Discriminating between climate observations in terms of their ability to improve an ensemble of climate predictions

In view of the cost and complexity of climate-observing systems, it is a matter of concern to know which measurements, by satellite or in situ, can best improve the accuracy and precision of long-term ensembles of climate projections. We follow a statistical procedure to evaluate the relative capabilities of a wide variety of observable data types for improving the accuracy and precision of an ensemble of Intergovernmental Panel on Climate Change (IPCC) models. Thirty-two data types are evaluated for their potential for improving a 50-y surface air temperature trend prediction with data from earlier periods, with an emphasis on 20 y. Data types can be ordered in terms of their ability to increase the precision of a forecast. Results show that important conclusions can follow from this ordering. The small size of the IPCC model ensemble (20 members) creates uncertainties in these conclusions, which need to be substantiated with the larger ensembles expected in the future. But the larger issue of whether the methodology can provide useful answers is demonstrated.     

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earth's climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO₂ uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO₂ uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle–climate models.     

Derivation of burn scar depths and estimation of carbon emissions with LIDAR in Indonesian peatlands

During the 1997/98 El Niño-induced drought peatland fires in Indonesia may have released 13–40% of the mean annual global carbon emissions from fossil fuels. One major unknown in current peatland emission estimations is how much peat is combusted by fire. Using a light detection and ranging data set acquired in Central Kalimantan, Borneo, in 2007, one year after the severe peatland fires of 2006, we determined an average burn scar depth of 0.33 ± 0.18 m. Based on this result and the burned area determined from satellite imagery, we estimate that within the 2.79 million hectare study area 49.15 ± 26.81 megatons of carbon were released during the 2006 El Niño episode. This represents 10–33% of all carbon emissions from transport for the European Community in the year 2006. These emissions, originating from a comparatively small area (approximately 13% of the Indonesian peatland area), underline the importance of peat fires in the context of green house gas emissions and global warming. In the past decade severe peat fires occurred during El Niño-induced droughts in 1997, 2002, 2004, 2006, and 2009. Currently, this important source of carbon emissions is not included in IPCC carbon accounting or in regional and global carbon emission models. Precise spatial measurements of peat combusted and potential avoided emissions in tropical peat swamp forests will also be required for future emission trading schemes in the framework of Reduced Emissions from Deforestation and Degradation in developing countries.     

Afforestation in China cools local land surface temperature

China has the largest afforested area in the world (∼62 million hectares in 2008), and these forests are carbon sinks. The climatic effect of these new forests depends on how radiant and turbulent energy fluxes over these plantations modify surface temperature. For instance, a lower albedo may cause warming, which negates the climatic benefits of carbon sequestration. Here, we used satellite measurements of land surface temperature (LST) from planted forests and adjacent grasslands or croplands in China to understand how afforestation affects LST. Afforestation is found to decrease daytime LST by about 1.1 ± 0.5 °C (mean ± 1 SD) and to increase nighttime LST by about 0.2 ± 0.5 °C, on average. The observed daytime cooling is a result of increased evapotranspiration. The nighttime warming is found to increase with latitude and decrease with average rainfall. Afforestation in dry regions therefore leads to net warming, as daytime cooling is offset by nighttime warming. Thus, it is necessary to carefully consider where to plant trees to realize potential climatic benefits in future afforestation projects.The area of planted forest (PF) in China has increased by ∼1.7 million hectares per year (about 41% of the global afforestation rate) during the last 2 decades (1, 2). China had the largest PF area in the world in 2008, at ∼62 million hectares (Fig. 1), or ∼23% of global plantation area (264 million hectares) (1, 2). The Chinese government launched several projects to convert croplands (CR) and marginal lands into forests, to reduce soil and water quality degradation, in the 1980s and 1990s (2). This afforestation contributed to increased carbon storage (3, 4) but also altered local energy budgets, which has the potential to offer feedback on local and regional climates (5–10).Open in a separate windowFig. 1.Spatial distribution of planted forest in China and an example of a 40 × 40 km sample area. (A) Spatial distribution map of PF with mean annual precipitation background. (B) Land cover types; (C) daytime LST; and (D) nighttime LST for the example sample area.Forests generally have a lower albedo than grasslands (GR) and CR. Thus, afforestation increases the amount of absorbed solar radiation at the surface (9, 10). Surface cooling will result if this extra energy is dissipated as evapotranspiration (ET) (11) or heat convection (7); otherwise, afforestation will result in surface warming. The biophysical effects of afforestation on local climate can be much larger than the small global cooling effect resulting from uptake of CO₂ by growing forests (8, 12, 13). However, these biophysical effects are also complex and depend on “background” climate (14). Afforestation generally cools the surface in tropical areas but warms it in boreal lands (6, 8–10). The effects of afforestation in temperate regions are not clear. The large area under afforestation in China, the diversity of projects (over former CR, GR, or marginal lands), and the broad range of background climates (most plantations are in temperate regions with varying degrees of annual average rainfall) provide an interesting test bed to assess how afforestation affects local temperature.In this article, we investigate how plantations affect land surface temperature (LST) across China, using satellite-derived LST data sets from Earth Observing System (EOS)-Terra and EOS-Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) instruments during the period from 2003 to 2010 (Methods). These LST data depend on the radiative properties of the land surface (15, 16) and, therefore, have a larger diurnal amplitude than the standard 2-m air temperature data from meteorological stations (17). The primary objective of this investigation is to quantify the space–time distribution of differences in LST between PF and adjacent GR or CR (ΔLST), during both daytime and nighttime.     

Deriving meteorological variables across Africa for the study and control of vector-borne disease: a comparison of remote sensing and spatial interpolation of climate

This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration's (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) on-board the European Meteorological Satellite programme's (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study and control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy.     

Bedrock displacements in Greenland manifest ice mass variations, climate cycles and climate change

The Greenland GPS Network (GNET) uses the Global Positioning System (GPS) to measure the displacement of bedrock exposed near the margins of the Greenland ice sheet. The entire network is uplifting in response to past and present-day changes in ice mass. Crustal displacement is largely accounted for by an annual oscillation superimposed on a sustained trend. The oscillation is driven by earth's elastic response to seasonal variations in ice mass and air mass (i.e., atmospheric pressure). Observed vertical velocities are higher and often much higher than predicted rates of postglacial rebound (PGR), implying that uplift is usually dominated by the solid earth's instantaneous elastic response to contemporary losses in ice mass rather than PGR. Superimposed on longer-term trends, an anomalous 'pulse' of uplift accumulated at many GNET stations during an approximate six-month period in 2010. This anomalous uplift is spatially correlated with the 2010 melting day anomaly.     

The Antarctic ozone hole and the pattern effect on climate sensitivity

Since about 1980, the tropical Pacific has been anomalously cold, while the broader tropics have warmed. This has caused anomalous weather in midlatitudes as well as a reduction in the apparent sensitivity of the climate associated with enhanced low-cloud abundance over the cooler waters of the eastern tropical Pacific. Recent modeling work has shown that cooler temperatures over the Southern Ocean around Antarctica can lead to cooler temperatures over the eastern tropical Pacific. Here we suggest that surface wind anomalies associated with the Antarctic ozone hole can cause cooler temperatures over the Southern Ocean that extend into the tropics. We use the short-term variability of the Southern Annular Mode of zonal wind variability to show an association between surface zonal wind variations over the Southern Ocean, cooling over the Southern Ocean, and cooling in the eastern tropical Pacific. This suggests that the cooling of the eastern tropical Pacific may be associated with the onset of the Antarctic ozone hole.

Since about 1979, the tropical eastern Pacific Ocean has cooled, while the western tropical Pacific Ocean has warmed. This pattern of sea surface temperature (SST) change has been identified with a reduction in absorbed solar radiation that has slowed the response of global surface temperature to increasing greenhouse gases (1–3). The primary mechanism that relates this SST change pattern to a reduction in apparent climate sensitivity is the development of enhanced boundary layer clouds over the cooler SST region, which reflect more solar radiation and thereby cool the planet. It is important to understand whether this pattern effect is natural variability or part of the forced response to climate change, as this may determine how long the pattern effect will persist and thereby slow the effect of greenhouse gases on global warming. In addition, the pattern of SST trend since 1979 resembles a La Niña event, which has known impacts on seasonal climate around the world, including increasing the probability of drought in the western United States (4). Here we review some recent research on the connection between changes in the Southern Ocean (SO) and changes in the tropical Pacific Ocean. Arguing from connections established in the published literature, we outline a mechanism to connect the reduction in stratospheric ozone in the Antarctic region to cooling of the tropical eastern Pacific. In this mechanism, a surface wind shift in high latitudes associated with the Antarctic ozone hole (5) triggers a cooling of the SO, which, through feedback processes involving atmospheric circulation, low-cloud feedbacks, and ocean current changes, leads to a cooling in the eastern tropical Pacific Ocean. We show, in observations, a connection between stronger winds over the SO, reduced SST there, and associated cooler ocean temperatures in the tropical eastern Pacific Ocean. If this mechanism is what has produced the SST trends since 1980, then we may expect the eastern tropical Pacific to remain relatively cool as the rest of the tropical oceans warm. This would have important consequences for apparent climate sensitivity and for the structure of climate change in the Pacific and for North and South America.     

Climate Endgame: Exploring catastrophic climate change scenarios

Prudent risk management requires consideration of bad-to-worst-case scenarios. Yet, for climate change, such potential futures are poorly understood. Could anthropogenic climate change result in worldwide societal collapse or even eventual human extinction? At present, this is a dangerously underexplored topic. Yet there are ample reasons to suspect that climate change could result in a global catastrophe. Analyzing the mechanisms for these extreme consequences could help galvanize action, improve resilience, and inform policy, including emergency responses. We outline current knowledge about the likelihood of extreme climate change, discuss why understanding bad-to-worst cases is vital, articulate reasons for concern about catastrophic outcomes, define key terms, and put forward a research agenda. The proposed agenda covers four main questions: 1) What is the potential for climate change to drive mass extinction events? 2) What are the mechanisms that could result in human mass mortality and morbidity? 3) What are human societies'' vulnerabilities to climate-triggered risk cascades, such as from conflict, political instability, and systemic financial risk? 4) How can these multiple strands of evidence—together with other global dangers—be usefully synthesized into an “integrated catastrophe assessment”? It is time for the scientific community to grapple with the challenge of better understanding catastrophic climate change.     

Dynamic climate clubs: On the effectiveness of incentives in global climate agreements

A proposal to combat free riding in international climate agreements is the establishment of a climate club—a coalition of countries in a structure to encourage high levels of participation. Empirical models of climate clubs in the early stages relied on the analysis of single-period coalition formation. The earlier results suggested that there were limits to the potential strength of clubs and that it would be difficult to have deep abatement strategies in the club framework. The current study extends the single-period approach to many periods and develops an approach analyzing “supportable policies” to analyze multiperiod clubs. The major element of the present study is the interaction between club effectiveness and rapid technological change. Neither alone will produce incentive-compatible policies that can attain the ambitious objectives of international climate policy. The trade sanctions without rapid technological decarbonization will be too costly to produce deep abatement; similarly, rapid technological decarbonization by itself will not induce deep abatement because of country free riding. However, the two together can achieve international climate objectives.

Global agreements on climate change date back to the Kyoto Protocol in 1997, yet little substantial coordinated abatement has taken place. Free riding is a major hurdle in curbing global externalities and is at the heart of the international failures to deal with climate change. Without an appropriate incentive structure, no individual country has an incentive to cut its emissions sharply. Moreover, if there is an international agreement, nations have a strong incentive not to participate. If they do participate, there is a further incentive to miss ambitious objectives. The outcome is a noncooperative free-riding equilibrium in which few countries undertake strong climate change policies—a situation that closely resembles the current international policy environment. Nations speak loudly but carry the tiniest of sticks.One proposal to combat free riding is the concept of a climate club, which is a coalition of countries organized to encourage high levels of participation and abatement. The idea, analyzed in ref. 1, is that nations can overcome the syndrome of free riding in international climate agreements if they adopt the club model rather than voluntary arrangements. The central feature of the club model is that the structure includes both obligations in terms of strong abatement and penalties for either nonparticipation or failure to meet the club obligations.The club model analyzed here centers on an “international target carbon price” that is the focal provision of the agreement. (The power of the price as a single instrument has been shown in ref. 2.) For example, countries might agree that each country will implement policies that produce a minimum domestic carbon price of $50 per metric ton of CO₂. The target price might apply to 2025 and rise over time at, say, 3% per year in real terms. Carbon prices might be determined by either a cap-and-trade system or by carbon taxes as best fits the structures of individual countries, but many details for measuring remain to be determined. Additionally, no consideration is given to transfers among regions.The need for a special type of agreement is required by the combination of climate as a global public good and the lack of a mechanism for requiring participation of individual countries. Both the theory and history of international agreements show that some form of penalty is required to induce countries to participate in agreements with local costs but diffuse benefits (see particularly refs. 3 and 4). While the exact degree of free riding and cooperation will differ according to the technology and the assumptions about coalition formation and stability, most theoretical and empirical modeling suggests that reaching a grand bargain of most regions with strong abatement will be extraordinarily difficult (5–9). Studies of club-like structures can be found in refs. 10–14. For an independent empirical modeling analysis, see ref. 15.The original proposal in the climate club was a uniform tariff on all imports of nonclub countries into the club. Take as an example a penalty tariff of 5%. If nonparticipant country A exports $100 billion into the club region, it would be penalized by $5 billion of tariffs. In calculations of the coalition stability of a one-shot climate club using the Coalition-DICE (C-DICE) model (1), it was estimated that climate clubs would be extremely effective (relative to no club) for low carbon prices (less than $100/tCO₂ in 2015). Those estimates also showed that a club would have difficulty supporting higher carbon prices at the current economic structure.However, that analysis was limited to a single period. The reason was that the computational complexity of the C-DICE model was too great for a full dynamic model (see SI Appendix for a discussion of complexity). The present study tackles the question of sustainable climate clubs in a multiperiod framework.Here are the major results. The major analytical concept developed here is a “supportable policy.” This designates the upper bound on a contribution to the public good that is compatible with the incentives contained in the agreement. At the most general level, supportable policies are ones that will minimize carbon emissions each period subject to a constraint that the policy is incentive-compatible with the agreement. More precisely, the supportable policy is one in which the costs of participating (through abatement) just equal the costs of nonparticipation (imposed through the trade sanctions). We can interpret supportable policies as ones with maximum stringency given the incentives to be in the club (here, the incentives are tariffs, but they could be something else). The required policies could be emissions prices, emissions limits, or other constraints on producer and consumer behavior, although the present study examines supportable carbon prices. Policies that have target carbon prices lower than the supportable price have lower abatement; policies with higher target carbon prices induce countries to drop out of the club and therefore also have lower abatement. The study defines supportable targets, shows how to find them in a simple example, and then develops a global empirical model that allows the calculation of supportable policies over time.A second contribution is to develop a simple analytical model of the supportable participation of a country in a regime (such as a climate club) that imposes costs but also conveys rewards for participation (or imposes punishments for nonparticipation). While estimating the equilibrium of a coalition in a dynamic framework is computationally extremely burdensome, as noted in SI Appendix, determining supportable policies is relatively simple both analytically and computationally for the multiperiod model.A third finding in a simple analytical model provides the key determinants of supportable policies. It shows that the time path of supportable policies for the climate club depends primarily on six determinants. These are trade openness (the trade–output ratio), the tariff rate, the rate of decarbonization, the fraction of the world in the club, the welfare loss per unit tariff, and the rate of technological change in the backstop technology. Additionally, in the simple model, the growth of output does not affect the outcome because it cancels out for costs and benefits.The fourth contribution is developing a simple global computable model (Trade DICE or TDICE) for estimating supportable carbon prices, emissions, and geophysical variables such as concentrations and temperature. The model uses much of the structure of the standard DICE model (described in Modeling Details) but adds equations that represent the public-goods character of damages, “club” variables such as trade, the gains from trade, and the costs of trade sanctions. By combining the different components, it is possible to determine the supportable carbon prices and emissions—that is, policies in which emissions are minimized subject to the constraint that the costs of participating just equal the costs of nonparticipation.Fifth, the results of the TDICE model show several features. First consider a scenario with baseline technology and other parameters. Even with strong trade sanctions of 10% uniform tariffs for nonparticipation, emissions are slowed sharply in the club relative to no club policy but do not attain the high levels of abatement that are the objectives of international climate policy. With baseline parameters and strong sanctions, industrial emissions in 2050 are 26 GtCO₂ rather than the target of zero. The global temperature in 2100 reaches 3.1 °C rather than the 1.5 or 2 °C targets. This result confirms the conclusion in ref. 16 that the incentives in the climate club as originally conceived are insufficient to attain international objectives.A sixth finding shows the importance of the combination of the club incentives and rapid decarbonizing technological change. Two important parameters in the analysis are the rate of decarbonization and the rate of technological change in the backstop technology. Technological improvements provide powerful boosts to the club incentive because they lower the cost of participation. As a polar and ambitious objective, the model examines the club incentives along with a rapid rate of decarbonization (2% per year faster than historical rates) as well as a rapid decline in the cost of the backstop technology (at 4% per year instead of 1% in the base assumption). With these assumptions and the strong tariff incentive of 10% penalty tariff, global emissions in the TDICE model are slightly negative in 2050, and global temperatures stay within the 2 °C limit. While the combination of a strong club and rapid technological change are at the outer edge of political and technological realism, they do point to a potential political–economic–technological mechanism for attaining ambitious climate objectives.Finally, the major surprise of the study is the interaction between the club structure and rapidly decarbonizing technological change in a dynamic framework. Neither a club nor rapid technological change by themselves will produce incentive-compatible policies that can attain the ambitious objectives of international climate policy. The trade sanctions without rapid technological decarbonization will be too costly to induce highly costly deep abatement; similarly, rapid technological decarbonization by itself will not induce deep abatement because of country free riding. However, the two together—providing incentives to participate but lowering the costs of participation at the same time—are a team that, in principle and according to the current study, can achieve the international objectives.     

Insects and recent climate change

Insects have diversified through more than 450 million y of Earth’s changeable climate, yet rapidly shifting patterns of temperature and precipitation now pose novel challenges as they combine with decades of other anthropogenic stressors including the conversion and degradation of land. Here, we consider how insects are responding to recent climate change while summarizing the literature on long-term monitoring of insect populations in the context of climatic fluctuations. Results to date suggest that climate change impacts on insects have the potential to be considerable, even when compared with changes in land use. The importance of climate is illustrated with a case study from the butterflies of Northern California, where we find that population declines have been severe in high-elevation areas removed from the most immediate effects of habitat loss. These results shed light on the complexity of montane-adapted insects responding to changing abiotic conditions. We also consider methodological issues that would improve syntheses of results across long-term insect datasets and highlight directions for future empirical work.     

Catalogue of abrupt shifts in Intergovernmental Panel on Climate Change climate models

Abrupt transitions of regional climate in response to the gradual rise in atmospheric greenhouse gas concentrations are notoriously difficult to foresee. However, such events could be particularly challenging in view of the capacity required for society and ecosystems to adapt to them. We present, to our knowledge, the first systematic screening of the massive climate model ensemble informing the recent Intergovernmental Panel on Climate Change report, and reveal evidence of 37 forced regional abrupt changes in the ocean, sea ice, snow cover, permafrost, and terrestrial biosphere that arise after a certain global temperature increase. Eighteen out of 37 events occur for global warming levels of less than 2°, a threshold sometimes presented as a safe limit. Although most models predict one or more such events, any specific occurrence typically appears in only a few models. We find no compelling evidence for a general relation between the overall number of abrupt shifts and the level of global warming. However, we do note that abrupt changes in ocean circulation occur more often for moderate warming (less than 2°), whereas over land they occur more often for warming larger than 2°. Using a basic proportion test, however, we find that the number of abrupt shifts identified in Representative Concentration Pathway (RCP) 8.5 scenarios is significantly larger than in other scenarios of lower radiative forcing. This suggests the potential for a gradual trend of destabilization of the climate with respect to such shifts, due to increasing global mean temperature change.The gradual rise in greenhouse gas concentrations is projected to drive a mostly smooth increase in global temperature (1). However, the Earth system is suspected to have a range of “tipping elements” with the characteristic that their gradual change will be punctuated by critical transitions on regional scales (2, 3). That is, for relatively small changes in atmospheric concentrations of greenhouse gases, parts of the Earth system exhibit major changes. The recent fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) presents a catalog of possible abrupt or irreversible changes (table 12.4 in ref. 4). This catalog builds on a previous literature review (2) of components believed to have the potential for an acceleration of change as fossil fuel burning changes atmospheric composition and thus radiative forcing.The expert elicitation (2) motivated discussion of a multitude of environmental threats to the planet in which it was critically argued that atmospheric carbon dioxide concentration should not cross 350 ppm (5), trying to determine what constitutes safe levels of global warming. This threshold was suggested in ref. 5 to minimize the risk due to massive sea ice change, sea level rise, or major changes to terrestrial ecosystems and crops. An alternative purely temperature-based threshold is that from the Copenhagen accord, setting an upper limit of 2° (6). However, major uncertainty exists in knowledge of climate sensitivity (7), which makes it difficult to relate this warming level to a precise CO₂ concentration. However, despite this and the growing interest in the societal effects of such transitions, there has been no systematic study of the potential for abrupt shifts in state-of-the-art Earth System Models.To explore what may be deduced from the current generation of climate models in this context, we analyze the simulations produced by Coupled Model Intercomparison Project 5 (CMIP5) (8) that were used to inform the IPCC. CMIP5 provides a compilation of coordinated climate model experiments. Each of 37 analyzed models includes representations of the oceans, atmosphere, land surface, and cryosphere. The climate models have been forced with future changes in atmospheric gas concentrations, depicted in four Representative Concentration Pathways (RCPs) (9), starting in year 2006. Of these, we analyze RCP2.6, RCP4.5, and RCP8.5 to explore a range of changes in radiative forcing, reaching levels of 2.6 W⋅m⁻², 4.5 W⋅m⁻², and 8.5 W⋅m⁻², respectively, by year 2100 (including all available simulations that go beyond 2100). We also analyze historical simulations, capturing changes from preindustrial conditions in year 1850 to the present, and preindustrial control simulations.To assess future risks of abrupt, potentially irreversible, changes in important climate phenomena, we first need to define what we mean by “abrupt.” This term clearly refers to time scale and is usually defined as when changes observed are faster than the time scale of the external forcing. Here we choose a methodology consisting of three stages. Firstly, we systematically screen the CMIP5 multimodel ensemble of simulations for evidence of abrupt changes using search criteria (Methods) to make a first filtering of regions of potentially relevant abrupt events from this dataset (stage 1). These criteria are motivated by the definition of the assessment report, AR5 (4): “A large-scale change in the climate system that takes place over a few decades or less, persists (or is anticipated to persist) for at least a few decades, and causes substantial disruptions in human and natural systems.” Other definitions have emphasized the timescales of the change, e.g., 30 y (10), and rapidity in comparison with the forcing (11), which also meet our search criteria. Global maps of quantities with potential to change abruptly are expressed as (i) the mean difference between end and beginning of a simulation, (ii) the SD of the detrended time series, and (iii) the maximum absolute change within 10 y. These maps are made for all scenario runs and compared with values for the preindustrial control runs. When at least two indicators suggest locations of major change, we construct time series for area averages of at least 0.5 × 10⁶ km² (roughly 10 by 10 degrees) and visually inspect these for abrupt shifts standing out from the internal variability (stage 2). Subsequently, we check whether the selected cases can indeed be considered examples of abrupt change applying formal classification criteria (Methods) such as the criterion that the change should be larger than 4 times the SD of the preindustrial simulation, in combination with additional statistical tests (stage 3).We find a broad range of transitions passing our classification criteria (Fig. 1, SI Appendix, Table S1), which can be grouped into four categories (Fig. 2). They include abrupt shifts in sea ice and ocean circulation patterns as well as abrupt shifts in vegetation and the terrestrial cryosphere. Fig. 2 shows a selected example for each category. All other time series are displayed in Fig. 3. Information on the regions where the shifts occur and the results of the statistical tests used for classification are displayed in SI Appendix, Tables S2 and S3, respectively. A list of the climate models and their acronyms is provided in SI Appendix, Table S1.Open in a separate windowFig. 1.Geographical location of the abrupt climate change occurrences. All 30 model cases listed in

Drought,drying and climate change: Emerging health issues for ageing Australians in rural areas

Older Australians living in rural areas have long faced significant challenges in maintaining health. Their circumstances are shaped by the occupations, lifestyles, environments and remoteness which characterise the diversity of rural communities. Many rural regions face threats to future sustainability and greater proportions of the aged reside in these areas. The emerging changes in Australia's climate over the past decade may be considered indicative of future trends, and herald amplification of these familiar challenges for rural communities. Such climate changes are likely to exacerbate existing health risks and compromise community infrastructure in some instances. This paper discusses climate change‐related health risks facing older people in rural areas, with an emphasis on the impact of heat, drought and drying on rural and remote regions. Adaptive health sector responses are identified to promote mitigation of this substantial emerging need as individuals and their communities experience the projected impact of climate change.     

High skill in low-frequency climate response through fluctuation dissipation theorems despite structural instability

Climate change science focuses on predicting the coarse-grained, planetary-scale, longtime changes in the climate system due to either changes in external forcing or internal variability, such as the impact of increased carbon dioxide. The predictions of climate change science are carried out through comprehensive, computational atmospheric, and oceanic simulation models, which necessarily parameterize physical features such as clouds, sea ice cover, etc. Recently, it has been suggested that there is irreducible imprecision in such climate models that manifests itself as structural instability in climate statistics and which can significantly hamper the skill of computer models for climate change. A systematic approach to deal with this irreducible imprecision is advocated through algorithms based on the Fluctuation Dissipation Theorem (FDT). There are important practical and computational advantages for climate change science when a skillful FDT algorithm is established. The FDT response operator can be utilized directly for multiple climate change scenarios, multiple changes in forcing, and other parameters, such as damping and inverse modelling directly without the need of running the complex climate model in each individual case. The high skill of FDT in predicting climate change, despite structural instability, is developed in an unambiguous fashion using mathematical theory as guidelines in three different test models: a generic class of analytical models mimicking the dynamical core of the computer climate models, reduced stochastic models for low-frequency variability, and models with a significant new type of irreducible imprecision involving many fast, unstable modes.     

Tipping elements in the Earth's climate system

The term “tipping point” commonly refers to a critical threshold at which a tiny perturbation can qualitatively alter the state or development of a system. Here we introduce the term “tipping element” to describe large-scale components of the Earth system that may pass a tipping point. We critically evaluate potential policy-relevant tipping elements in the climate system under anthropogenic forcing, drawing on the pertinent literature and a recent international workshop to compile a short list, and we assess where their tipping points lie. An expert elicitation is used to help rank their sensitivity to global warming and the uncertainty about the underlying physical mechanisms. Then we explain how, in principle, early warning systems could be established to detect the proximity of some tipping points.     

From the Cover: Recent changes in a remote Arctic lake are unique within the past 200,000 years

The Arctic is currently undergoing dramatic environmental transformations, but it remains largely unknown how these changes compare with long-term natural variability. Here we present a lake sediment sequence from the Canadian Arctic that records warm periods of the past 200,000 years, including the 20th century. This record provides a perspective on recent changes in the Arctic and predates by approximately 80,000 years the oldest stratigraphically intact ice core recovered from the Greenland Ice Sheet. The early Holocene and the warmest part of the Last Interglacial (Marine Isotope Stage or MIS 5e) were the only periods of the past 200,000 years with summer temperatures comparable to or exceeding today''s at this site. Paleoecological and geochemical data indicate that the past three interglacial periods were characterized by similar trajectories in temperature, lake biology, and lakewater pH, all of which tracked orbitally-driven solar insolation. In recent decades, however, the study site has deviated from this recurring natural pattern and has entered an environmental regime that is unique within the past 200 millennia.     

Quasi-resonant circulation regimes and hemispheric synchronization of extreme weather in boreal summer

The recent decade has seen an exceptional number of high-impact summer extremes in the Northern Hemisphere midlatitudes. Many of these events were associated with anomalous jet stream circulation patterns characterized by persistent high-amplitude quasi-stationary Rossby waves. Two mechanisms have recently been proposed that could provoke such patterns: (i) a weakening of the zonal mean jets and (ii) an amplification of quasi-stationary waves by resonance between free and forced waves in midlatitude waveguides. Based upon spectral analysis of the midtroposphere wind field, we show that the persistent jet stream patterns were, in the first place, due to an amplification of quasi-stationary waves with zonal wave numbers 6–8. However, we also detect a weakening of the zonal mean jet during these events; thus both mechanisms appear to be important. Furthermore, we demonstrate that the anomalous circulation regimes lead to persistent surface weather conditions and therefore to midlatitude synchronization of extreme heat and rainfall events on monthly timescales. The recent cluster of resonance events has resulted in a statistically significant increase in the frequency of high-amplitude quasi-stationary waves of wave numbers 7 and 8 in July and August. We show that this is a robust finding that holds for different pressure levels and reanalysis products. We argue that recent rapid warming in the Arctic and associated changes in the zonal mean zonal wind have created favorable conditions for double jet formation in the extratropics, which promotes the development of resonant flow regimes.Climatic warming over the 20th century has increased the frequency of extreme heat and heavy rainfall events (1–7). On a global scale, the magnitude of this gradual increase can largely be explained by a slowly warming atmosphere, i.e., by thermodynamic arguments only. Thus, the rise in the number of heat extremes can largely be explained by a shift in the mean to warmer values (4, 5, 8). Likewise, upward trends in annual maximum daily rainfall are consistent with the increase in atmospheric moisture associated with warmer air (1, 2).Global warming is also likely to affect large-scale atmospheric circulation patterns, which potentially could alter the frequency of heat and precipitation extremes on seasonal to subseasonal timescales (9–11). In principle, changes in atmospheric dynamics could cause a disproportionate change in the number and/or intensity of extreme weather events (12–14), beyond what is expected from thermodynamics. Moreover, the magnitude of several recent summer extreme weather events in the Northern Hemisphere midlatitudes cannot be explained by a simple shift in the mean (12, 15, 16). These events, which include high-impact extremes like the European heat wave of 2003 (15), the Russian heat wave and the Pakistan flooding in 2010 (17), and heat waves in the United States in recent years (18), were associated with anomalous circulation patterns characterized by persistent, blocking weather conditions (10, 19–22).     

Secure human attachment can promote support for climate change mitigation

Attachment theory is an ethological approach to the development of durable, affective ties between humans. We propose that secure attachment is crucial for understanding climate change mitigation, because the latter is inherently a communal phenomenon resulting from joint action and requiring collective behavioral change. Here, we show that priming attachment security increases acceptance (Study 1: n = 173) and perceived responsibility toward anthropogenic climate change (Study 2: n = 209) via increased empathy for others. Next, we demonstrate that priming attachment security, compared to a standard National Geographic video about climate change, increases monetary donations to a proenvironmental group in politically moderate and conservative individuals (Study 3: n = 196). Finally, through a preregistered field study conducted in the United Arab Emirates (Study 4: n = 143,558 food transactions), we show that, compared to a message related to carbon emissions, an attachment security–based message is associated with a reduction in food waste. Taken together, our work suggests that an avenue to promote climate change mitigation could be grounded in core ethological mechanisms associated with secure attachment.

The negative effects of climate change are looming, demanding forceful and immediate action from multiple stakeholders, including households and individuals. Despite the pressing need for climate change mitigation, many people still deny the reality or seriousness of climate change (1). Furthermore, even when people do acknowledge climate change, they often do not change their behavior in substantive ways to reduce carbon emissions (2). Several reasons have been proposed to explain the limited household action to mitigate climate change (3), and among alternative accounts, the hypothesis of motivated reasoning is gaining momentum. The motivated reasoning hypothesis proposes that limited action on climate change may function to safeguard core identity motives, ideologies, and worldviews, including perceived conflicts between mitigating climate change and maintaining economic prosperity (4). This perspective is increasingly prominent in the literature, particularly with research suggesting that individuals construe scientific evidence about climate change in ways that are self-serving (5). Therefore, given that attitudes and action about climate change are, at least partially, influenced by motivational processes, the question remains of how to motivate individuals toward more proenvironmental pathways.We propose that climate change mitigation may be promoted when psychological structures related to human interconnection are developed and active. This is based on the premise that the willingness to mitigate climate change involves accepting human (co)accountability, caring for others (present and future generations), and a readiness to act (together) as a mitigation response.Here, we specifically examine the role of attachment orientation in the willingness to mitigate climate change, in line with increasing calls to invest in demand side solutions to address global warming (6). We focus on attachment because it relates to the primal form of emotional bonding between humans (7). From an evolutionary perspective, attachment is conceptualized as an innate behavioral system aimed at safeguarding against potential threats by assuring proximity to caring and supportive others (8). The motivation to seek proximity to protective others is functionally different from more general affiliation needs (9); it aims to establish a secure base, which is defined as a sense that protective others are available and responsive in case of threat. This concept of protection from threat is pertinent to climate change because global warming poses an existential threat to humankind, which is within the realm of stimuli that could be expected to activate the attachment system.Researchers have identified two primary attachment orientations^* (10–12): a secure attachment orientation, which is used to describe people who have experienced a sense of safe haven, protection, and comfort from close others in times of distress, and an insecure attachment orientation, which is associated with experiences of being rejected or ignored by close others in times of need or threat (13).This distinction between attachment orientations is significant because the attachment system is linked to other behavioral systems (14), namely the caregiving system. The caregiving system is thought to have evolved to provide protection and support to others, and is inherently altruistic in nature (15). These behavioral systems are linked in a way that, when people feel comforted and safe in threatening situations (securely attached), the activation of caregiving is facilitated, enabling them to focus on the distress of others (16). By comparison, insecurely attached individuals tend to remain focused on their own distress and are less likely to engage in altruistic behaviors. Only when relief from threat is achieved, and a sense of safety restored, can individuals shift resources to other behavioral systems such as caregiving (17). Thus, attachment security does not activate the caregiving system directly but rather offers a solid psychological foundation for altruism (18). Previous research has shown the positive impact of secure attachment in multiple instances of caregiving, including volunteering and helping behavior (18, 19). Essentially, secure attachment, as a basic psychological need related to safety and protection, anchors the progression toward higher-level psychological processes (19) and offers a strong, theoretical foundation to understand prosocial behavior. In prior research, mitigating climate change has been defined as a form of prosocial behavior, which places individual self-interest behind the collective welfare (20).The interplay between the attachment and caregiving systems has several important implications for research about climate change. First, attachment theory sheds a different light on prosocial behavior, examined through an evolutionary perspective. Research based on evolutionary frameworks suggests that prosocial behavior occurs primarily to protect reputation and build reciprocity as a means to guarantee return benefits, particularly from in-group members (21, 22). However, the distinctiveness of the attachment system lies in the ethology of the bonding process, which goes beyond the notion of transactional social ties. Seminal evidence from humans and nonhuman primates (23, 24) has shown that the attachment system is not rooted in reward reinforcement from the caregiver (such as food) but rather is motivated by a need for protective bonding. Secure attachment has been linked to volunteering and helping behavior (which are features of the caregiving system) beyond the boundaries of close in-group members—for example, toward strangers and unrelated individuals (14–18).Second, secure attachment may be the psychological infrastructure on which several factors previously associated with caring for the environment are built. There is evidence showing the role of altruistic social orientation, empathy, and universality values in proenvironmental behaviors (25–27). This previous research, however, leaves unaddressed what promotes these factors. We propose that attachment security is a crucial, latent foundation because of its facilitating role in the activation of the caregiving system, which offers a broader conceptual perspective to previous findings.Third, the literature on adult attachment theory provides a validated, experimental apparatus for the design of interventions (18) to increase the manifestation of prosocial behavior. A core assumption in attachment theory is that attachment orientations are relatively stable over time (12) but prone to temporary variations (e.g., such as a parent’s death, a job loss, or a new intimate relationship) and transient fluctuations, including experimental manipulations (14). There is consistent causal evidence showing the effect of priming attachment security in increasing levels of empathy, trust, and helping behavior (11, 15, 18). Therefore, such validated, experimental manipulations also allow one to experimentally test the effect of attachment security on beliefs and action toward anthropogenic climate change.Finally, attachment theory is not culturally bound, unlike other perspectives on climate change (28). A central feature of attachment theory is the universality of its premise (7), with minor cultural variations (29). Fundamentally, attachment security is a psychological feature that can be nurtured in all humans. Given its link to a generalized concern for others’ welfare (14), attachment security could help the conservation of global public goods (20) that require protective action based on common concerns that affect all of humankind—of which climate change is a paradigmatic example.     

Atmospheric brown clouds: impacts on South Asian climate and hydrological cycle

South Asian emissions of fossil fuel SO(2) and black carbon increased approximately 6-fold since 1930, resulting in large atmospheric concentrations of black carbon and other aerosols. This period also witnessed strong negative trends of surface solar radiation, surface evaporation, and summer monsoon rainfall. These changes over India were accompanied by an increase in atmospheric stability and a decrease in sea surface temperature gradients in the Northern Indian Ocean. We conducted an ensemble of coupled ocean-atmosphere simulations from 1930 to 2000 to understand the role of atmospheric brown clouds in the observed trends. The simulations adopt the aerosol radiative forcing from the Indian Ocean experiment observations and also account for global increases in greenhouse gases and sulfate aerosols. The simulated decreases in surface solar radiation, changes in surface and atmospheric temperatures over land and sea, and decreases in monsoon rainfall are similar to the observed trends. We also show that greenhouse gases and sulfates, by themselves, do not account for the magnitude or even the sign in many instances, of the observed trends. Thus, our simulations suggest that absorbing aerosols in atmospheric brown clouds may have played a major role in the observed regional climate and hydrological cycle changes and have masked as much as 50% of the surface warming due to the global increase in greenhouse gases. The simulations also raise the possibility that, if current trends in emissions continue, the subcontinent may experience a doubling of the drought frequency in the coming decades.