However, confidence in predictions of future IOD change is limited by known biases in IOD models⁷ and the lack of information on natural IOD variability before anthropogenic climate change. Here we use precisely dated and highly resolved coral records from the eastern equatorial Indian Ocean, where the signature of IOD variability is strong and unambiguous, to produce a semi-continuous reconstruction of IOD variability that covers five centuries of the last millennium. Our reconstruction demonstrates that extreme positive IOD events were rare before 1960. However, the most extreme event on record (1997) is not unprecedented, because at least one event that was approximately 27 to 42 per cent larger occurred naturally during the seventeenth century. We further show that a persistent, tight coupling existed between the variability of the IOD and the El Niño/Southern Oscillation during the last millennium. Indo-Pacific coupling was characterized by weak interannual variability before approximately 1590, which probably altered teleconnection patterns, and by anomalously strong variability during the seventeenth century, which was associated with societal upheaval in tropical Asia. A tendency towards clustering of positive IOD events is evident in our reconstruction, which-together with the identification of extreme IOD variability and persistent tropical Indo-Pacific climate coupling-may have implications for improving seasonal and decadal predictions and managing the climate risks of future IOD variability.

A Transformative Concept: From Data Being Passive Objects to Data Being Active Subjects

The exploitation of potential societal benefits of Earth observations is hampered by users having to engage in often tedious processes to discover data and extract information and knowledge. A concept is introduced for a transition from the current perception of data as passive objects (DPO) to a new perception of data as active subjects (DAS). This transition would greatly increase data usage and exploitation, and support the extraction of knowledge from data products. Enabling the data subjects to actively reach out to potential users would revolutionize data dissemination and sharing and facilitate collaboration in user communities. The three core elements of the transformative DAS concept are: (1) “intelligent semantic data agents” (ISDAs) that have the capabilities to communicate with their human and digital environment. Each ISDA provides a voice to the data product it represents. It has comprehensive knowledge of the represented product including quality, uncertainties, access conditions, previous uses, user feedbacks, etc., and it can engage in transactions with users. (2) A knowledge base that constructs extensive graphs presenting a comprehensive picture of communities of people, applications, models, tools, and resources and provides tools for the analysis of these graphs. (3) An interaction platform that links the ISDAs to the human environment and facilitates transaction including discovery of products, access to products and derived knowledge, modifications and use of products, and the exchange of feedback on the usage. This platform documents the transactions in a secure way maintaining full provenance.

Late Holocene Glacial Fluctuations of Schiaparelli Glacier at Monte Sarmiento Massif, Tierra del Fuego (54°24′S)

The Magallanes–Tierra del Fuego region, Southern Patagonia (53–56°S) features a plethora of fjords and remote and isolated islands, and hosts several thousand glaciers. The number of investigated glaciers with respect to the multiple Neoglacial advances is based on a few individual studies and is still fragmentary, which complicates the interpretation of the glacial dynamics in the southernmost part of America. Schiaparelli Glacier (54°24′S, 70°50′W), located at the western side of the Cordillera Darwin, was selected for tree-ring-based and radiocarbon dating of the glacial deposits. One focus of the study was to address to the potential dating uncertainties that arise by the use of Nothofagus spp. as a pioneer species. A robust analysis of the age–height relationship, missing the pith of the tree (pith offset), and site-specific ecesis time revealed a total uncertainty value of ±59 years. Three adjacent terminal moraines were identified, which increasingly tapered towards the glacier, with oldest deposition dates of 1749 ± 5 CE, 1789 ± 5 CE, and 1867 ± 5 CE. Radiocarbon dates of trunks incorporated within the terminal moraine system indicate at least three phases of cumulative glacial activity within the last 2300 years that coincide with the Neoglacial phases of the Southern Patagonian Icefield and adjacent mountain glaciers. The sub-recent trunks revealed the first evidence of a Neoglacial advance between ~600 BCE and 100 CE, which so far has not been substantiated in the Magallanes–Tierra del Fuego region.