scispace - formally typeset
Search or ask a question

Showing papers by "Potsdam Institute for Climate Impact Research published in 2016"


Journal ArticleDOI
30 Jun 2016-Nature
TL;DR: Substantial enhancement or over-delivery on current INDCs by additional national, sub-national and non-state actions is required to maintain a reasonable chance of meeting the target of keeping warming well below 2 degrees Celsius.
Abstract: The Paris climate agreement aims at holding global warming to well below 2 degrees Celsius and to "pursue efforts" to limit it to 1.5 degrees Celsius. To accomplish this, countries have submitted Intended Nationally Determined Contributions (INDCs) outlining their post-2020 climate action. Here we assess the effect of current INDCs on reducing aggregate greenhouse gas emissions, its implications for achieving the temperature objective of the Paris climate agreement, and potential options for overachievement. The INDCs collectively lower greenhouse gas emissions compared to where current policies stand, but still imply a median warming of 2.6-3.1 degrees Celsius by 2100. More can be achieved, because the agreement stipulates that targets for reducing greenhouse gas emissions are strengthened over time, both in ambition and scope. Substantial enhancement or over-delivery on current INDCs by additional national, sub-national and non-state actions is required to maintain a reasonable chance of meeting the target of keeping warming well below 2 degrees Celsius.

2,333 citations


Journal ArticleDOI
TL;DR: The Scenario Model Intercomparison Project (ScenarioMIP) as discussed by the authors is the primary activity within Phase 6 of the Coupled Model Comparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models.
Abstract: . Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.

1,758 citations


Journal ArticleDOI
TL;DR: In this article, the authors quantify potential global impacts of different negative emissions technologies on various factors (such as land, greenhouse gas emissions, water, albedo, nutrients and energy) to determine the biophysical limits to, and economic costs of, their widespread application.
Abstract: To have a >50% chance of limiting warming below 2 °C, most recent scenarios from integrated assessment models (IAMs) require large-scale deployment of negative emissions technologies (NETs). These are technologies that result in the net removal of greenhouse gases from the atmosphere. We quantify potential global impacts of the different NETs on various factors (such as land, greenhouse gas emissions, water, albedo, nutrients and energy) to determine the biophysical limits to, and economic costs of, their widespread application. Resource implications vary between technologies and need to be satisfactorily addressed if NETs are to have a significant role in achieving climate goals.

974 citations


Journal ArticleDOI
TL;DR: In this article, B. Sonnenschein, E.R. dos Santos, P.J. Schultz, C.A. Ha, M.K. Choi and C.P.

683 citations


Journal ArticleDOI
TL;DR: In this article, the authors provide an assessment of key impacts of climate change at warming levels of 1.5°C and 2°C, including extreme weather events, water availability, agricultural yields, sea-level rise and risk of coral reef loss.
Abstract: . Robust appraisals of climate impacts at different levels of global-mean temperature increase are vital to guide assessments of dangerous anthropogenic interference with the climate system. The 2015 Paris Agreement includes a two-headed temperature goal: "holding the increase in the global average temperature to well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C". Despite the prominence of these two temperature limits, a comprehensive overview of the differences in climate impacts at these levels is still missing. Here we provide an assessment of key impacts of climate change at warming levels of 1.5 °C and 2 °C, including extreme weather events, water availability, agricultural yields, sea-level rise and risk of coral reef loss. Our results reveal substantial differences in impacts between a 1.5 °C and 2 °C warming that are highly relevant for the assessment of dangerous anthropogenic interference with the climate system. For heat-related extremes, the additional 0.5 °C increase in global-mean temperature marks the difference between events at the upper limit of present-day natural variability and a new climate regime, particularly in tropical regions. Similarly, this warming difference is likely to be decisive for the future of tropical coral reefs. In a scenario with an end-of-century warming of 2 °C, virtually all tropical coral reefs are projected to be at risk of severe degradation due to temperature-induced bleaching from 2050 onwards. This fraction is reduced to about 90 % in 2050 and projected to decline to 70 % by 2100 for a 1.5 °C scenario. Analyses of precipitation-related impacts reveal distinct regional differences and hot-spots of change emerge. Regional reduction in median water availability for the Mediterranean is found to nearly double from 9 % to 17 % between 1.5 °C and 2 °C, and the projected lengthening of regional dry spells increases from 7 to 11 %. Projections for agricultural yields differ between crop types as well as world regions. While some (in particular high-latitude) regions may benefit, tropical regions like West Africa, South-East Asia, as well as Central and northern South America are projected to face substantial local yield reductions, particularly for wheat and maize. Best estimate sea-level rise projections based on two illustrative scenarios indicate a 50 cm rise by 2100 relative to year 2000-levels for a 2 °C scenario, and about 10 cm lower levels for a 1.5 °C scenario. In a 1.5 °C scenario, the rate of sea-level rise in 2100 would be reduced by about 30 % compared to a 2 °C scenario. Our findings highlight the importance of regional differentiation to assess both future climate risks and different vulnerabilities to incremental increases in global-mean temperature. The article provides a consistent and comprehensive assessment of existing projections and a good basis for future work on refining our understanding of the difference between impacts at 1.5 °C and 2 °C warming.

549 citations


Journal ArticleDOI
TL;DR: There are discernible differences in climate impacts between 1.5 °C and 2 °C of warming as discussed by the authors, and the extent of countries' near-term mitigation ambition will determine the success of the Paris Agreement's temperature goal.
Abstract: There are discernible differences in climate impacts between 1.5 °C and 2 °C of warming. The extent of countries' near-term mitigation ambition will determine the success of the Paris Agreement's temperature goal.

510 citations


Journal ArticleDOI
TL;DR: In this article, the authors argue that policy decisions made in the next few years to decades will have profound impacts on global climate, ecosystems and human societies, not just for this century, but for the next ten millennia and beyond.
Abstract: Most of the policy debate surrounding the actions needed to mitigate and adapt to anthropogenic climate change has been framed by observations of the past 150 years as well as climate and sea-level projections for the twenty-first century. The focus on this 250-year window, however, obscures some of the most profound problems associated with climate change. Here, we argue that the twentieth and twenty-first centuries, a period during which the overwhelming majority of human-caused carbon emissions are likely to occur, need to be placed into a long-term context that includes the past 20 millennia, when the last Ice Age ended and human civilization developed, and the next ten millennia, over which time the projected impacts of anthropogenic climate change will grow and persist. This long-term perspective illustrates that policy decisions made in the next few years to decades will have profound impacts on global climate, ecosystems and human societies — not just for this century, but for the next ten millennia and beyond.

388 citations


Journal ArticleDOI
TL;DR: This is the first, to the authors' knowledge, estimate of global sea-level (GSL) change over the last ∼3,000 years that is based upon statistical synthesis of a global database of regional sea- level reconstructions, and indicates that, without global warming, GSL in the 20th century very likely would have risen by between −3 cm and +7 cm, rather than the ∼14 cm observed.
Abstract: We assess the relationship between temperature and global sea-level (GSL) variability over the Common Era through a statistical metaanalysis of proxy relative sea-level reconstructions and tide-gauge data. GSL rose at 0.1 ± 0.1 mm/y (2σ) over 0-700 CE. A GSL fall of 0.2 ± 0.2 mm/y over 1000-1400 CE is associated with ∼ 0.2 °C global mean cooling. A significant GSL acceleration began in the 19th century and yielded a 20th century rise that is extremely likely (probability [Formula: see text]) faster than during any of the previous 27 centuries. A semiempirical model calibrated against the GSL reconstruction indicates that, in the absence of anthropogenic climate change, it is extremely likely ([Formula: see text]) that 20th century GSL would have risen by less than 51% of the observed [Formula: see text] cm. The new semiempirical model largely reconciles previous differences between semiempirical 21st century GSL projections and the process model-based projections summarized in the Intergovernmental Panel on Climate Change's Fifth Assessment Report.

372 citations


Journal ArticleDOI
TL;DR: In this article, the authors identify eleven interglacials in the last 800,000 years, a result that is robust to alternative definitions, such as the onset of an interglacial (glacial termination) seems to require a reducing precession parameter (increasing Northern Hemisphere summer insolation), but this condition alone is insufficient.
Abstract: Interglacials, including the present (Holocene) period, are warm, low land ice extent (high sea level), end-members of glacial cycles. Based on a sea level definition, we identify eleven interglacials in the last 800,000 years, a result that is robust to alternative definitions. Data compilations suggest that despite spatial heterogeneity, Marine Isotope Stages (MIS) 5e (last interglacial) and 11c (~400 ka ago) were globally strong (warm), while MIS 13a (~500 ka ago) was cool at many locations. A step change in strength of interglacials at 450 ka is apparent only in atmospheric CO2 and in Antarctic and deep ocean temperature. The onset of an interglacial (glacial termination) seems to require a reducing precession parameter (increasing Northern Hemisphere summer insolation), but this condition alone is insufficient. Terminations involve rapid, nonlinear, reactions of ice volume, CO2, and temperature to external astronomical forcing. The precise timing of events may be modulated by millennial-scale climate change that can lead to a contrasting timing of maximum interglacial intensity in each hemisphere. A variety of temporal trends is observed, such that maxima in the main records are observed either early or late in different interglacials. The end of an interglacial (glacial inception) is a slower process involving a global sequence of changes. Interglacials have been typically 10–30 ka long. The combination of minimal reduction in northern summer insolation over the next few orbital cycles, owing to low eccentricity, and high atmospheric greenhouse gas concentrations implies that the next glacial inception is many tens of millennia in the future.

360 citations


Journal ArticleDOI
TL;DR: In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Concerning on Climate Change (UNFCCC) invited the Inter- governmental Panel on Climate change (IPCC).
Abstract: In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Con- vention on Climate Change (UNFCCC) invited the Inter- governmental Panel on Climate Change ...

348 citations


Journal ArticleDOI
TL;DR: This paper showed that grid-based and point-based simulations and statistical regressions, without deliberate adaptation or CO 2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales.
Abstract: The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO 2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify 'method uncertainty' in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

Journal ArticleDOI
TL;DR: In this article, the authors provide consolidated datasets of historical atmospheric concentrations (mole fractions) of 43 GHGs to be used in the Climate Model Intercomparison Project Phase 6 (CMIP6) experiments.
Abstract: . Atmospheric greenhouse gas (GHG) concentrations are at unprecedented, record-high levels compared to the last 800 000 years. Those elevated GHG concentrations warm the planet and – partially offset by net cooling effects by aerosols – are largely responsible for the observed warming over the past 150 years. An accurate representation of GHG concentrations is hence important to understand and model recent climate change. So far, community efforts to create composite datasets of GHG concentrations with seasonal and latitudinal information have focused on marine boundary layer conditions and recent trends since the 1980s. Here, we provide consolidated datasets of historical atmospheric concentrations (mole fractions) of 43 GHGs to be used in the Climate Model Intercomparison Project – Phase 6 (CMIP6) experiments. The presented datasets are based on AGAGE and NOAA networks, firn and ice core data, and archived air data, and a large set of published studies. In contrast to previous intercomparisons, the new datasets are latitudinally resolved and include seasonality. We focus on the period 1850–2014 for historical CMIP6 runs, but data are also provided for the last 2000 years. We provide consolidated datasets in various spatiotemporal resolutions for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), as well as 40 other GHGs, namely 17 ozone-depleting substances, 11 hydrofluorocarbons (HFCs), 9 perfluorocarbons (PFCs), sulfur hexafluoride (SF6), nitrogen trifluoride (NF3) and sulfuryl fluoride (SO2F2). In addition, we provide three equivalence species that aggregate concentrations of GHGs other than CO2, CH4 and N2O, weighted by their radiative forcing efficiencies. For the year 1850, which is used for pre-industrial control runs, we estimate annual global-mean surface concentrations of CO2 at 284.3 ppm, CH4 at 808.2 ppb and N2O at 273.0 ppb. The data are available at https://esgf-node.llnl.gov/search/input4mips/ and http://www.climatecollege.unimelb.edu.au/cmip6 . While the minimum CMIP6 recommendation is to use the global- and annual-mean time series, modelling groups can also choose our monthly and latitudinally resolved concentrations, which imply a stronger radiative forcing in the Northern Hemisphere winter (due to the latitudinal gradient and seasonality).

Journal ArticleDOI
12 Feb 2016-Science
TL;DR: The results underscore the importance of climate–vegetation–carbon cycle feedbacks at high latitudes and indicate that in recent decades, photosynthetic carbon uptake has reacted much more strongly to warming than have carbon release processes.
Abstract: Atmospheric monitoring of high northern latitudes (above 40°N) has shown an enhanced seasonal cycle of carbon dioxide (CO2) since the 1960s, but the underlying mechanisms are not yet fully understood. The much stronger increase in high latitudes relative to low ones suggests that northern ecosystems are experiencing large changes in vegetation and carbon cycle dynamics. We found that the latitudinal gradient of the increasing CO2 amplitude is mainly driven by positive trends in photosynthetic carbon uptake caused by recent climate change and mediated by changing vegetation cover in northern ecosystems. Our results underscore the importance of climate-vegetation-carbon cycle feedbacks at high latitudes; moreover, they indicate that in recent decades, photosynthetic carbon uptake has reacted much more strongly to warming than have carbon release processes.

Journal ArticleDOI
TL;DR: The Paris Agreement duly reflects the latest scientific understanding of systemic global warming risks as discussed by the authors, and Limiting the anthropogenic temperature anomaly to 1.5-2 °C is possible, yet requires transformational change across the board of modernity.
Abstract: The Paris Agreement duly reflects the latest scientific understanding of systemic global warming risks. Limiting the anthropogenic temperature anomaly to 1.5–2 °C is possible, yet requires transformational change across the board of modernity.

Journal ArticleDOI
TL;DR: It is hypothesized that climate-related disaster occurrence enhances armed-conflict outbreak risk in ethnically fractionalized countries and this observation has important implications for future security policies as several of the world’s most conflict-prone regions are both exceptionally vulnerable to anthropogenic climate change and characterized by deep ethnic divides.
Abstract: Social and political tensions keep on fueling armed conflicts around the world. Although each conflict is the result of an individual context-specific mixture of interconnected factors, ethnicity appears to play a prominent and almost ubiquitous role in many of them. This overall state of affairs is likely to be exacerbated by anthropogenic climate change and in particular climate-related natural disasters. Ethnic divides might serve as predetermined conflict lines in case of rapidly emerging societal tensions arising from disruptive events like natural disasters. Here, we hypothesize that climate-related disaster occurrence enhances armed-conflict outbreak risk in ethnically fractionalized countries. Using event coincidence analysis, we test this hypothesis based on data on armed-conflict outbreaks and climate-related natural disasters for the period 1980–2010. Globally, we find a coincidence rate of 9% regarding armed-conflict outbreak and disaster occurrence such as heat waves or droughts. Our analysis also reveals that, during the period in question, about 23% of conflict outbreaks in ethnically highly fractionalized countries robustly coincide with climatic calamities. Although we do not report evidence that climate-related disasters act as direct triggers of armed conflicts, the disruptive nature of these events seems to play out in ethnically fractionalized societies in a particularly tragic way. This observation has important implications for future security policies as several of the world’s most conflict-prone regions, including North and Central Africa as well as Central Asia, are both exceptionally vulnerable to anthropogenic climate change and characterized by deep ethnic divides.

Journal ArticleDOI
01 Dec 2016-EPL
TL;DR: Complex network analysis of time series opens up new venues to address interdisciplinary challenges in climate dynamics, multiphase flow, brain functions, ECG dynamics, economics and traffic systems.
Abstract: Revealing complicated behaviors from time series constitutes a fundamental problem of continuing interest and it has attracted a great deal of attention from a wide variety of fields on account of its significant importance. The past decade has witnessed a rapid development of complex network studies, which allow to characterize many types of systems in nature and technology that contain a large number of components interacting with each other in a complicated manner. Recently, the complex network theory has been incorporated into the analysis of time series and fruitful achievements have been obtained. Complex network analysis of time series opens up new venues to address interdisciplinary challenges in climate dynamics, multiphase flow, brain functions, ECG dynamics, economics and traffic systems.

Journal ArticleDOI
TL;DR: This paper examines the problem of tracking control of networked multi-agent systems with multiple delays and impulsive effects, whose results are applied to mechanical robotic systems and a relationship between the frequencies of impulses and systems' parameters is unveiled.
Abstract: This paper examines the problem of tracking control of networked multi-agent systems with multiple delays and impulsive effects, whose results are applied to mechanical robotic systems. Four kinds of impulsive effects are taken into account: 1) both the strengths of impulsive effects and the number of nodes injected with impulses are time dependent; 2) the strengths of impulsive effects occur according to certain probabilities and the number of nodes under impulsive control is time varying; 3) the strengths of impulses are time varying, whereas the number of nodes with impulses takes place according to certain probabilities; 4) both the strengths of impulses and the number of nodes with impulsive control occur according to certain probabilities. By utilizing the comparison principle, criteria are established for these different cases and a relationship between the frequencies (occurrence probabilities) of impulses and systems' parameters is unveiled. Finally, an example for tracking control of robotic systems is provided to show the effectiveness of the presented results.

Journal ArticleDOI
01 Oct 2016-Energy
TL;DR: In this article, the authors present and validate a novel and computational efficient time slice approach that is readily applicable to input data for all kinds of power system models, and illustratively determine representative days for the long-term model LIMES-EU and show that a small number of model days developed in this way is sufficient to reflect the characteristic fluctuations of the input data.

Journal ArticleDOI
TL;DR: In this paper, the authors evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the AgMIP.
Abstract: Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.

Journal ArticleDOI
TL;DR: In this article, a causal effect network (CEN) based on graphical models is introduced to assess causal relationships and their time delays between different processes in the Northern Hemisphere midlatitudes.
Abstract: In recent years, the Northern Hemisphere midlatitudes have suffered from severe winters like the extreme 2012/13 winter in the eastern United States. These cold spells were linked to a meandering upper-tropospheric jet stream pattern and a negative Arctic Oscillation index (AO). However, the nature of the drivers behind these circulation patterns remains controversial. Various studies have proposed different mechanisms related to changes in the Arctic, most of them related to a reduction in sea ice concentrations or increasing Eurasian snow cover.Here, a novel type of time series analysis, called causal effect networks (CEN), based on graphical models is introduced to assess causal relationships and their time delays between different processes. The effect of different Arctic actors on winter circulation on weekly to monthly time scales is studied, and robust network patterns are found. Barents and Kara sea ice concentrations are detected to be important external drivers of the midlatitude circula...

Journal ArticleDOI
TL;DR: In this paper, the authors develop a framework that addresses the biophysical, socio-economic, and ethical dimensions of bridging across scales, to provide a consistently applicable approach for translating the planetary boundaries into national-level fair shares of Earth's safe operating space.
Abstract: The planetary boundaries framework proposes quantitative global limits to the anthropogenic perturbation of crucial Earth system processes, and thus marks out a planetary safe operating space for human activities. Yet, decisions regarding resource use and emissions are mostly made at less aggregated scales, by national and sub-national governments, businesses, and other local actors. To operationalize the planetary boundaries concept, the boundaries need to be translated into and aligned with targets that are relevant at these decision-making scales. In this paper, we develop a framework that addresses the biophysical, socio-economic, and ethical dimensions of bridging across scales, to provide a consistently applicable approach for translating the planetary boundaries into national-level fair shares of Earth’s safe operating space. We discuss our findings in the context of previous studies and their implications for future analyses and policymaking. In this way, we link the planetary boundaries framework to widely-applied operational and policy concepts for more robust strong sustainability decision-making.

Journal ArticleDOI
TL;DR: In this paper, a terrestrial biogeochemical model that simulates diverse forest communities suggests that plant trait diversity may enable the Amazon rainforest to adjust to new climate conditions via a process of ecological sorting, protecting the Amazon's carbon sink function.
Abstract: Application of a terrestrial biogeochemical model that simulates diverse forest communities suggests that plant trait diversity may enable the Amazon rainforest to adjust to new climate conditions via a process of ecological sorting. Climate change threatens ecosystems worldwide, yet their potential future resilience remains largely unquantified1. In recent years many studies have shown that biodiversity, and in particular functional diversity, can enhance ecosystem resilience by providing a higher response diversity2,3,4,5. So far these insights have been mostly neglected in large-scale projections of ecosystem responses to climate change6. Here we show that plant trait diversity, as a key component of functional diversity, can have a strikingly positive effect on the Amazon forests’ biomass under future climate change. Using a terrestrial biogeochemical model that simulates diverse forest communities on the basis of individual tree growth7, we show that plant trait diversity may enable the Amazon forests to adjust to new climate conditions via a process of ecological sorting, protecting the Amazon’s carbon sink function. Therefore, plant trait diversity, and biodiversity in general, should be considered in large-scale ecosystem projections and be included as an integral part of climate change research and policy.

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the yield-increasing potential of elevated irrigation water productivity and optimized use of in situ precipitation water (alleviated soil evaporation, enhanced infiltration, water harvesting for supplemental irrigation) under current and projected future climate.
Abstract: As planetary boundaries are rapidly being approached, humanity has little room for additional expansion and conventional intensification of agriculture, while a growing world population further spreads the food gap. Ample evidence exists that improved on-farm water management can close water-related yield gaps to a considerable degree, but its global significance remains unclear. In this modeling study we investigate systematically to what extent integrated crop water management might contribute to closing the global food gap, constrained by the assumption that pressure on water resources and land does not increase. Using a process-based bio-/agrosphere model, we simulate the yield-increasing potential of elevated irrigation water productivity (including irrigation expansion with thus saved water) and optimized use of in situ precipitation water (alleviated soil evaporation, enhanced infiltration, water harvesting for supplemental irrigation) under current and projected future climate (from 20 climate models, with and without beneficial CO2 effects). Results show that irrigation efficiency improvements can save substantial amounts of water in many river basins (globally 48% of non-productive water consumption in an 'ambitious' scenario), and if rerouted to irrigate neighboring rainfed systems, can boost kcal production significantly (26% global increase). Low-tech solutions for small-scale farmers on water-limited croplands show the potential to increase rainfed yields to a similar extent. In combination, the ambitious yet achievable integrated water management strategies explored in this study could increase global production by 41% and close the water-related yield gap by 62%. Unabated climate change will have adverse effects on crop yields in many regions, but improvements in water management as analyzed here can buffer such effects to a significant degree.

Journal ArticleDOI
TL;DR: It is concluded that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges.
Abstract: Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

Journal ArticleDOI
TL;DR: An approach that combines information about the equilibrium sea level response to global warming and last century's observed contribution from the individual components to constrain projections for this century is presented, which may lead to a better understanding of the gap between process-based and global semiempirical approaches.
Abstract: Sea level has been steadily rising over the past century, predominantly due to anthropogenic climate change. The rate of sea level rise will keep increasing with continued global warming, and, even if temperatures are stabilized through the phasing out of greenhouse gas emissions, sea level is still expected to rise for centuries. This will affect coastal areas worldwide, and robust projections are needed to assess mitigation options and guide adaptation measures. Here we combine the equilibrium response of the main sea level rise contributions with their last century's observed contribution to constrain projections of future sea level rise. Our model is calibrated to a set of observations for each contribution, and the observational and climate uncertainties are combined to produce uncertainty ranges for 21st century sea level rise. We project anthropogenic sea level rise of 28-56 cm, 37-77 cm, and 57-131 cm in 2100 for the greenhouse gas concentration scenarios RCP26, RCP45, and RCP85, respectively. Our uncertainty ranges for total sea level rise overlap with the process-based estimates of the Intergovernmental Panel on Climate Change. The "constrained extrapolation" approach generalizes earlier global semiempirical models and may therefore lead to a better understanding of the discrepancies with process-based projections.

Journal ArticleDOI
TL;DR: In this paper, the authors combine results from networks of field experiments and global crop models to present a spatially explicit global perspective on crop water productivity (CWP, the ratio of crop yield to evapotranspiration) for wheat, maize, rice and soybean under elevated CO2 and associated climate change projected for a high-end greenhouse gas emissions scenario.
Abstract: Increasing atmospheric CO2 concentrations are expected to enhance photosynthesis and reduce plant water use. Research now reveals regional disparities in this effect on crops, with potential implications for food production and water consumption. Rising atmospheric CO2 concentrations ([CO2]) are expected to enhance photosynthesis and reduce crop water use1. However, there is high uncertainty about the global implications of these effects for future crop production and agricultural water requirements under climate change. Here we combine results from networks of field experiments1,2 and global crop models3 to present a spatially explicit global perspective on crop water productivity (CWP, the ratio of crop yield to evapotranspiration) for wheat, maize, rice and soybean under elevated [CO2] and associated climate change projected for a high-end greenhouse gas emissions scenario. We find CO2 effects increase global CWP by 10[0;47]%–27[7;37]% (median[interquartile range] across the model ensemble) by the 2080s depending on crop types, with particularly large increases in arid regions (by up to 48[25;56]% for rainfed wheat). If realized in the fields, the effects of elevated [CO2] could considerably mitigate global yield losses whilst reducing agricultural consumptive water use (4–17%). We identify regional disparities driven by differences in growing conditions across agro-ecosystems that could have implications for increasing food production without compromising water security. Finally, our results demonstrate the need to expand field experiments and encourage greater consistency in modelling the effects of rising [CO2] across crop and hydrological modelling communities.

Journal ArticleDOI
TL;DR: These findings provide unequivocal evidence that visual rhythmic stimulation entrains brain oscillations, thus validating the approach of rhythmicstimulation as a manipulation of brain oscillation.
Abstract: The functional relevance of brain oscillations in the alpha frequency range (8-13 Hz) has been repeatedly investigated through the use of rhythmic visual stimulation. The underlying mechanism of the steady-state visual evoked potential (SSVEP) measured in EEG during rhythmic stimulation, however, is not known. There are two hypotheses on the origin of SSVEPs: entrainment of brain oscillations and superposition of event-related responses (ERPs). The entrainment but not the superposition hypothesis justifies rhythmic visual stimulation as a means to manipulate brain oscillations, because superposition assumes a linear summation of single responses, independent from ongoing brain oscillations. Here, we stimulated participants with a rhythmic flickering light of different frequencies and intensities. We measured entrainment by comparing the phase coupling of brain oscillations stimulated by rhythmic visual flicker with the oscillations induced by arrhythmic jittered stimulation, varying the time, stimulation frequency, and intensity conditions. In line with a theoretical concept of entrainment (the so called Arnold tongue), we found the phase coupling to be more pronounced with increasing stimulation intensity as well as at stimulation frequencies closer to each participant's intrinsic frequency. Only inside the Arnold tongue did the conditions significantly differ from the jittered stimulation. Furthermore, even in a single sequence of an SSVEP, we found non-linear features (intermittency of phase locking) that contradict the linear summation of single responses, as assumed by the superposition hypothesis. Our findings provide unequivocal evidence that visual rhythmic stimulation entrains brain oscillations, thus validating the approach of rhythmic stimulation as a manipulation of brain oscillations.

Journal ArticleDOI
TL;DR: Five new forest free-air CO2 enrichment experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space, and a unique opportunity to initiate a model-data interaction as an integral part of experimental design is presented.
Abstract: The first generation of forest free-air CO2 enrichment (FACE) experiments has successfully provided deeper understanding about how forests respond to an increasing CO2 concentration in the atmosphere. Located in aggrading stands in the temperate zone, they have provided a strong foundation for testing critical assumptions in terrestrial biosphere models that are being used to project future interactions between forest productivity and the atmosphere, despite the limited inference space of these experiments with regards to the range of global ecosystems. Now, a new generation of FACE experiments in mature forests in different biomes and over a wide range of climate space and biodiversity will significantly expand the inference space. These new experiments are: EucFACE in a mature Eucalyptus stand on highly weathered soil in subtropical Australia; AmazonFACE in a highly diverse, primary rainforest in Brazil; BIFoR-FACE in a 150-yr-old deciduous woodland stand in central England; and SwedFACE proposed in a hemiboreal, Pinus sylvestris stand in Sweden. We now have a unique opportunity to initiate a model-data interaction as an integral part of experimental design and to address a set of cross-site science questions on topics including responses of mature forests; interactions with temperature, water stress, and phosphorus limitation; and the influence of biodiversity.

Journal ArticleDOI
TL;DR: In this article, the authors combine several published datasets to create a comprehensive set of emissions pathways for each country and Kyoto gas, covering the years 1850 to 2014 with yearly values, for all UNFCCC member states and most non-UNFCCC territories.
Abstract: . To assess the history of greenhouse gas emissions and individual countries' contributions to emissions and climate change, detailed historical data are needed. We combine several published datasets to create a comprehensive set of emissions pathways for each country and Kyoto gas, covering the years 1850 to 2014 with yearly values, for all UNFCCC member states and most non-UNFCCC territories. The sectoral resolution is that of the main IPCC 1996 categories. Additional time series of CO2 are available for energy and industry subsectors. Country-resolved data are combined from different sources and supplemented using year-to-year growth rates from regionally resolved sources and numerical extrapolations to complete the dataset. Regional deforestation emissions are downscaled to country level using estimates of the deforested area obtained from potential vegetation and simulations of agricultural land. In this paper, we discuss the data sources and methods used and present the resulting dataset, including its limitations and uncertainties. The dataset is available from doi:10.5880/PIK.2016.003 and can be viewed on the website accompanying this paper ( http://www.pik-potsdam.de/primap-live/primap-hist/ ).

Journal ArticleDOI
TL;DR: In this article, the authors analyze the dynamics of global fossil resource markets under different assumptions for the supply of fossil fuel resources, development pathways for energy demand, and climate policy settings, and use the REMIND model to explore economic effects of changes in coal, oil and gas markets induced by climate-change mitigation policies.
Abstract: We analyze the dynamics of global fossil resource markets under different assumptions for the supply of fossil fuel resources, development pathways for energy demand, and climate policy settings. Resource markets, in particular the oil market, are characterized by a large discrepancy between costs of resource extraction and commodity prices on international markets. We explain this observation in terms of (a) the intertemporal scarcity rent, (b) regional price differentials arising from trade and transport costs, (c) heterogeneity and inertia in the extraction sector. These effects are captured by the REMIND model. We use the model to explore economic effects of changes in coal, oil and gas markets induced by climate-change mitigation policies. A large share of fossil fuel reserves and resources will be used in the absence of climate policy leading to atmospheric GHG concentrations well beyond a level of 550 ppm CO2-eq. This result holds independently of different assumptions about energy demand and fossil fuel availability. Achieving ambitious climate targets will drastically reduce fossil fuel consumption, in particular the consumption of coal. Conventional oil and gas as well as non-conventional oil reserves are still exhausted. We find the net present value of fossil fuel rent until 2100 at 30tril.US$ with a large share of oil and a small share of coal. This is reduced by 9 and 12tril.US$ to achieve climate stabilization at 550 and 450 ppm CO2-eq, respectively. This loss is, however, overcompensated by revenues from carbon pricing that are 21 and 32tril.US$, respectively. The overcompensation also holds under variations of energy demand and fossil fuel supply.