ALBERT

Description: Code for coupling the Parallel Ice Sheet Model PISM with the Modular Ocean Model MOM

Description: Atlantic hurricane activity varies substantially from year to year and so do the associated damages. Longer-term forecasting of hurricane risks is a key element to reduce damages and societal vulnerabilities by enabling targeted disaster preparedness and risk reduction measures. While the immediate synoptic drivers of tropical cyclone formation and intensification are increasingly well understood, precursors of hurricane activity on longer time-horizons are still not well established. Here we use a causal network-based algorithm to identify physically motivated late-spring precursors of seasonal 15Atlantic hurricane activity. Based on these precursors we construct seasonal forecast models with competitive skill compared to operational forecasts. We present a skillful model to forecast July to October cyclone activity at the beginning of April.Earlier seasonal hurricane forecasting provides a multi-month lead time to implement more effective disaster risk reduction measures. Our approach also highlights the potential of applying causal effects network analysis in seasonal forecasting

Description: Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and assess the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimates of the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes, forcings employed and initial states of ice sheet models. This study presents results from ice flow model simulations from 13 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015–2100 as part of the Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climate model results. Simulations of the Antarctic ice sheet contribution to sea level rise in response to increased warming during this period varies between −7.8 and 30.0 cm of sea level equivalent (SLE) under Representative Concentration Pathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment with constant climate conditions and should therefore be added to the mass loss contribution under climate conditions similar to present-day conditions over the same period. The simulated evolution of the West Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica mass change varies between −6.1 and 8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional simulated mass loss of 28 mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared to simulations done under present-day conditions for the two CMIP5 forcings used and display limited mass gain in East Antarctica.

Description: Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

Description: We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1,500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5C until the end of the century would reduce global output by 7-14% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73-142$/tCO2 in 2020, rising to 92-181$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise.

Description: Mass loss from the Antarctic Ice Sheet constitutes the largest uncertainty in projections of future sea level rise. Ocean-driven melting underneath the floating ice shelves and subsequent acceleration of the inland ice streams is the major reason for currently observed mass loss from Antarctica and is expected to become more important in the future. Here we show that for projections of future mass loss from the Antarctic Ice Sheet, it is essential (1) to better constrain the sensitivity of sub-shelf melt rates to ocean warming and (2) to include the historic trajectory of the ice sheet. In particular, we find that while the ice sheet response in simulations using the Parallel Ice Sheet Model is comparable to the median response of models in three Antarctic Ice Sheet Intercomparison projects – initMIP, LARMIP-2 and ISMIP6 – conducted with a range of ice sheet models, the projected 21st century sea level contribution differs significantly depending on these two factors. For the highest emission scenario RCP8.5, this leads to projected ice loss ranging from 1.4 to 4.0 cm of sea level equivalent in the ISMIP6 simulations where the sub-shelf melt sensitivity is comparably low, opposed to a likely range of 9.2 to 35.9 cm using the exact same initial setup, but emulated from the LARMIP-2 experiments with a higher melt sensitivity based on oceanographic studies. Furthermore, using two initial states, one with and one without a previous historic simulation from 1850 to 2014, we show that while differences between the ice sheet configurations in 2015 are marginal, the historic simulation increases the susceptibility of the ice sheet to ocean warming, thereby increasing mass loss from 2015 to 2100 by about 50 %. Our results emphasize that the uncertainty that arises from the forcing is of the same order of magnitude as the ice dynamic response for future sea level projections.

Description: This software can be used to quantify emissions mitigation targets stated in the Nationally Determined Contributions (NDCs). The output includes national targets and emissions pathways and globally aggregated mitigated emissions pathways. Several quantification options are available, including, i.a., the five marker scenarios of the Shared Socioeconomic Pathways (SSPs) as baseline trajectories.

Description: Power systems are subject to fundamental changes due to the increasing infeed of decentralized renewable energy sources and storage. The decentralized nature of the new actors in the system requires new concepts for structuring the power grid and achieving a wide range of control tasks ranging from seconds to days. Here, we introduce a multiplex dynamical network model covering all control timescales. Crucially, we combine a decentralized, self-organized low-level control and a smart grid layer of devices that can aggregate information from remote sources. The safety-critical task of frequency control is performed by the former and the economic objective of demand matching dispatch by the latter. Having both aspects present in the same model allows us to study the interaction between the layers. Remarkably, we find that adding communication in the form of aggregation does not improve the performance in the cases considered. Instead, the self-organized state of the system already contains the information required to learn the demand structure in the entire grid. The model introduced here is highly flexible and can accommodate a wide range of scenarios relevant to future power grids. We expect that it is especially useful in the context of low-energy microgrids with distributed generation. Highly decentralized power grids, possibly in the context of prosumer systems, require new concepts for their stable operation. We expect that both self-organized systems and intelligent devices with communication capability that can aggregate information from remote sources will play a central role. Here, we introduce a multiplex network model that combines both aspects and use it in a basic scenario and uncover surprising interactions between the layers.

Description: Outlier detection refers to the identification of rare items that are deviant from the general data distribution. Existing approaches suffer from high computational complexity, low predictive capability, and limited interpretability. As a remedy, we present a novel outlier detection algorithm called COPOD, which is inspired by copulas for modeling multivariate data distribution. COPOD first constructs a empirical copula, and then uses it to predict tail probabilities of each given data point to determine its level of “extremeness”. Intuitively, we think of this as calculating an anomalous p-value. This makes COPOD both parameter-free, highly interpretable, and computationally efficient. In this work, we make three key contributions, 1) propose a novel, parameterfree outlier detection algorithm with both great performance and interpretability, 2) perform extensive experiments on 30 benchmark datasets to show that COPOD outperforms in most cases and is also one of the fastest algorithms, and 3) release an easy-to-use Python implementation for reproducibility.

Description: Input data for the PISM-MOM coupling framework as used in Kreuzer et al., Geoscientific Model Development publication (gmd-2020-230) [Coupling framework (1.0) for the ice sheet model PISM (1.1.1) and the ocean model MOM5 (5.1.0) via the ice-shelf cavity module PICO]

Description: One of the most challenging issues in Mediterranean ecosystems to date has been to understand the emergence of discontinuous changes or catastrophic shifts. In the era of the 2030 Sustainable Development Goals, which encompass ideas around Land Degradation Neutrality, advancing this understanding has become even more critical and urgent. The aim of this paper is to synthesize insights into the drivers, processes and management of catastrophic shifts to highlight ways forward for the management of Mediterranean ecosystems. We use a multidisciplinary approach that extends beyond the typical single site, single scale, single approach studies in the current literature. We link applied and theoretical ecology at multiple scales with analyses and modeling of human–environment–climate relations and stakeholder engagement in six field sites in Mediterranean ecosystems to address three key questions: i) How do major degradation drivers affect ecosystem functioning and services in Mediterranean ecosystems? ii) What processes happen in the soil and vegetation during a catastrophic shift? iii) How can management of vulnerable ecosystems be optimized using these findings? Drawing together the findings from the use of different approaches allows us to address the whole pipeline of changes from drivers through to action. We highlight ways to assess ecosystem vulnerability that can help to prevent ecosystem shifts to undesirable states; identify cost-effective management measures that align with the vision and plans of land users; and evaluate the timing of these measures to enable optimization of their application before thresholds are reached. Such a multidisciplinary approach enables improved identification of early warning signals for discontinuous changes informing more timely and cost-effective management, allowing anticipation of, adaptation to, or even prevention of, undesirable catastrophic ecosystem shifts.

Description: This archive provides the model result of the AbuMIP experiments: The Antarctic BUttressing Model Intercomparison Project.

Description: The EMF-30 study uses a scenario approach in which a coordinated suite of scenarios is used to explore how stylized global policies to reduce SLCFs impacts emissions, concentrations, radiative forcing, and global temperature change. The SLCF reduction scenarios focus on methane across all sectors and black carbon from transportation and buildings. Greenhouse gas (GHG) mitigation scenarios are also considered, including the combination of GHG and SLCF mitigation.

Description: Antarctica’s ice shelves modulate the grounded ice flow, and weakening of ice shelves due to climate forcing will decrease their ‘buttressing’ effect, causing a response in the grounded ice. While the processes governing ice-shelf weakening are complex, uncertainties in the response of the grounded ice sheet are also difficult to assess. The Antarctic BUttressing Model Intercomparison Project (ABUMIP) compares ice-sheet model responses to decrease in buttres-sing by investigating the ‘end-member’ scenario of total and sustained loss of ice shelves. Although unrealistic, this scenario enables gauging the sensitivity of an ensemble of 15 ice-sheet models to a total loss of buttressing, hence exhibiting the full potential of marine ice-sheet instability. All models predict that this scenario leads to multi-metre (1–12 m) sea-level rise over 500 years from present day. West Antarctic ice sheet collapse alone leads to a 1.91–5.08 m sea-level rise due to the marine ice-sheet instability. Mass loss rates are a strong func-tion of the sliding/friction law, with plastic laws cause a further destabilization of the Aurora and Wilkes Subglacial Basins, East Antarctica. Improvements to marine ice-sheet models have greatly reduced variability between modelled ice-sheet responses to extreme ice-shelf loss, e.g. compared to the SeaRISE assessments.

Description: Global Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is 〉 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge 〉 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds.

Description: The planetary boundaries concept was formulated in 2009 by an international research group led by Johan Rockström,and revised in 2015 by Will Steffen and colleagues(Rockström et al. 2009; Steffen et al. 2015b). The concept emerged against the background of the Anthropocene–a period of timeasso-ciated with rapidly growing environmental pressures,and increasing degradation and scarcity of global environmental resources,which intensifies risks for the stability and functioning of the Earth system. The human burden on the global environment and ecosystems has reached a level where sud-den non-linear systemic changes can no longer be ruled out. The UFOPLAN project 'Planetary Boundaries –Challengesfor Science, Civil Society and Politics' (FKZ 3714 100 0) addresses the challenge of operationalizing the planetary boundaries concept. The project analyzesthe requirements that the concept places on politics, science, civil society and business, with the aim ofinformingthe political implementation of the concept. In addition to cross-sectional papers that deal with topics of significance for various political processes (e.g., the potential for environmen-tal communication, risks associated withtransgressing boundaries and a methodology for operational-ization), political focus topics were addressed. The political focus topics addressquestionsof how the planetary boundaries conceptcan be applied to specific environmental policymakingareas (e.g.,the formulation of a national nitrogen strategy and the Integrated Environmental Programme 2030). Important next steps for the operationalization of the concept include thestronger inclusion of plane-tary boundaries in sustainability strategies and a reorientation of science fundingtoward the inte-grated development of the concept.

Description: Abstract. Tropical convective activity represents a source of predictability for mid-latitude weather in the Northern Hemi-sphere. In winter, the El Niño–Southern Oscillation (ENSO) is the dominant source of predictability in the tropics and ex-tratropics, but its role in summer is much less pronounced and the exact teleconnection pathways are not well under-stood. Here, we assess how tropical convection interacts with mid-latitude summer circulation at different intra-seasonal timescales and how ENSO affects these interactions. First, we apply maximum covariance analysis (MCA) between tropical convective activity and mid-latitude geopotential height fields to identify the dominant modes of interaction. The first MCA mode connects the South Asian monsoon with the mid-latitude circumglobal teleconnection pattern. The second MCA mode connects the western North Pacific summer monsoon in the tropics with a wave-5 pattern centred over the North Pacific High in the mid-latitudes. We show that the MCA patterns are fairly insensitive to the selected intra-seasonal timescale from weekly to 4-weekly data. To study the potential causal interdependencies between these modes and with other atmospheric fields, we apply the causal discovery method PCMCI at different timescales. PCMCI extends standard correlation analysis by removing the con-founding effects of autocorrelation, indirect links and com-mon drivers. In general, there is a two-way causal interaction between the tropics and mid-latitudes, but the strength and sometimes sign of the causal link are timescale dependent. We introduce causal maps that show the regionally specific causal effect from each MCA mode. Those maps confirm the dominant patterns of interaction and in addition high-light specific mid-latitude regions that are most strongly con-nected to tropical convection. In general, the identified causal teleconnection patterns are only mildly affected by ENSO and the tropical mid-latitude linkages remain similar. Still, La Niña strengthens the South Asian monsoon generating a stronger response in the mid-latitudes, while during El Niño years the Pacific pattern is reinforced. This study paves the way for process-based validation of boreal summer telecon-nections in (sub-)seasonal forecast models and climate mod-els and therefore works towards improved sub-seasonal pre-dictions and climate projections.

Description: The isotopic composition of Si in biogenic silica (BSi), such as opal buried in the oceans' sediments, has changed over time. Paleo records suggest that the isotopic composition, described in terms of δ30Si, was generally much lower during glacial times than today. There is consensus that this variability is attributable to differing environmental conditions at the respective time of BSi production and sedimentation. The detailed links between environmental conditions and the isotopic composition of BSi in the sediments remain, however, poorly constrained. In this study, we explore the effects of a suite of offset boundary conditions during the LGM on the isotopic composition of BSi archived in sediments in an Earth System Model of intermediate complexity. Our model results suggest that a change in the isotopic composition of Si supply to the glacial ocean is sufficient to explain the observed overall low (er) glacial δ30Si in BSi. All other processes explored triggered model responses of either wrong sign or magnitude, or are inconsistent with a recent estimate of bottom water oxygenation in the Atlantic Sector of the Southern Ocean. Caveats, mainly associated with generic uncertainties in today's pelagic biogeochemical modules, remain.

Description: This is the PISM code version used for the Antarctic Ice Sheet hysteresis simulations published and discussed in Garbe, J., Albrecht, T., Levermann, A., Donges, J. F., and Winkelmann, R. The hysteresis of the Antarctic Ice Sheet. Nature 585(7826), 2020. The code is based on PISM release v1.0, but contains several improvements and modifications

Description: Should economic growth continue in a world threatened by the prospect of catastrophic climate change? The scientific and public debate has brought forth a broad spectrum of views and narratives on this question, ranging from neoclassical economics to degrowth. We argue that different positions can be attributed to underlying differences in views on (a) factors that determine human well‐being, (b) the feasibility and desirability of economic growth, (c) appropriate intervention points, and (d) preferences about governance and policy options. For each of these dimensions, we propose points of agreement on which a consensus between conflicting positions might be achieved. From this basis, we distill a sustainability transition perspective that could act as a basis for a renewed debate on how to align human well‐being with environmental sustainability.

Description: This paper explores the consequences of different policy assumptions and the derivation of globally consistent, national low-carbon development pathways for the seven largest greenhouse gas (GHG)–emitting countries (EU28 as a bloc) in the world, covering approximately 70% of global CO2 emissions, in line with their contributions to limiting global average temperature increase to well below 2 °C as compared with pre-industrial levels. We introduce the methodology for developing these pathways by initially discussing the process by which global integrated assessment model (IAM) teams interacted and derived boundary conditions in the form of carbon budgets for the different countries. Carbon budgets so derived for the 2011–2050 period were then used in eleven different national energy-economy models and IAMs for producing low-carbon pathways for the seven countries in line with a well below 2 °C world up to 2050. We present a comparative assessment of the resulting pathways and of the challenges and opportunities associated with them. Our results indicate quite different mitigation pathways for the different countries, shown by the way emission reductions are split between different sectors of their economies and technological alternatives.

Description: Understanding cities as complex systems, sustainable urban planning depends on reliable high-resolution data, for example of the building stock to upscale region-wide retrofit policies. For some cities and regions, these data exist in detailed 3D models based on real-world measurements. However, they are still expensive to build and maintain, a significant challenge, especially for small and medium-sized cities that are home to the majority of the European population. New methods are needed to estimate relevant building stock characteristics reliably and cost-effectively. Here, we present a machine learning based method for predicting building heights, which is based only on open-access geospatial data on urban form, such as building footprints and street networks. The method allows to predict building heights for regions where no dedicated 3D models exist currently. We train our model using building data from four European countries (France, Italy, the Netherlands, and Germany) and find that the morphology of the urban fabric surrounding a given building is highly predictive of the height of the building. A test on the German state of Brandenburg shows that our model predicts building heights with an average error well below the typical floor height (about 2.5 m), without having access to training data from Germany. Furthermore, we show that even a small amount of local height data obtained by citizens substantially improves the prediction accuracy. Our results illustrate the possibility of predicting missing data on urban infrastructure; they also underline the value of open government data and volunteered geographic information for scientific applications, such as contextual but scalable strategies to mitigate climate change.

Description: This policy brief explores and provides a holistic view of the existing practices, issues, and opportunities for a sustainable coastal management initiative among the G20 member countries. Specifically, it highlights coastal disaster risk reduction and resilience strategies, along with the financial implications of public investment on the need of a proper assessment of the social return of adaptation projects, and on the avoided fiscal deadweight loss. The brief also discusses the importance of funding for development projects to reach mitigation targets and the need for an evaluation framework to improve the efficiency of these adaptation efforts. The policy brief suggests establishing an initiative within the G20 to address disaster risk reduction (G20- DRR) by providing a decision support system as well as a centralized dissemination platform for quality-controlled, transparent national climate impact assessments by fostering global collaboration between institutions, researchers, and experts.

Description: We know perfectly well that the combined effects of anthropogenic climate change and natural var-iability are very likely to lead to major, undesira-ble climate impacts for most citizens around the world in the not-so-distant future. To limit cli-mate impacts is essentially about weaning the world economy off greenhouse gases, adapting to those climate impacts that were not avoided, and compensating for what we cannot adapt to. All of these three components of climate policy are pursued under the auspices of the 1992 UN Frame-work Convention on Climate Change (UNFCCC), yet also by many countries, social movements, and forward-looking businesses alike (Luterbacher and Sprinz 2018).

Description: Chamberlin and Salisbury's assessment of the Permian a century ago captured the essence of the period: it is an interval of extremes yet one sufficiently recent to have affected a biosphere with near-modern complexity. The events of the Permian – the orogenic episodes, massive biospheric turnovers, both icehouse and greenhouse antitheses, and Mars-analog lithofacies – boggle the imagination and present us with great opportunities to explore Earth system behavior. The ICDP-funded workshops dubbed “Deep Dust,” held in Oklahoma (USA) in March 2019 (67 participants from nine countries) and Paris (France) in January 2020 (33 participants from eight countries), focused on clarifying the scientific drivers and key sites for coring continuous sections of Permian continental (loess, lacustrine, and associated) strata that preserve high-resolution records. Combined, the two workshops hosted a total of 91 participants representing 14 countries, with broad expertise. Discussions at Deep Dust 1.0 (USA) focused on the primary research questions of paleoclimate, paleoenvironments, and paleoecology of icehouse collapse and the run-up to the Great Dying and both the modern and Permian deep microbial biosphere. Auxiliary science topics included tectonics, induced seismicity, geothermal energy, and planetary science. Deep Dust 1.0 also addressed site selection as well as scientific approaches, logistical challenges, and broader impacts and included a mid-workshop field trip to view the Permian of Oklahoma. Deep Dust 2.0 focused specifically on honing the European target. The Anadarko Basin (Oklahoma) and Paris Basin (France) represent the most promising initial targets to capture complete or near-complete stratigraphic coverage through continental successions that serve as reference points for western and eastern equatorial Pangaea.

Description: Previous studies have projected a significant role for bioenergy in decarbonizing the global economy and helping realize international climate goals such as limiting global average warming to 2 ˚C or 1.5 ˚C. However, with substantial variability in bioenergy results and significant concerns about potential environmental and social implications, greater transparency and dedicated assessment of the underlying modeling and results and more detailed understanding of the potential role of bioenergy are needed. Stanford University’s Energy Modeling Forum (EMF) initiated a 33rd study (EMF-33) to explore the viability of large-scale bioenergy as part of a comprehensive climate management strategy. This special issue presents the papers of the EMF-33 study—a multi-year inter-model comparison project designed to understand and assess global, long-run biomass supply and bioenergy deployment potentials and related uncertainties. Using a novel scenario design with independent biomass supply and bioenergy demand protocols, EMF-33 separately elucidates and explores the modeling of biomass feedstock supplies and bioenergy technologies and their deployment—revealing, comparing, and assessing the modeling that is suggesting that bioenergy could be a key climate containment strategy. This introduction provides an overview of the EMF-33 study design and the overview, thematic, and individual modeling team papers and types of insights that make up this special issue. By providing enhanced transparency and new detailed insights, we hope to inform policy dialogue about the potential role of bioenergy and facilitate new research.

Description: Dataset containing all greenhouse gas emissions data submitted by countries under climate change convention (CRF data) as published by the UNFCCC secretariat at 2020-10-25

Description: Climate change is one of the most pressing political issues of our time. Science is uncovering the unprecedented nature and scale of its impacts on people, economies and ecosystems worldwide. One critical dimension of these impacts is their effect on international peace and security.This report summarises the state of knowledge regarding security risks related to climate change. To this end, it synthesises and contextualises the existing scientific evidence. It does not reflect all aspects of the debate that have emerged across social science but focuses on those that are particularly relevant at the political level.Climate change itself is rarely a direct cause of conflict. Yet, there is ample evidence that its effects exacerbate important drivers and contextual factors of conflict and fragility, thereby challenging the stability of states and societies.

Description: Taking a comparative case study approach between Canada and Germany, this book investigates the contrasting response of governments to anti-wind movements. Environmental social movements have been critical players for encouraging the shift towards increased use of renewable energy. However, social movements mobilizing against the installation of wind turbines have now become a major obstacle to their increased deployment. Andrea Bues draws on a cross-Atlantic comparative analysis to investigate the different contexts of contentious energy policy. Focusing on two sub-national forerunner regions in installed wind power capacity – Brandenburg and Ontario – Bues draws on social movement theory to explore the concept of discursive energy space and propose explanations as to why governments respond differently to social movements. Overall, Social Movements against Wind Power in Canada and Germany offers a novel conceptualization of discursive-institutional contexts of contentious energy politics and helps better understand protest against renewable energy policy. This book will be of great interest to students and scholars of renewable energy policy, sustainability and climate change politics, social movement studies and environmental sociology.

Description: 1. Introduction: Renewable Energy Politics and Protest 2. Contentious Wind Energy and Context 3. Renewable Energy Policy and Politics in Canada and Germany 4. Larger Setbacks, Saving the Forests: The Anti-Wind Movement in Germany, Case Study Brandenburg 5. Preserving Health, Curbing Costs: The Anti-Wind Movement in Canada, Case Study Ontario 6. Contention in Context: Governmental Response to Social Movements 7. Conclusion: The Changing Winds of Discourses on Decarbonization

Description: Grasslands are subject to degradation in arid and semi-arid areas as the result of various pressures, including climate change. Therefore, spatial and temporal monitoring of vegetation cover fluctuation is needed for better understanding and management of natural resources to sustain livelihoods that depend on these grasslands. In this study, changes in vegetation cover were monitored over 1985-2015, using vegetation indices derived from the Landsat images in Chaharmahal-va-Bakhtiyari province, Iran. The percentage of vegetation cover was recorded from sampling plots in the study areas and vegetation indices were calculated from Landsat data over the study period. The relationship between vegetation cover and climate parameters (temperature (T) and precipitation (P)) was determined from precipitation maps, produced from spatial interpolation of weather stations data and temperature maps, produced by regression equation established between DEM-derived elevation and temperature. Then, a regression equation between climate variables and vegetation cover over a period of 30 years’ period was developed and applied on projected climatic variables for the 2050 under RCP2.6 and RCP8.5 scenarios. The Green Vegetation Index (GVI) was found to be the best index for estimation of vegetation cover from the correlation coefficient (r=0.79) and model RMSE (1.98). The GVI fluctuation was associated with the fluctuation in climate variables, and this was especially evident in especially dry years (1999, 2001 and 2012). From the difference between current and future vegetation cover maps, future vegetation cover change maps were produced and vulnerable areas most likely to be impacted by climate change were identified. The results predict that vegetation cover will be reduced under both scenarios, mostly in the eastern parts of the study region, while 5-25% of vegetation cover increases are projected for some areas in the western parts of the region. Further analysis showed that currently, oak forest covers large swaths of the western parts adjacent to grasslands, but forest degradation will lead to increase of grassland areas at the expense of oak forests. Overall, substantial loss of vegetation cover is predicted in the central parts and extends to the southern parts of the province. Loss of vegetation cover would pave the way to conversion of grassland to other non-productive cover types for pastoral systems. Appropriate management programs and adaptation strategies should be designed and implemented to reduce climate change impacts on grasslands in the identified vulnerable areas.