Reconstructing past climate from noisy data

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.

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.

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.

No evidence for globally coherent warm and cold periods over the preindustrial Common Era

Earth's climate history is often understood by breaking it down into constituent climatic epochs¹. Over the Common Era (the past 2,000 years) these epochs, such as the Little Ice Age^2-4, have been characterized as having occurred at the same time across extensive spatial scales⁵. Although the rapid global warming seen in observations over the past 150 years does show nearly global coherence⁶, the spatiotemporal coherence of climate epochs earlier in the Common Era has yet to be robustly tested. Here we use global palaeoclimate reconstructions for the past 2,000 years, and find no evidence for preindustrial globally coherent cold and warm epochs. In particular, we find that the coldest epoch of the last millennium-the putative Little Ice Age-is most likely to have experienced the coldest temperatures during the fifteenth century in the central and eastern Pacific Ocean, during the seventeenth century in northwestern Europe and southeastern North America, and during the mid-nineteenth century over most of the remaining regions. Furthermore, the spatial coherence that does exist over the preindustrial Common Era is consistent with the spatial coherence of stochastic climatic variability. This lack of spatiotemporal coherence indicates that preindustrial forcing was not sufficient to produce globally synchronous extreme temperatures at multidecadal and centennial timescales. By contrast, we find that the warmest period of the past two millennia occurred during the twentieth century for more than 98 per cent of the globe. This provides strong evidence that anthropogenic global warming is not only unparalleled in terms of absolute temperatures⁵, but also unprecedented in spatial consistency within the context of the past 2,000 years.

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

Multi-decadal surface temperature changes may be forced by natural as well as anthropogenic factors, or arise unforced from the climate system. Distinguishing these factors is essential for estimating sensitivity to multiple climatic forcings and the amplitude of the unforced variability. Here we present 2,000-year-long global mean temperature reconstructions using seven different statistical methods that draw from a global collection of temperature-sensitive paleoclimate records. Our reconstructions display synchronous multi-decadal temperature fluctuations, which are coherent with one another and with fully forced CMIP5 millennial model simulations across the Common Era. The most significant attribution of pre-industrial (1300-1800 CE) variability at multi-decadal timescales is to volcanic aerosol forcing. Reconstructions and simulations qualitatively agree on the amplitude of the unforced global mean multi-decadal temperature variability, thereby increasing confidence in future projections of climate change on these timescales. The largest warming trends at timescales of 20 years and longer occur during the second half of the 20^th century, highlighting the unusual character of the warming in recent decades.

Possible causes of data model discrepancy in the temperature history of the last Millennium

Model simulations and proxy-based reconstructions are the main tools for quantifying pre-instrumental climate variations. For some metrics such as Northern Hemisphere mean temperatures, there is remarkable agreement between models and reconstructions. For other diagnostics, such as the regional response to volcanic eruptions, or hemispheric temperature differences, substantial disagreements between data and models have been reported. Here, we assess the potential sources of these discrepancies by comparing 1000-year hemispheric temperature reconstructions based on real-world paleoclimate proxies with climate-model-based pseudoproxies. These pseudoproxy experiments (PPE) indicate that noise inherent in proxy records and the unequal spatial distribution of proxy data are the key factors in explaining the data-model differences. For example, lower inter-hemispheric correlations in reconstructions can be fully accounted for by these factors in the PPE. Noise and data sampling also partly explain the reduced amplitude of the response to external forcing in reconstructions compared to models. For other metrics, such as inter-hemispheric differences, some, although reduced, discrepancy remains. Our results suggest that improving proxy data quality and spatial coverage is the key factor to increase the quality of future climate reconstructions, while the total number of proxy records and reconstruction methodology play a smaller role.

Quantifying heterogeneous responses of fish community size structure using novel combined statistical techniques

To understand changes in ecosystems, the appropriate scale at which to study them must be determined. Large marine ecosystems (LMEs) cover thousands of square kilometres and are a useful classification scheme for ecosystem monitoring and assessment. However, averaging across LMEs may obscure intricate dynamics within. The purpose of this study is to mathematically determine local and regional patterns of ecological change within an LME using empirical orthogonal functions (EOFs). After using EOFs to define regions with distinct patterns of change, a statistical model originating from control theory is applied (Nonlinear AutoRegressive Moving Average with eXogenous input - NARMAX) to assess potential drivers of change within these regions. We have selected spatial data sets (0.5° latitude × 1°longitude) of fish abundance from North Sea fisheries research surveys (spanning 1980-2008) as well as of temperature, oxygen, net primary production and a fishing pressure proxy, to which we apply the EOF and NARMAX methods. Two regions showed significant changes since 1980: the central North Sea displayed a decrease in community size structure which the NARMAX model suggested was linked to changes in fishing; and the Norwegian trench region displayed an increase in community size structure which, as indicated by NARMAX results, was primarily linked to changes in sea-bottom temperature. These regions were compared to an area of no change along the eastern Scottish coast where the model determined the community size structure was most strongly associated to net primary production. This study highlights the multifaceted effects of environmental change and fishing pressures in different regions of the North Sea. Furthermore, by highlighting this spatial heterogeneity in community size structure change, important local spatial dynamics are often overlooked when the North Sea is considered as a broad-scale, homogeneous ecosystem (as normally is the case within the political Marine Strategy Framework Directive).

Soil bacterial diversity patterns and drivers along an elevational gradient on Shennongjia Mountain, China

Understanding biological diversity elevational pattern and the driver factors are indispensable to develop the ecological theories. Elevational gradient may minimize the impact of environmental factors and is the ideal places to study soil microbial elevational patterns. In this study, we selected four typical vegetation types from 1000 to 2800 m above the sea level on the northern slope of Shennongjia Mountain in central China, and analysed the soil bacterial community composition, elevational patterns and the relationship between soil bacterial diversity and environmental factors by using the 16S rRNA Illumina sequencing and multivariate statistical analysis. The results revealed that the dominant bacterial phyla were Acidobacteria, Actinobacteria, Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria and Verrucomicrobia, which accounted for over 75% of the bacterial sequences obtained from tested samples, and the soil bacterial operational taxonomic unit (OTU) richness was a significant monotonous decreasing (P < 0.01) trend with the elevational increasing. The similarity of soil bacterial population composition decreased significantly (P < 0.01) with elevational distance increased as measured by the Jaccard and Bray–Curtis index. Canonical correspondence analysis and Mantel test analysis indicated that plant diversity and soil pH were significantly correlated (P < 0.01) with the soil bacterial community. Therefore, the soil bacterial diversity on Shennongjia Mountain had a significant and different elevational pattern, and plant diversity and soil pH may be the key factors in shaping the soil bacterial spatial pattern.

Divergent global precipitation changes induced by natural versus anthropogenic forcing

As a result of global warming, precipitation is likely to increase in high latitudes and the tropics and to decrease in already dry subtropical regions. The absolute magnitude and regional details of such changes, however, remain intensely debated. As is well known from El Niño studies, sea-surface-temperature gradients across the tropical Pacific Ocean can strongly influence global rainfall. Palaeoproxy evidence indicates that the difference between the warm west Pacific and the colder east Pacific increased in past periods when the Earth warmed as a result of increased solar radiation. In contrast, in most model projections of future greenhouse warming this gradient weakens. It has not been clear how to reconcile these two findings. Here we show in climate model simulations that the tropical Pacific sea-surface-temperature gradient increases when the warming is due to increased solar radiation and decreases when it is due to increased greenhouse-gas forcing. For the same global surface temperature increase the latter pattern produces less rainfall, notably over tropical land, which explains why in the model the late twentieth century is warmer than in the Medieval Warm Period (around AD 1000-1250) but precipitation is less. This difference is consistent with the global tropospheric energy budget, which requires a balance between the latent heat released in precipitation and radiative cooling. The tropospheric cooling is less for increased greenhouse gases, which add radiative absorbers to the troposphere, than for increased solar heating, which is concentrated at the Earth's surface. Thus warming due to increased greenhouse gases produces a climate signature different from that of warming due to solar radiation changes.

Quantifications of dendrochronological information from contrasting microdensitometric measuring circumstances of experimental wood samples

We analyzed how the pretreatment method of Scots pine (Pinus sylvestris L.) wood specimens together with X-ray methodology applied for density analyses affect resulting tree-ring data and derived proxy-based climate information. We also evaluated whether these results from two contrasting laboratory circumstances could be homogenized by applying dendroclimatic statistical methods. For this study, we measured a pair of X-ray based microdensitometry datasets using double samples of subfossil and recent wood specimens. Dendrochronological information of earlywood and latewood series was examined to determine for alterations in the resulting data. We found that the level of overall density, its trend over cambial ages and the growth amplitude altered due to the sample pretreatment/density measuring exercise, which means that comparisons of heterogeneous datasets should be, in general, regarded cautiously. Dendrochronological standardization did, however, even out several potentially biasing influences from the differing overall densities and their trends. The two latewood (maximum) density chronologies yielded paleoclimatic reconstructions which both calibrated and verified satisfactorily with the instrumental warm-season (March-September) mean temperatures. The transfer functions were found to further equalize the differences between the two proxy records. We recommend (if no strictly homogenous data are available) reconciling similar data assemblages through transfer functions with multiple independent variables.

Growing season temperatures in Europe and climate forcings over the past 1400 years

Background

The lack of instrumental data before the mid-19th-century limits our understanding of present warming trends. In the absence of direct measurements, we used proxies that are natural or historical archives recording past climatic changes. A gridded reconstruction of spring-summer temperature was produced for Europe based on tree-rings, documentaries, pollen assemblages and ice cores. The majority of proxy series have an annual resolution. For a better inference of long-term climate variation, they were completed by low-resolution data (decadal or more), mostly on pollen and ice-core data.

Methodology/Principal Findings

An original spectral analog method was devised to deal with this heterogeneous dataset, and to preserve long-term variations and the variability of temperature series. So we can replace the recent climate changes in a broader context of the past 1400 years. This preservation is possible because the method is not based on a calibration (regression) but on similarities between assemblages of proxies. The reconstruction of the April-September temperatures was validated with a Jack-knife technique. It was also compared to other spatially gridded temperature reconstructions, literature data, and glacier advance and retreat curves. We also attempted to relate the spatial distribution of European temperature anomalies to known solar and volcanic forcings.

Conclusions

We found that our results were accurate back to 750. Cold periods prior to the 20^th century can be explained partly by low solar activity and/or high volcanic activity. The Medieval Warm Period (MWP) could be correlated to higher solar activity. During the 20^th century, however only anthropogenic forcing can explain the exceptionally high temperature rise. Warm periods of the Middle Age were spatially more heterogeneous than last decades, and then locally it could have been warmer. However, at the continental scale, the last decades were clearly warmer than any period of the last 1400 years. The heterogeneity of MWP versus the homogeneity of the last decades is likely an argument that different forcings could have operated. These results support the fact that we are living a climate change in Europe never seen in the past 1400 years.

Ensemble reconstruction constraints on the global carbon cycle sensitivity to climate

The processes controlling the carbon flux and carbon storage of the atmosphere, ocean and terrestrial biosphere are temperature sensitive and are likely to provide a positive feedback leading to amplified anthropogenic warming. Owing to this feedback, at timescales ranging from interannual to the 20-100-kyr cycles of Earth's orbital variations, warming of the climate system causes a net release of CO(2) into the atmosphere; this in turn amplifies warming. But the magnitude of the climate sensitivity of the global carbon cycle (termed gamma), and thus of its positive feedback strength, is under debate, giving rise to large uncertainties in global warming projections. Here we quantify the median gamma as 7.7 p.p.m.v. CO(2) per degrees C warming, with a likely range of 1.7-21.4 p.p.m.v. CO(2) per degrees C. Sensitivity experiments exclude significant influence of pre-industrial land-use change on these estimates. Our results, based on the coupling of a probabilistic approach with an ensemble of proxy-based temperature reconstructions and pre-industrial CO(2) data from three ice cores, provide robust constraints for gamma on the policy-relevant multi-decadal to centennial timescales. By using an ensemble of >200,000 members, quantification of gamma is not only improved, but also likelihoods can be assigned, thereby providing a benchmark for future model simulations. Although uncertainties do not at present allow exclusion of gamma calculated from any of ten coupled carbon-climate models, we find that gamma is about twice as likely to fall in the lowermost than in the uppermost quartile of their range. Our results are incompatibly lower (P < 0.05) than recent pre-industrial empirical estimates of approximately 40 p.p.m.v. CO(2) per degrees C (refs 6, 7), and correspondingly suggest approximately 80% less potential amplification of ongoing global warming.

A method for computing the fraction of attributable risk related to climate damages

The recent decision of the U.S. Supreme Court on the regulation of CO2 emissions from new motor vehicles shows the need for a robust methodology to evaluate the fraction of attributable risk from such emissions. The methodology must enable decisionmakers to reach practically relevant conclusions on the basis of expert assessments the decisionmakers see as an expression of research in progress, rather than as knowledge consolidated beyond any reasonable doubt. This article presents such a methodology and demonstrates its use for the Alpine heat wave of 2003. In a Bayesian setting, different expert assessments on temperature trends and volatility can be formalized as probability distributions, with initial weights (priors) attached to them. By Bayesian learning, these weights can be adjusted in the light of data. The fraction of heat wave risk attributable to anthropogenic climate change can then be computed from the posterior distribution. We show that very different priors consistently lead to the result that anthropogenic climate change has contributed more than 90% to the probability of the Alpine summer heat wave in 2003. The present method can be extended to a wide range of applications where conclusions must be drawn from divergent assessments under uncertainty.

Comment on "Reconstructing Past Climate from Noisy Data"

von Storch et al. (Reports, 22 October 2004, p. 679) criticized the ability of the "hockey stick" climate field reconstruction method to yield realistic estimates of past variation in Northern Hemisphere temperature. However, their conclusion was based on incorrect implementation of the reconstruction procedure. Calibration was performed using detrended data, thus artificially removing a large fraction of the physical response to radiative forcing.

Climate sensitivity constrained by temperature reconstructions over the past seven centuries

The magnitude and impact of future global warming depends on the sensitivity of the climate system to changes in greenhouse gas concentrations. The commonly accepted range for the equilibrium global mean temperature change in response to a doubling of the atmospheric carbon dioxide concentration, termed climate sensitivity, is 1.5-4.5 K (ref. 2). A number of observational studies, however, find a substantial probability of significantly higher sensitivities, yielding upper limits on climate sensitivity of 7.7 K to above 9 K (refs 3-8). Here we demonstrate that such observational estimates of climate sensitivity can be tightened if reconstructions of Northern Hemisphere temperature over the past several centuries are considered. We use large-ensemble energy balance modelling and simulate the temperature response to past solar, volcanic and greenhouse gas forcing to determine which climate sensitivities yield simulations that are in agreement with proxy reconstructions. After accounting for the uncertainty in reconstructions and estimates of past external forcing, we find an independent estimate of climate sensitivity that is very similar to those from instrumental data. If the latter are combined with the result from all proxy reconstructions, then the 5-95 per cent range shrinks to 1.5-6.2 K, thus substantially reducing the probability of very high climate sensitivity.

Changes in surface water supply across Africa with predicted climate change

Across Africa, perennial drainage density as a function of mean annual rainfall defines three regimes separated by threshold values of precipitation. This nonlinear response of drainage to rainfall will most seriously affect regions in the intermediate, unstable regime. A 10% decrease in precipitation in regions on the upper regime boundary (1000 millimeters per year) would reduce drainage by 17%, whereas in regions receiving 500 millimeters per year, such a drop would cut 50% of surface drainage. By using predicted precipitation changes, we calculate that a decrease in perennial drainage will significantly affect present surface water access across 25% of Africa by the end of this century.

The spatial extent of 20th-century warmth in the context of the past 1200 years

Periods of widespread warmth or cold are identified by positive or negative deviations that are synchronous across a number of temperature-sensitive proxy records drawn from the Northern Hemisphere. The most significant and longest duration feature during the last 1200 years is the geographical extent of warmth in the middle to late 20th century. Positive anomalies during 890 to 1170 and negative anomalies during 1580 to 1850 are consistent with the concepts of a Medieval Warm Period and a Little Ice Age, but comparison with instrumental temperatures shows the spatial extent of recent warmth to be of greater significance than that during the medieval period.

Highly variable Northern Hemisphere temperatures reconstructed from low- and high-resolution proxy data

A number of reconstructions of millennial-scale climate variability have been carried out in order to understand patterns of natural climate variability, on decade to century timescales, and the role of anthropogenic forcing. These reconstructions have mainly used tree-ring data and other data sets of annual to decadal resolution. Lake and ocean sediments have a lower time resolution, but provide climate information at multicentennial timescales that may not be captured by tree-ring data. Here we reconstruct Northern Hemisphere temperatures for the past 2,000 years by combining low-resolution proxies with tree-ring data, using a wavelet transform technique to achieve timescale-dependent processing of the data. Our reconstruction shows larger multicentennial variability than most previous multi-proxy reconstructions, but agrees well with temperatures reconstructed from borehole measurements and with temperatures obtained with a general circulation model. According to our reconstruction, high temperatures--similar to those observed in the twentieth century before 1990--occurred around ad 1000 to 1100, and minimum temperatures that are about 0.7 K below the average of 1961-90 occurred around ad 1600. This large natural variability in the past suggests an important role of natural multicentennial variability that is likely to continue.