ALBERT

Description: Open data, as an essential element in the sustainable development of the digital economy, is highly valued by many relevant sectors in the implementation process. However, most studies suppose that there are only data providers and users in the open data process and ignore the existence of data regulators. In order to establish long-term green supply relationships between multistakeholders, we hereby introduce data regulators and propose an evolutionary game model to observe the cooperation tendency of multistakeholders (data providers, users, and regulators). The newly proposed game model enables us to intensively study the trading behavior which can be realized as strategies and payoff functions of the data providers, users, and regulators. Besides, a replicator dynamic system is built to study evolutionary stable strategies of multistakeholders. In simulations, we investigate the evolution of the cooperation ratio as time progresses under different parameters, which is proved to be in agreement with our theoretical analysis. Furthermore, we explore the influence of the cost of data users to acquire data, the value of open data, the reward (penalty) from the regulators, and the data mining capability of data users to group strategies and uncover some regular patterns. Some meaningful results are also obtained through simulations, which can guide stakeholders to make better decisions in the future.

Description: The article evidences to what extent rights-based climate litigation is applied as a strategy to enhance the recognition and protection of climate-induced migrants. Adopting a deduc- tive approach and desk review, the study, illustrates how climate-induced migration has been addressed by International Human Rights Law, with some attention also paid to the growing application of the right to a safe climate and climate justice. The study highlights the duties of both States and private actors in tackling the emerging climate crisis under the human rights agenda. Relevant responsibilities are framed in particular within the scope of rights-based litiga- tion dealing with the topic. We present an analysis of litigation linked to climate-induced migration that was filed before distinct international, regional, and national jurisdictions and, in doing so, propose a chronology of cases—structured in three generations—of how population movements as a result of climate change have been discussed by judicial means. The first generation relates to cases that consider the issue from the perspective of protection—in both national, regional, and international jurisdictions. The second generation emerges within general climate litigation claims, involving commitments linked to the climate agenda. In addition to raising (forced) pop- ulation movements as one of the expected impacts of climate change, such cases frequently call upon a rights-based approach. The third generation encompasses rights-based cases cen- tred on climate-induced migrants per se. The strengths and limitations of rights-based litigation to respond to the topic are finally highlighted: we conclude that litigation remains a blunt but not unpromising tool to respond to climate-induced migration. Generic references to the risk of (forced) population movements largely prevail; nevertheless, strategic rights-based litigation can facilitate the visibility of climate-induced migrants to the international community, fostering the development of legal solutions in the longer term.

Description: The complex phase interactions of the two-phase flow are a key factor in understanding the flow pattern evolutional mechanisms, yet these complex flow behaviors have not been well understood. In this paper, we employ a series of gas–liquid two-phase flow multivariate fluctuation signals as observations and propose a novel interconnected ordinal pattern network to investigate the spatial coupling behaviors of the gas–liquid two-phase flow patterns. In addition, we use two network indices, which are the global subnetwork mutual information (⁠ ⁠) and the global subnetwork clustering coefficient (⁠ ⁠), to quantitatively measure the spatial coupling strength of different gas–liquid flow patterns. The gas–liquid two-phase flow pattern evolutionary behaviors are further characterized by calculating the two proposed coupling indices under different flow conditions. The proposed interconnected ordinal pattern network provides a novel tool for a deeper understanding of the evolutional mechanisms of the multi-phase flow system, and it can also be used to investigate the coupling behaviors of other complex systems with multiple observations.

Description: Global hydrological models (GHMs) are widely used to assess the impact of climate change on streamflow, floods, and hydrological droughts. For the 'model evaluation and impact attribution' part of the current round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a), modelling teams generated historical simulations based on observed climate and direct human forcings with updated model versions. Here we provide a comprehensive evaluation of daily and maximum annual discharge based on ISIMIP3a simulations from nine GHMs by comparing the simulations to observational data from 644 river gauge stations. We also assess low flows and the effects of different river routing schemes. We find that models can reproduce variability in daily and maximum annual discharge, but tend to overestimate both quantities, as well as low flows. Models perform better at stations in wetter areas and at lower elevations. Discharge routed with the river routing model CaMa-Flood can improve the performance of some models, but for others, variability is overestimated, leading to reduced model performance. This study indicates that areas for future model development include improving the simulation of processes in arid regions and cold dynamics at high elevations. We further suggest that studies attributing observed changes in discharge to historical climate change using the current model ensemble will be most meaningful in humid areas, at low elevations, and in places with a regular seasonal discharge as these are the regions where the underlying dynamics seem to be best represented.

Description: Urban agriculture, including peri-urban farming, can nourish around one billion city dwellers and provide multiple social, economic, and environmental benefits. However, these benefits depend on various factors and are debated. Therefore, we used machine learning to semi-automate a systematic review of the existing literature on urban agriculture. It started with around 76,000 records for initial screening based on a broad keyword search strategy. We applied the topic modeling approach to systematically understand various aspects of urban agriculture based on the full text of around 1450 relevant publications. Urban agriculture literature covers 14 topics, clustered into 11 themes related to urban agriculture forms, their multi-functionalities, and their underlying challenges. These forms are small-scale ground-based and building-integrated systems. The multifunctionalities include food, livelihoods, health benefits, social space, green infrastructure, biodiversity, and ecosystem services. Therefore, promoting urban agriculture requires accounting for its multi-functionalities, besides food provisioning,and encouraging efficient and sustainable practices.

Description: Having experienced low prices for about a decade, the European Union Emissions Trading System has been supplemented with the market stability reserve (MSR) that adjusts the supply of allowances to market outcomes. We critically review the literature assessing the performance of the MSR against several policy objectives. In doing so, we cover both conceptual aspects and quantitative assessments. We conclude by pointing out important policy implications and open issues for further research.

Description: Carbon prices in the EU emissions trading system are a key instrument driving Europe’s decarbonization. Between 2017 and 2021, they surged tenfold, exceeding €80 tCO2−1 and reshaping investment decisions across the electricity and industry sectors. What has driven this increase is an open question. While it coincided with two significant reforms tightening the cap (‘MSR reform’ and ‘Fit for 55’), we argue that a reduced supply of allowances alone cannot fully explain the price rise. A further crucial aspect is that actors must have become more farsighted as the reform signalled policymakers’ credible long-term commitment to climate targets. This is consistent with model results that show historic prices can be better explained with myopic actors, whereas explaining prices after the reforms requires actors to be farsighted. To underline the role of credibility, we test what would happen if a crisis undermines policy credibility such that actors become myopic again, demonstrating that carbon prices could plummet and endanger the energy transition.

Description: In diesem Positionspapier zur Neubewertung der DGE-Position zu veganer Ernährung werden neben neuen Daten zur Gesundheit auch die weiteren Zieldimensionen einer nachhaltigeren Ernährung (Umwelt, Tierwohl und Soziales) betrachtet. Zur Identifizierung relevanter Publikationen wurden ein Umbrella Review und ein ergänzendes systematisches Review durchgeführt sowie weitere Publikationen berücksichtigt. Die Betrachtung der Zieldimensionen Tierwohl und Soziales zeigt, dass die bisherigen Ansätze zur Bewertung der Auswirkung von Ernährungsweisen in diesem Zusammenhang noch nicht ausreichend etabliert sind und nicht umfassend angewendet werden. Daher werden nur die Zieldimensionen Gesundheit und Umwelt in die Position einbezogen. Gegenüber anderen Ernährungsweisen wurden bei einer veganen Ernährung potenzielle Vor- und Nachteile für die Gesundheit identifiziert. Für die gesunde erwachsene Allgemeinbevölkerung kann neben anderen Ernährungsweisen auch eine vegane Ernährung, unter der Voraussetzung der Einnahme eines Vitamin-B12- Präparats, einer ausgewogenen, gut geplanten Lebensmittelauswahl sowie einer bedarfsdeckenden Zufuhr der potenziell kritischen Nährstoffe (ggf. auch durch weitere Nährstoffpräparate), eine gesundheitsfördernde Ernährung darstellen. Für die vulnerablen Gruppen Kinder, Jugendliche, Schwangere, Stillende und Senior*innen kann die DGE aufgrund der weiterhin eingeschränkten Datenlage weder eine eindeutige Empfehlung für noch gegen eine vegane Ernährung aussprechen. Aufgrund des Risikos für potenzielle, teilweise irreversible Konsequenzen bei inadäquater Durchführung müssen für eine vegane Ernährung in vulnerablen Gruppen besonders fundierte Ernährungskompetenzen vorliegen. Eine Ernährungsberatung durch qualifizierte Fachkräfte ist daher für diese Gruppen dringend angeraten. Eine vegane Ernährung ist als äußerst umweltfreundlich anzusehen, sie stellt eine empfehlenswerte Maßnahme zur Verringerung der Umweltbelastungen des Ernährungssystems dar. Unter Berücksichtigung sowohl gesundheits- als auch umweltrelevanter Aspekte ist eine Ernährungsweise mit einer deutlichen Reduktion tierischer Lebensmittel zu empfehlen.

Description: What role do socio-demographic and local environmental factors play in the perception of climate change? The article of Landwehr et al. to be discussed here presents interdisciplinary findings on this question, which are particularly interesting regarding the group of farmers. However, the findings also raise questions about the degree of abstraction of climate perception, the rigidity of social identity, the role of the media and the strategy of targeting. In the context of recent “farmer protests” and populist narratives, the author of this response concludes that future interdisciplinary research projects on climate perceptions should also analyse political variables and the relevance of populist discourses.

Description: Welche Rolle spielen sozio-demografische und lokale Umweltfaktoren für die Klimawandelwahrnehmung? Der hier besprochene Artikel von Landwehr et al. stellt interdisziplinäre Befunde zu dieser Frage vor, die besonders mit Blick auf die Gruppe der Landwirt(inn)e(n) interessant sind. Die Befunde werfen aber auch Fragen zum Abstraktionsgrad der Klimawahrnehmung, der Rigidität sozialer Identität, der Rolle der Medien und der Zielgruppenstrategie auf. Im Kontext der jüngsten ,,Bauernproteste“ und populistischer Narrative folgert der Autor dieser Reaktion, dass in künftigen interdisziplinären Forschungsprojekten zur Klimawahrnehmung auch politische Variablen und die Relevanz populistischer Diskurse untersucht werden sollten.

Description: Climate change poses a threat to the agricultural sector, increasing the risk of crop failures, food insecurity and poverty. Given the need for an efficient allocation of scarce adaptation finance, scientific evidence can help to guide the prioritization of adaptation options. This article offers reflections on lessons learned from the AGRICA project, a collaboration between the Potsdam Institute for Climate Impact Research (PIK) and Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) on behalf of the German Federal Ministry for Economic Cooperation and Development (BMZ). Running from 2018 to 2024, AGRICA aimed to provide scientific evidence on climate risks, related impacts and suitable adaptation strategies for the agricultural sector in sub-Saharan Africa. Bringing together insights from science, development cooperation and policy, we argue for the need to produce and use rigorous scientific evidence for adaptation policy and planning, including for the formulation and implementation of ambitious National Adaptation Plans (NAPs) and Nationally Determined Contributions (NDCs). This is motivated by assessments such as from the IPCC (2022), which deems current NDC efforts in the agricultural sector insufficient for achieving the Paris Agreement. We discuss lessons learned with a focus on trade-offs between in-depth and standardized assessments, data availability and spatial resolution, modelling uncertainty and methodological pluralism to bridge the science-policy gap.

Description: Forest ecosystems, their products and services play an important role in achieving ambitious climate change mitigation objectives at the same time requiring profound adaptation to climate change. Forest management schemes to support climate action have to be developed within their regional context but also have to be aligned with national or EU-level climate, forest and sustainability policies.The conference on “Managing forests in the 21st century” is the final conference of the FORMASAM, REFORCEand FOREXCLIMresearch projects. The conference bringstogether scientific experts on forest management from all over Europe facing very specific management challenges. The aim isto discuss and improve the understanding therole of forests and forest management in the context of climate change. The conference addressesclimate change impacts, as well as needs for mitigation and adaptation especially with regard to the following scientific questions:1.What are the impacts of climate extremes and disturbances?2.What are the management challenges (and options) for resilient forests?3.What can we do to increase the contribution of forest management to climate change mitigation?

Description: This article investigates the event-triggered adaptive containment control problem for a class of stochastic nonlinear multiagent systems with unmeasurable states. A stochastic system with unknown heterogeneous dynamics is established to describe the agents in a random vibration environment. Besides, the uncertain nonlinear dynamics are approximated by radial basis function neural networks (NNs), and the unmeasured states are estimated by constructing the NN-based observer. In addition, the switching-threshold-based event-triggered control method is adopted with the hope of reducing communication consumption and balancing system performance and network constraints. Moreover, we develop the novel distributed containment controller by utilizing the adaptive backstepping control strategy and the dynamic surface control (DSC) approach such that the output of each follower converges to the convex hull spanned by multiple leaders, and all signals of the closed-loop system are cooperatively semi-globally uniformly ultimately bounded in mean square. Finally, we verify the efficiency of the proposed controller by the simulation examples.

Description: This paper presents a study on the predefined-time (PdT) and practical PdT synchronization of competitive neural networks (CNN) in the presence of different time scales and external disturbances. Two types of external disturbances, which satisfy Lipschitz or bounded conditions, are investigated respectively. The new PdT and practical PdT stability theorems are derived in singularly perturbed systems, where the final residual set is given in detail. By employing the newly derived stability theorems, novel autonomous controllers are designed without relying on a continuous linear term and time scale parameters, while enabling PdT or practical PdT synchronization for drive-response CNNs. Additionally, upper bounds for the settling time are estimated, allowing for adjusting the predefined synchronization times regardless of the initial conditions. Finally, numerical simulations are conducted to demonstrate the effectiveness of the main results.

Description: The evolution of the Antarctic Ice Sheet is of vital importance given the coastal and societal implications of ice loss, with a potential to raise sea level by up to 58 m if melted entirely. However, future ice-sheet trajectories remain highly uncertain. One of the main sources of uncertainty is related to nonlinear processes and feedbacks of the ice sheet with the Earth System on different timescales. Due to these feedbacks and the ice-sheet inertia, ice loss may already be triggered in the next decades and then unfolds delayed on multi-centennial to millennial timescales. This committed Antarctic sea-level contribution is not reflected in typical sea-level projections based on mass balance changes of Antarctica, which often cover decadal-to-centennial timescales. Here, using two ice-sheet models, we systematically assess the multi-millennial sea-level commitment from Antarctica in response to warming projected over the next centuries under low- and high-emission pathways. This allows bringing together the time horizon of stakeholder planning with the much longer response times of the Antarctic Ice Sheet. Our results show that warming levels representative of the lower-emission pathway SSP1-2.6 may already result in an Antarctic mass loss of up to 6 m sea-level equivalent on multi-millennial timescales. This committed mass loss is due to a strong grounding-line retreat in the Amundsen Sea Embayment as well as a potential drainage from the Ross Ice Shelf catchment and onset of ice loss in Wilkes subglacial basin. Beyond warming levels reached by the end of this century under the higher-emission trajectory SSP5-8.5, a collapse of the West Antarctic Ice Sheet is triggered in the entire ensemble of simulations from both ice-sheet models. Under enhanced warming, next to the marine parts, we also find a substantial decline in ice volume of regions grounded above sea level in East Antarctica. Over the next millennia, this gives rise to a sea-level increase of up to 40 m in our experiments, stressing the importance of including the committed Antarctic sea-level contribution in future projections.

Description: Detection of critical slowing down (CSD) is the dominant avenue for anticipating critical transitions from noisy time-series data. Most commonly, changes in variance and lag-1 autocorrelation [AC(1)] are used as CSD indicators. However, these indicators will only produce reliable results if the noise driving the system is white and stationary. In the more realistic case of time-correlated red noise, increasing (decreasing) the correlation of the noise will lead to spurious (masked) alarms for both variance and AC(1). Here, we propose two new methods that can discriminate true CSD from possible changes in the driving noise characteristics. We focus on estimating changes in the linear restoring rate based on Langevin-type dynamics driven by either white or red noise. We assess the capacity of our new estimators to anticipate critical transitions and show that they perform significantly better than other existing methods both for continuous-time and discrete-time models. In addition to conceptual models, we apply our methods to climate model simulations of the termination of the African Humid Period. The estimations rule out spurious signals stemming from nonstationary noise characteristics and reveal a destabilization of the African climate system as the dynamical mechanism underlying this archetype of abrupt climate change in the past.

Description: We show that many delay-based reservoir computers considered in the literature can be characterized by a universal master memory function (MMF). Once computed for two independent parameters, this function provides linear memory capacity for any delay-based single-variable reservoir with small inputs. Moreover, we propose an analytical description of the MMF that enables its efficient and fast computation. Our approach can be applied not only to single-variable delay-based reservoirs governed by known dynamical rules, such as the Mackey–Glass or Stuart–Landau-like systems, but also to reservoirs whose dynamical model is not available.

Description: Central Asia (CA) is among the world's most vulnerable regions to climate change. Increasing anthropogenic greenhouse gas concentrations (GHGs) are the primary forcing of the current and future climate system for the time scale of a century. By analysing observation datasets, we show that a warming of 1.2°C led to a decrease of 20% in snow-depth CA during the last 70 years, especially over the mountains. In recent decades, longer summer times and fewer icing days (more than 20 days·year−1) have exposed unprecedented shock to CA's climate system's components. Furthermore, we analyse 442 model simulations from Coupled Model Inter-comparison Project Phase 5 and 6 (CMIP5, CMIP6) and show that CMIP6 simulations are generally warmer and wetter than the CMIP5 ones in CA. For instance, under the highest emission scenarios (RCP8.5 and SSP5-8.5), CMIP6 projects a 6.1°C increase, while CMIP5 projects a 5.3°C increase, suggesting CMIP6 anticipates greater warming with high emissions. In contrast to CMIP6, the CMIP5 precipitation trends suggest a potential nonlinear relationship between increased greenhouse gas emissions and changes in precipitation, though the impact is much less pronounced than the temperature changes. Our analysis shows that CMIP6 models are more sensitive to temperature rise than CMIP5 ones. Both simulation sets' ensemble means capture well the observed warming trend. The imposed snow-melting leads to an increase in the run-off in the vicinity of glaciers. Such climatic shifts lead to more flooding events in CA. Given the projected warming range of 2–6°C in CA at the end of the century in various scenarios and models, such warming trends might be catastrophic in this region. The seasonal cycle of the temperature change indicates an extension of the glacier's melting period under future scenarios with fossil-fueled development. The models' uncertainty increases for the far-future time-slice, and warming larger than 4°C in CA is very likely among all the models and during all the seasons if no sustainable action is taken. This study also incorporates a detailed Köppen climate classification analysis, revealing significant shifts towards warmer climate categories in Central Asia, which may have profound implications for regional hydrological cycles and water resource management, particularly in the Amu Darya and Syr Darya river basins under warmer scenario by the end of the century. The Tundra and ice cap climate categories will lose more than 60% of their coverage at the end of the century compared to the historical period in the Amu Darya and Syr Darya river basins.

Description: Media inform the public, thereby influencing societal debates and political decisions. Despite climate change’s importance, drivers of media attention to climate change remain differently understood. Here we assess how different sociopolitical and extreme weather events affect climate change media coverage, both immediately and in the weeks following the event. To this end, we construct a data set of over 90,000 climate change articles published in nine major German newspapers over the past three decades and apply fixed effects panel regressions to control for confounders. We find that United Nations Climate Change Conferences affect coverage most strongly and most persistently. Climate protests incite climate coverage that extends well beyond the reporting on the event itself, whereas many articles on weather extremes do not mention climate change. The influence of all events has risen over time, increasing the media prominence of climate change.

Description: Understanding the ongoing investments in coal-fired power plants requires an analysis of the political economy. Here, we conduct a computational analysis of 212 interviews from 12 countries on the political economy of coal using topic modelling (TM). Our study highlights relevant topics by actor group and country. While most topics are similarly distributed across all actor groups, we find distinct clusters of countries in which similar topics play important roles. For example, in Indonesia and India, sustaining low electricity tariffs is brought forward as a reason to invest in coal, whereas in South Africa and Kenya the civil society is considered instrumental in the choice of coal or alternatives. To validate our findings, we compare them to outcomes of qualitative case studies and to papers grouping countries based on quantifiable factors. As this study is among the first to apply TM to interview data, we thereby highlight strengths and challenges for such application and the interpretability of results. We argue that topic models are effective supplements to qualitative case studies, particularly when analysing large amounts of text.

Description: Driven primarily by variations in the earth's axis wobble, tilt, and orbit eccentricity, our planet experienced massive glacial/interglacial reorganizations of climate and atmospheric CO2 concentrations during the Pleistocene (2.58 million years ago (Ma)–11.7 thousand years ago (ka)). Even after decades of research, the underlying climate response mechanisms to these astronomical forcings have not been fully understood. To further quantify the sensitivity of the earth system to orbital-scale forcings, we conducted an unprecedented quasi-continuous coupled general climate model simulation with the Community Earth System Model version 1.2 (CESM1.2, ∼3.75∘ horizontal resolution), which covers the climatic history of the past 3 million years (3 Myr). In addition to the astronomical insolation changes, CESM1.2 is forced by estimates of CO2 and ice-sheet topography which were obtained from a simulation previously conducted with the CLIMBER-2 earth system model of intermediate complexity. Our 3 Ma simulation consists of 42 transient interglacial/glacial simulation chunks, which were partly run in parallel to save computing time. The chunks were subsequently merged, accounting for spin-up and overlap effects to yield a quasi-continuous trajectory. The computer model data were compared against a plethora of paleo-proxy data and large-scale climate reconstructions. For the period from the Mid-Pleistocene Transition (MPT, ∼1 Ma) to the late Pleistocene we find good agreement between simulated and reconstructed temperatures in terms of phase and amplitude (−5.7 ∘C temperature difference between Last Glacial Maximum and Holocene). For the earlier part (3–1 Ma), differences in orbital-scale variability occur between model simulation and the reconstructions, indicating potential biases in the applied CO2 forcing. Our model-proxy data comparison also extends to the westerlies, which show unexpectedly large variance on precessional timescales, and hydroclimate variables in major monsoon regions. Eccentricity-modulated precessional variability is also responsible for the simulated changes in the amplitude and flavors of the El Niño–Southern Oscillation. We further identify two major modes of planetary energy transport, which played a crucial role in Pleistocene climate variability: the first obliquity and CO2-driven mode is linked to changes in the Equator-to-pole temperature gradient; the second mode regulates the interhemispheric heat imbalance in unison with the eccentricity-modulated precession cycle. During the MPT, a pronounced qualitative shift occurs in the second mode of planetary energy transport: the post-MPT eccentricity-paced variability synchronizes with the CO2 forced signal. This synchronized feature is coherent with changes in global atmospheric and ocean circulations, which might contribute to an intensification of glacial cycle feedbacks and amplitudes. Comparison of this paleo-simulation with greenhouse warming simulations reveals that for an RCP8.5 greenhouse gas emission scenario, the projected global mean surface temperature changes over the next 7 decades would be comparable to the late Pleistocene glacial-interglacial range; but the anthropogenic warming rate will exceed any previous ones by a factor of ∼100.

Description: Climate stabilization is crucial for restabilizing the Earth system but should not undermine biosphere integrity, a second pillar of Earth system functioning. This is of particular con- cern if it is to be achieved through biomass-based negative emission (NE) technologies that compete for land with food production and ecosystem protection. We assess the NE con- tribution of land- and calorie-neutral pyrogenic carbon capture and storage (LCN-PyCCS) facilitated by biochar-based fertilization, which sequesters carbon and reduces land demand by increasing crop yields. Applying the global biosphere model LPJmL with an enhanced representation of fast-growing species for PyCCS feedstock production, we calculated a land-neutral global NE potential of 0.20–1.10 GtCO2 year−1 assuming 74% of the biochar carbon remaining in the soil after 100 years (for + 10% yield increase; no potential for + 5%; 0.61–1.88 GtCO 2 year−1 for + 15%). The potential is primarily driven by the achiev- able yield increase and the management intensity of the biomass producing systems. NE production is estimated to be enhanced by + 200–270% if management intensity increases from a marginal to a moderate level. Furthermore, our results show sensitivity to process- specific biochar yields and carbon contents, producing a difference of + 40–75% between conservative assumptions and an optimized setting. Despite these challenges for making world-wide assumptions on LCN-PyCCS systems in modeling, our findings point to dis- crepancies between the large NE volumes calculated in demand-driven and economically optimized mitigation scenarios and the potentials from analyses focusing on supply-driven approaches that meet environmental and socioeconomic preconditions as delivered by LCN-PyCCS.

Description: China has made substantial investment in agricultural research and development (R&D) to promote technological change (TC). Although the role of TC in enhancing agricultural production and mitigating environmental impacts is widely recognized in separate contexts, knowledge about its’ effects on food security and the environment, especially with a focus on China, is still lacking. This study uses an agro-economic optimization model to assess the impact of TC on food security and climate change mitigation. Our results indicate that TC plays an important role in improving agricultural productivity, which, in turn, contributes to a comparative advantage in agricultural trade. It also strengthens food security through lowering food prices. By contrast, a higher TC level increases greenhouse gas (GHG) emissions, albeit marginally, due to higher agricultural production for exports. This indicates a rebound effect of agricultural productivity on GHG emissions. Therefore, additional efforts are required in China to improve food security without compromising GHG mitigation.

Description: Quantitative climate mobility research has, so far, focused primarily on climate change impacts on migration outcomes. This focus has led to a separation between quantitative climate migration research and the broader field of migration studies. In this paper ways are proposed for quantitative research to better address the complexity in the relationship between climate change and mobility. First technical suggestions are presented to improve upon migration model setups and designs and highlight promising developments. Then it is argued that quantitative methodologies can broaden the scope of research inquiries by examining how climate mitigation and adaptation efforts influence mobility, as well as assessing how mobility itself impacts vulnerability.

Description: This paper aims to improve the Soil and Water Assessment Tool (SWAT) model performance across the Major River Basins in Madagascar (MRBM), specifically for SWAT simulation in the Manambolo, Onilahy, Mananara, and Mandrare basins. A multi-gauge calibration was carried out to compare the performance of SWAT+ Toolbox, and R-SWAT, SWAT+ Editor Hard calibration on a monthly time step for the periods 1982–1999. We found that the SWAT+ model generated greater surface runoff, while the SWAT model resulted in higher groundwater flow in both CSFR and CHIRPS datasets. It has been demonstrated that the SWAT+ Toolbox had more potential in calibrating runoff across the MRBM compared to R-SWAT. Calibration in both methods led to a reduction in surface runoff, percolation, water yield, and curve number but increased the lateral flow, evapotranspiration (ET), and groundwater flow. The results showed that the multi-gauge calibrations did not significantly enhance simulation performance in the MRBM compared to single-site calibration. The performance of the SWAT+ model for runoff simulation within the SWAT+ Toolbox and R-SWAT was unsatisfactory for most basins (NSE 〈 0) except for Betsiboka, Mahavavy, Tsiribihina, Mangoro, and Mangoky basins (NSE = 0.40–0.70; R2 = 0.45–0.80, PBIAS≤ ±25), whether considering the CHIRPS or CSFR datasets. Further study is still required to address this issue.

Description: Urban heat island (UHI) not only reflects the environmental thermal comfort and energy consumption, but also affects the urban meso‑scale climate. There are many researches related with UHI mainly focusing on urban and rural area, while neglecting dynamic rural–urban transition especially in a rapid urbanization in China. Beijing and Zhengzhou are studied by using city clustering algorithm (CCA) and boundary generation algorithm (BGA) to delineate the urban, peri‑urban and rural boundaries from 2000 to 2023 within three stages. Fourier transform model was used to identify the UHI patterns. Results show: 1) Two cities have undergone obvious expansions in 20 years, with a consistent mean LST decrease from urban to peri‑urban and rural areas in three stages. 2) The distribution of UHII was more consistent in Beijing, while it varied more in Zhengzhou across seasons. 3) The UHI patterns notably differ, with Zhengzhou experiencing variable patterns and Beijing consistently showing oblate patterns. 4) The profiles of UHII and NDVI in two cities varied seasonally and reflected urban expansions in terms of longitude and latitude. Understanding the long-term changes and patterns of urban heat islands in different cities will provide information for formulating adaptive policies for urban sustainability.

Description: Transportation and mobility patterns contribute to greenhouse gas emissions. Understanding the drivers of these emissions, particularly for high emitters, is key to designing appropriate climate and mobility policies. In this article, we study the distribution of emissions from mobility in Germany and their drivers. We use a 2017 nation-wide mobility survey to calculate the carbon footprint of individuals associated with day-to-day and long-distance travels. We use quantile regression to investigate both socio-economic and attitudinal drivers of emissions across different categories of emitters, and for different mobility types. We discuss our results with respect to previous findings in the literature. Overall, we find that the top 10% of emitters are responsible for 51% of total emissions, and for 80% of emissions from long-distance travel. The statistical analysis reveals strong differences regarding the contribution of socio-economic drivers such as income or location at different levels of emissions. Attitudes towards different transportation modes also strongly correlate with differences in mobility behaviors.

Description: Climate change heavily threatens forest ecosystems worldwide and there is urgent need to understand what controls tree survival and forests stability. There is evidence that biodiversity can enhance ecosystem stability (Loreau and de Mazancourt in Ecol Lett 16:106–115, 2013; McCann in Nature 405:228–233, 2000), however it remains largely unclear whether this also holds for climate change and what aspects of biodiversity might be most important. Here we apply machine learning to outputs of a flexible-trait Dynamic Global Vegetation Model to unravel the effects of enhanced functional tree trait diversity and its sub-components on climate-change resistance of temperate forests (http://www.pik-potsdam.de/~billing/video/Forest_Resistance_LPJmLFIT.mp4). We find that functional tree trait diversity enhances forest resistance. We explain this with 1. stronger complementarity effects (~ 25% importance) especially improving the survival of trees in the understorey of up to + 16.8% (± 1.6%) and 2. environmental and competitive filtering of trees better adapted to future climate (40–87% importance). We conclude that forests containing functionally diverse trees better resist and adapt to future conditions. In this context, we especially highlight the role of functionally diverse understorey trees as they provide the fundament for better survival of young trees and filtering of resistant tree individuals in the future.

Description: Background: Inherited blood disorders affect 7% of the population worldwide, with higher prevalences in countries in the “thalassemia belt,” which includes Bangladesh. Clinical management options for severely affected individuals are expensive; thus, targeted government policies are needed to support prevention and treatment programs. In Bangladesh, there is a lack of data, in particular community-based estimates, to determine population prevalence. This study aims to estimate the prevalence of a wide range of hemoglobinopathies and their associations with anemia in a community-based sample of women and young children in rural Sylhet, Bangladesh. - Methods: Capillary blood samples from 900 reproductive-aged women and 395 children (aged 6–37 months) participating in the Food and Agricultural Approaches to Reducing Malnutrition (FAARM) trial in two sub-districts of Habiganj, Sylhet Division, Bangladesh were analyzed for alpha thalassemia, beta thalassemia, and other hemoglobinopathies. We examined the association of each inherited blood disorder with hemoglobin concentration and anemia using linear and logistic regression. - Results: We identified at least one inherited blood disorder in 11% of women and 10% of children. Alpha thalassemia was most prevalent, identified in 7% of women and 5% of children, followed by beta thalassemia and hemoglobin E in 2–3%. We also identified cases of hemoglobin S and hemoglobin D in this population. Having any of the identified inherited blood disorders was associated with lower hemoglobin values among non-pregnant women, largely driven by alpha and beta thalassemia. Pregnant women with beta thalassemia were also more likely to have lower hemoglobin concentrations. Among children, we found weak evidence for a relationship between hemoglobinopathy and lower hemoglobin concentrations. - Conclusions: We found a high prevalence of alpha thalassemia among both women and children in rural Sylhet, Bangladesh–higher than all other identified hemoglobinopathies combined. Community-based estimates of alpha thalassemia prevalence in Bangladesh are scarce, yet our findings suggest that alpha thalassemia may comprise the majority of inherited blood disorders in some regions of the country. We recommend that future research on inherited blood disorders in Bangladesh include estimates of alpha thalassemia in their reporting for public health awareness and to facilitate couples counseling.

Description: Oil palm cultivation has become one of the world's most important drivers of land use change in the tropics causing biodiversity loss and greenhouse gas emissions. The impact of climate change and rising carbon dioxide (CO2) concentrations in the atmosphere on oil palm productivity is not well understood. If environmental change leads to declining palm oil yields in existing cultivation areas, cultivation areas may expand or shift to other regions. Here we assess climate change impacts on palm oil production using an extended version of the dynamic global vegetation model with managed land, LPJmL4, and a range of climate scenarios from the inter-sectoral impact model intercomparison project. We find increasing average yields under all future climate scenarios. This contradicts earlier studies, which did not consider the potential positive effect of CO2 fertilization. If we do not account for CO2 fertilization, future yields also decrease in our simulations. Our results indicate the potentially large role of rising CO2 levels on oil palm cultivation. This highlights the importance of further applied plant science to better understand the impact of climate change and elevated CO2 levels on oil palm growth and productivity.

Description: Many physical, biological, and social systems exhibit emergent properties arising from their components’ interactions (cells). In this study, we systematically treat every-pair interactions (a) that exhibit power-law dependence on the Euclidean distance and (b) act in structures that can be characterized using fractal geometry. It can represent the two-body interaction potential, the heat flux between two parts of a structure, friendship strength between two people, etc.. We analytically derive the average intensity of influence that one cell has on the others or, conversely, receives from them. This quantity is referred to as the mean interaction field of the cells, and we find that (i) in a long-range interaction regime, the mean interaction field increases following a power-law with the size of the system, (ii) in a short-range interaction regime, the field saturates, and (iii) in the intermediate range it follows a logarithmic behavior. To validate our analytical solution, we perform numerical simulations. For long-range interactions, the theoretical calculations align closely with the numerical results. However, for short-range interactions, we observe that discreteness significantly impacts the continuum approximation used in the derivation, leading to incorrect asymptotic behavior in this regime. To address this issue, we propose an expansion that substantially improves the accuracy of the analytical expression. We discuss applications of the every-pair interactions system proposed, and one of them is to explore a framework for estimating the fractal dimension of unknown structures. This approach offers an alternative to established methods such as box-counting or sandbox methods. Overall, we believe that our analytical work will have broad applicability in systems where every-pair interactions play a role.

Description: Adaptive management of crop growing periods by adjusting sowing dates and cultivars is one of the central aspects of crop production systems, tightly connected to local climate. However, it is so far underrepresented in crop-model based assessments of yields under climate change. In this study, we integrate models of farmers’ decision making with biophysical crop modeling at the global scale to simulate crop calendars adaptation and its effect on crop yields of maize, rice, sorghum, soybean and wheat. We simulate crop growing periods and yields (1986-2099) under counterfactual management scenarios assuming no adaptation, timely adaptation or delayed adaptation of sowing dates and cultivars. We then compare the counterfactual growing periods and corresponding yields at the end of the century (2080-2099). We find that (i) with adaptation, temperature-driven sowing dates (typical at latitudes 〉30°N-S) will have larger shifts than precipitation-driven sowing dates (at latitudes 〈30°N-S); (ii) later-maturing cultivars will be needed, particularly at higher latitudes; (iii) timely adaptation of growing periods would increase actual crop yields by ~12%, reducing climate change negative impacts and enhancing the positive CO2 fertilization effect. Despite remaining uncertainties, crop growing periods adaptation require consideration in climate change impact assessments.

Description: Mountain glaciers are sensitive recorders of natural and human-induced climate change. Therefore, it is imperative to obtain a comprehensive understanding of the interplay between climate and glacier response on both short and long timescales. Here we present an analysis of oxygen and carbon isotope data from speleothems formed mainly below a glacier-covered catchment in the Alps 300,000 to 200,000 years ago. Isotope-enabled climate model simulations reveal that δ18O of precipitation in the Alps was higher by approximately 1 ‰ during interstadials compared to stadials. This agrees with interstadial-stadial amplitudes of our new speleothem-based estimate after correcting for cave-internal effects. We propose that the variability of these cave-internal effects offers a unique tool for reconstructing long-term dynamics of warm-based Alpine palaeoglaciers. Our data thereby suggests a close link between North Atlantic interstadial-stadial variability and the meltwater dynamics of Alpine glaciers during Marine Isotope Stage 8 and 7d.

Description: The instability with respect to global glaciation is a fundamental property of the climate system caused by the positive ice-albedo feedback. The atmospheric concentration of carbon dioxide (CO2) at which this Snowball bifurcation occurs changes through Earth's history, most notably because of the slowly increasing solar luminosity. Quantifying this critical CO2 concentration is not only interesting from a climate dynamics perspective but also constitutes an important prerequisite for understanding past Snowball Earth episodes, as well as the conditions for habitability on Earth and other planets. Earlier studies are limited to investigations with very simple climate models for Earth's entire history or studies of individual time slices carried out with a variety of more complex models and for different boundary conditions, making comparisons and the identification of secular changes difficult. Here, we use a coupled climate model of intermediate complexity to trace the Snowball bifurcation of an aquaplanet through Earth's history in one consistent model framework. We find that the critical CO2 concentration decreased more or less logarithmically with increasing solar luminosity until about 1 billion years ago but dropped faster in more recent times. Furthermore, there was a fundamental shift in the dynamics of the critical state about 1.2 billion years ago (unrelated to the downturn in critical CO2 values), driven by the interplay of wind-driven sea-ice dynamics and the surface energy balance: for critical states at low solar luminosities, the ice line lies in the Ferrel cell, stabilised by the poleward winds despite moderate meridional temperature gradients under strong greenhouse warming. For critical states at high solar luminosities, on the other hand, the ice line rests at the Hadley cell boundary, stabilised against the equatorward winds by steep meridional temperature gradients resulting from the increased solar energy input at lower latitudes and stronger Ekman transport in the ocean.

Description: To represent the impact of grazing livestock on carbon (C) and nitrogen (N) dynamics in grasslands, we implement a livestock module into LPJmL5.0-tillage, a global vegetation and crop model with explicit representation of managed grasslands and pastures, forming LPJmL5.0-grazing. The livestock module uses lactating dairy cows as a generic representation of grazing livestock. The new module explicitly accounts for forage quality in terms of dry-matter intake and digestibility using relationships derived from compositional analyses for different forages. Partitioning of N into milk, feces, and urine as simulated by the new livestock module shows very good agreement with observation-based relationships reported in the literature. Modelled C and N dynamics depend on forage quality (C:N ratios in grazed biomass), forage quantity, livestock densities, manure or fertilizer inputs, soil, atmospheric CO2 concentrations, and climate conditions. Due to the many interacting relationships, C sequestration, GHG emissions, N losses, and livestock productivity show substantial variation in space and across livestock densities. The improved LPJmL5.0-grazing model can now assess the effects of livestock grazing on C and N stocks and fluxes in grasslands. It can also provide insights about the spatio-temporal variability of grassland productivity and about the trade-offs between livestock production and environmental impacts.

Description: Temperature targets of the Paris Agreement limit global net cumulative emissions to very tight carbon budgets. The possibility to overshoot the budget and offset near-term excess emissions by net-negative emissions is considered economically attractive as it eases near-term mitigation pressure. While potential side effects of carbon removal deployment are discussed extensively, the additional climate risks and the impacts and damages have attracted less attention. We link six models for an integrative analysis of the climatic, environmental and socio-economic consequences of temporarily overshooting a carbon budget consistent with the 1.5 °C temperature target along the cause-effect chain from emissions and carbon removals to climate risks and impact. Global climatic indicators such as CO2-concentration and mean temperature closely follow the carbon budget overshoot with mid-century peaks of 50 ppmv and 0.35 °C, respectively. Our findings highlight that investigating overshoot scenarios requires temporally and spatially differentiated analysis of climate, environmental and socioeconomic systems. We find persistent and spatially heterogeneous differences in the distribution of carbon across various pools, ocean heat content, sea-level rise as well as economic damages. Moreover, we find that key impacts, including degradation of marine ecosystem, heat wave exposure and economic damages, are more severe in equatorial areas than in higher latitudes, although absolute temperature changes being stronger in higher latitudes. The detrimental effects of a 1.5 °C warming and the additional effects due to overshoots are strongest in non-OECD countries (Organization for Economic Cooperation and Development). Constraining the overshoot inflates CO2 prices, thus shifting carbon removal towards early afforestation while reducing the total cumulative deployment only slightly, while mitigation costs increase sharply in developing countries. Thus, scenarios with carbon budget overshoots can reverse global mean temperature increase but imply more persistent and geographically heterogeneous impacts. Overall, the decision about overshooting implies more severe trade-offs between mitigation and impacts in developing countries.

Description: Over the past decade, Greenland has experienced several extreme melt events, the most pronounced ones in the years 2010, 2012 and 2019. With progressing climate change, such extreme melt events can be expected to occur more frequently and potentially become more severe and persistent. So far, however, projections of ice loss and sea level change from Greenland typically rely on scenarios which only take gradual changes in the climate into account. Using the Parallel Ice Sheet Model (PISM), we investigate the effect of extreme melt events on the overall mass balance of the Greenland Ice Sheet and the changes in ice flow, invoked by the altered surface topography. As a first constraint, this study estimates the overall effect of extreme melt events on the cumulative mass loss of the Greenland Ice Sheet. We find that the sea level contribution from Greenland might increase by 2 to 45 cm (0.2 % to 14 %) by the year 2300 if extreme events occur more frequently in the future under a Representative Concentration Pathway 8.5 (RCP8.5) scenario, and the ice sheet area might be reduced by an additional 6000 to 26 000 km2 by 2300 in comparison to future warming scenarios without extremes. In conclusion, projecting the future sea level contribution from the Greenland Ice Sheet requires consideration of the changes in both the frequency and intensity of extreme events. It is crucial to individually address these extremes at a monthly resolution as temperature forcing with the same excess temperature but evenly distributed over longer timescales (e.g., seasonal) leads to less sea level rise than for the simulations of the resolved extremes. Extremes lead to additional mass loss and thinning. This, in turn, reduces the driving stress and surface velocities, ultimately dampening the ice loss attributed to ice flow and discharge. Overall, we find that the surface elevation feedback largely amplifies melting for scenarios with and without extremes, with additional mass loss attributed to this feedback having the greatest impact on projected sea level.

Description: The timescales of the flow and retreat of Greenland’s and Antarctica’s outlet glaciers and their potential instabilities are arguably the largest uncertainty in future sea-level projections. Here we derive a scaling relation that allows the comparison of the timescales of observed complex ice flow fields with geometric similarity. The scaling relation is derived under the assumption of fast, laterally confined, geometrically similar outlet-glacier flow over a slippery bed, i.e., with negligible basal friction. According to the relation, the time scaling of the outlet flow is determined by the product of the inverse of 1) the fourth power of the width-to-length ratio of its confinement, 2) the third power of the confinement depth and 3) the temperature- dependent ice softness. For the outflow at the grounding line of streams with negligible basal friction this means that the volume flux is proportional to the ice softness and the bed depth, but goes with the fourth power of the gradient of the bed and with the fifth power of the width of the stream. We show that the theoretically derived scaling relation is supported by the observed velocity scaling of outlet glaciers across Greenland as well as by idealized numerical simulations of marine ice-sheet instabilities (MISIs) as found in Antarctica. Assuming that changes in the ice-flow velocity due to ice-dynamic imbalance are proportional to the equilibrium velocity, we combine the scaling relation with a statistical analysis of the topography of 13 MISI-prone Antarctic outlets. Under these assumptions the timescales in response to a potential destabilization are fastest for Thwaites Glacier in West Antarctica and Mellor, Ninnis and Cook Glaciers in East Antarctica; between 16 and 67 times faster than for Pine Island Glacier. While the applicability of our results is limited by several strong assumptions, the utilization and potential further development of the presented scaling approach may help to constrain time-scale estimates of outlet glacier- flow, augmenting the commonly exploited and comparatively computationally expensive approach of numerical modeling.

Description: We present a new open source dataset FLODIS that links estimates of flood-induced human displacements, fatalities, and economic damages to flooded areas observed through remote sensing. The dataset connects displacement data from the Internal Displacement Monitoring Centre (IDMC), as well as data on fatalities and damages from the Emergency Events Database (EM-DAT), with the Global Flood Database (GFD), a satellite-based inventory of historic flood footprints. It thereby provides a spatially explicit estimate of the flood hazard underlying each individual disaster event. FLODIS contains two datasets with event-specific information for 335 human displacement events and 695 mortality/damage events that occurred around the world between 2000 and 2018. Additionally, we provide estimates of affected population, GDP, and critical infrastructure, as well as socio-economic indicators; and we provide geocoding for displacement events ascribed to other types of disasters, such as tropical cyclones, so that they may be linked to corresponding hazard estimates in future work. FLODIS facilitates integrated flood risk analysis, allowing, for example, for detailed assessments of local flood-damage and displacement vulnerability.

Description: Many phenomena of high relevance for economic development such as human capital, geography and climate vary considerably within countries as well as between them. Yet, global data sets of economic output are typically available at the national level only, thereby limiting the accuracy and precision of insights gained through empirical analyses. Recent work has used interpolation and downscaling to yield estimates of sub-national economic output at a global scale, but respective data sets based on official, reported values only are lacking. We here present DOSE — the MCC-PIK Database Of Sub-national Economic Output. DOSE contains harmonised data on reported economic output from 1,661 sub-national regions across 83 countries from 1960 to 2020. To avoid interpolation, values are assembled from numerous statistical agencies, yearbooks and the literature and harmonised for both aggregate and sectoral output. Moreover, we provide temporally- and spatially-consistent data for regional boundaries, enabling matching with geo-spatial data such as climate observations. DOSE provides the opportunity for detailed analyses of economic development at the subnational level, consistent with reported values.

Description: The summer of 2018 was an extraordinary season in climatological terms for northern and central Europe, bringing simultaneous, widespread, and concurrent heat and drought extremes in large parts of the continent with extensive impacts on agriculture, forests, water supply, and socio-economic sector. Here, we present a comprehensive, multi-faceted analysis of the 2018 extreme summer in terms of heat and drought in central and northern Europe, with a particular focus on Germany. The heatwave first affected Scandinavia by mid-July, shifted towards central Europe in late July, while Iberia was primarily affected in early August. The atmospheric circulation was characterized by strongly positive blocking anomalies over Europe, in combination with a positive summer North Atlantic Oscillation and a double jet stream configuration before the initiation of the heatwave. In terms of possible precursors common to previous European heatwaves, the Eurasian double jet structure and a tripolar sea-surface temperature anomaly over the North Atlantic were identified already in spring. While in the early stages over Scandinavia the air masses at mid- and upper-levels were often of remote, maritime origin, at later stages over Iberia the air masses had primarily a local-to-regional origin. The drought affected Germany the most, starting with warmer than average conditions in spring, associated with enhanced latent heat release that initiated a severe depletion of soil moisture. During summer, a continued precipitation deficit exacerbated the problem, leading to hydrological and agricultural drought. A probabilistic attribution assessment of the heatwave in Germany showed that such events of prolonged heat have become more likely due to anthropogenic global warming. Regarding future projections, an extreme summer such as this of 2018 is expected to occur every two out of three years in Europe under a 1.5 °C warmer world and virtually every single year under 2 °C of global warming. With such large-scale and impactful extreme events becoming more frequent and intense under anthropogenic climate change, comprehensive and multi-faceted studies like the one presented here quantify the multitude of effects and provide valuable information as basis for adaptation and mitigation strategies.

Description: Background: Heat exposure, which can negatively affect human health and wellbeing, is heterogeneous within US cities. However, little is known about who can avoid heat stress by adjusting their everyday behaviour. We aimed to analyse the effect of ambient temperature on mobility, specifically subway (ie, the underground railway system) use, in New York City, NY, USA, during 2014–19. - Methods: For this empirical study, subway use across New York City was measured with turnstile data from the New York City Metropolitan Transportation Authority between Jan 1, 2014, and Dec 31, 2019. Passenger numbers were then aggregated to the zip code tabulation area (ZCTA) level. Daily observational climate data were obtained from the US National Weather Service between Jan 1, 2014, and Dec 31, 2019. Socioeconomic data at the ZCTA level originated from the American Community Survey 2019. We extracted data on population age, ethnicity, commuting, employment, median household income, rent, and health-insurance coverage. We used a fixed-effects panel-regression model to assess the influence of temperature on subway use in New York City, which was the main outcome of our study. - Findings: We obtained data for 438 subway stations across New York City. After data cleaning and preprocessing, the final aggregated data sample consisted of 238 508 instances of subway use in 1955 days across 6 years for 122 ZCTAs, with 168 days missing in the raw data and 67 days removed as outliers. The results of the fixed-effects panel-regression analysis showed a strong, non-linear effect of daily maximum temperature on subway use. Subway use was highest at 11·5°C and substantially decreased for temperatures that were colder and warmer than that, with reductions reaching 6·5% (95% CI 2·5–10·5) for the coldest temperature (ie, –6·5°C) and 10·5% (6·0–14·0) for the hottest temperature (ie, 34·5°C). Reductions differed between weekdays and weekends, when residents generally had more freedom to adjust their behaviour. Neighbourhoods that were at a socioeconomic disadvantage experienced smaller or no reductions in mobility in heat; mobility increased in neighbourhoods with beach access. - Interpretation: Our study showed that temperature had a strong, non-linear effect on subway use, but the magnitude of the effect on subway use was heterogeneous across areas of the city on warm days. Weaker avoidance of heat stress correlated with less privilege, indicating compounding health risks. Everyday behavioural adaptation to heat is therefore an effect pathway that contributes to unequal heat effects and should be explored in future research.

Description: Vine phenology modelling is increasingly important for winegrowers and viticulturists. Model calibration is often required before practical applications. However, when multiple models and optimization methods are applied for different varieties, it is rarely known which factor tends to mostly affect the calibration results. We mainly aim to investigate the main source of the variability in the modelling errors for the flowering timings of two important varieties of vine in the Douro Demarcated Region (DDR) of Portugal; this is based on five phenology model simulations that use optimal parameters and that are estimated by three optimization algorithms (MLE, SA and SCE-UA). Our results indicate that the main source of the variability in calibration can be affected by the initially assumed parameter boundary. Restricting the initial parameter distribution to a narrow range impedes the algorithm from exploring the full parameter space and searching for optimal parameters. This can lead to the largest variation in different models. At an identified appropriate boundary, the difference between the two varieties represents the largest source of uncertainty, while the choice of algorithm for calibration contributes least to the overall uncertainty. The smaller variability among different models or algorithms (tools for analysis) compared to between different varieties could indicate the overall reliability of the calibration. All optimization algorithms show similar results in terms of the obtained goodness-of-fit: the RMSE (MAE) is 5–6 (4–5) days with a negligible mean bias and moderately good R2 (0.5–0.6) for the ensemble median predictor. Nevertheless, a similar predictive performance can result from differently estimated parameter values, due to the equifinality or multi-modal issue in which different parameter combinations give similar results. This mainly occurs for models with a non-linear structure compared to those with a near-linear one. Yet, the former models are found to outperform the latter ones in predicting the flowering timing of the two varieties in the DDR. Overall, our findings highlight the importance of carefully defining the initial parameter boundary and decomposing the total variance of prediction errors. This study is expected to bring new insights that will help to better inform users about the importance of choice when these factors are involved in calibration. Nonetheless, the importance of each factor can change depending on the specific situation. Details of how the optimization methods are applied and of the continuous model improvement are important.

Description: Data on women’s living conditions and socio-economic development are important for understanding and addressing the pronounced challenges and inequalities faced by women worldwide. While such information is increasingly available at the national level, comparable data at the sub-national level are missing. We here present the LivWell global longitudinal dataset, which includes a set of key indicators on women’s socio-economic status, health and well-being, access to basic services and demographic outcomes. It covers 447 regions in 52 countries and includes a total of 265 different indicators. The majority of these are based on 199 Demographic and Health Surveys (DHS) for the period 1990–2019 and are complemented by extensive information on socio-economic and climatic conditions in the respective regions. The resulting dataset offers various opportunities for policy-relevant research on gender inequality, inclusive development and demographic trends at the sub-national level.

Description: Classic Maya populations living in peri-urban states were highly dependent on seasonally distributed rainfall for reliable surplus crop yields. Despite intense study of the potential impact of decadal to centennial-scale climatic changes on the demise of Classic Maya sociopolitical institutions (750-950 CE), its direct importance remains debated. We provide a detailed analysis of a precisely dated speleothem record from Yok Balum cave, Belize, that reflects local hydroclimatic changes at seasonal scale over the past 1600 years. We find that the initial disintegration of Maya sociopolitical institutions and population decline occurred in the context of a pronounced decrease in the predictability of seasonal rainfall and severe drought between 700 and 800 CE. The failure of Classic Maya societies to successfully adapt to volatile seasonal rainfall dynamics likely contributed to gradual but widespread processes of sociopolitical disintegration. We propose that the complex abandonment of Classic Maya population centres was not solely driven by protracted drought but also aggravated by year-to-year decreases in rainfall predictability, potentially caused by a regional reduction in coherent Intertropical Convergence Zone-driven rainfall.

Description: We present the Land Input Generator (LandInG) version 1.0, a new toolbox for generating input datasets for terrestrial ecosystem models (TEMs) from diverse and partially conflicting data sources. While LandInG 1.0 is applicable to process data for any TEM, it is developed specifically for the open-source dynamic global vegetation, hydrology, and crop growth model LPJmL (Lund–Potsdam–Jena with managed Land). The toolbox documents the sources and processing of data to model inputs and allows for easy changes to the spatial resolution. It is designed to make inconsistencies between different sources of data transparent so that users can make their own decisions on how to resolve these should they not be content with the default assumptions made here. As an example, we use the toolbox to create input datasets at 5 and 30 arcmin spatial resolution covering land, country, and region masks, soil, river networks, freshwater reservoirs, irrigation water distribution networks, crop-specific annual land use, fertilizer, and manure application. We focus on the toolbox describing the data processing rather than only publishing the datasets as users may want to make different choices for reconciling inconsistencies, aggregation, spatial extent, or similar. Also, new data sources or new versions of existing data become available continuously, and the toolbox approach allows for incorporating new data to stay up to date.

Description: Process-based forest models combine biological, physical, and chemical process understanding to simulate forest dynamics as an emergent property of the system. As such, they are valuable tools to investigate the effects of climate change on forest ecosystems. Specifically, they allow testing of hypotheses regarding long-term ecosystem dynamics and provide means to assess the impacts of climate scenarios on future forest development. As a consequence, numerous local-scale simulation studies have been conducted over the past decades to assess the impacts of climate change on forests. These studies apply the best available models tailored to local conditions, parameterized and evaluated by local experts. However, this treasure trove of knowledge on climate change responses remains underexplored to date, as a consistent and harmonized dataset of local model simulations is missing. Here, our objectives were (i) to compile existing local simulations on forest development under climate change in Europe in a common database, (ii) to harmonize them to a common suite of output variables, and (iii) to provide a standardized vector of auxiliary environmental variables for each simulated location to aid subsequent investigations. Our dataset of European stand- and landscape-level forest simulations contains over 1.1 million simulation runs representing 135 million simulation years for more than 13,000 unique locations spread across Europe. The data were harmonized to consistently describe forest development in terms of stand structure (dominant height), composition (dominant species, admixed species), and functioning (leaf area index). Auxiliary variables provided include consistent daily climate information (temperature, precipitation, radiation, vapor pressure deficit) as well as information on local site conditions (soil depth, soil physical properties, soil water holding capacity, plant-available nitrogen). The present dataset facilitates analyses across models and locations, with the aim to better harness the valuable information contained in local simulations for large-scale policy support, and for fostering a deeper understanding of the effects of climate change on forest ecosystems in Europe.

Description: The Texas power grid on the Gulf Coast of the United States is frequently hit by tropical cyclones (TCs) causing widespread power outages, a risk that is expected to substantially increase under global warming. Here we introduce a new approach that combines a probabilistic line failure model with a network model of the Texas grid to simulate the spatio-temporal co-evolution of wind-induced failures of high-voltage transmission lines and the resulting cascading power outages from seven major historical TCs. The approach allows reproducing observed supply failures. In addition, compared to existing static approaches, it provides a notable advantage in identifying critical lines whose failure can trigger large supply shortages. We show that hardening only 1% of total lines can reduce the likelihood of the most destructive type of outage by a factor of between 5 and 20. The proposed modelling approach could represent a so far missing tool for identifying effective options to strengthen power grids against future TC strikes, even under limited knowledge.

Description: The Greenland Ice Sheet and Atlantic Meridional Overturning Circulation are considered tipping elements in the climate system, where global warming exceeding critical threshold levels in forcing can lead to large-scale and nonlinear reductions in ice volume and overturning strength, respectively. The positive-negative feedback loop governing their interaction (with a destabilizing effect on the AMOC due to ice loss and subsequent freshwater flux into the North Atlantic as well as a stabilizing effect of a net-cooling around Greenland with an AMOC weakening) may determine the long-term stability of both tipping elements. Here we explore the potential dynamic regimes arising from this positive-negative tipping feedback loop in a process-based conceptual model. Under idealized forcing scenarios we identify conditions under which different kinds of tipping cascades can occur: Herein, we distinguish between overshoot tipping cascades (leading to tipping of both GIS and AMOC) and rate-induced tipping cascades (where the AMOC despite not having crossed its own intrinsic tipping point tips nonetheless due to the fast rate of ice loss from Greenland). These different cascades occur within corridors of distinct tipping pathways that are affected by the GIS melting patterns and thus eventually by the imposed forcing and its time scales. Our results suggest that it is not only necessary to avoid breaching the respective critical levels of the environmental drivers for the Greenland Ice Sheet and Atlantic Meridional Overturning Circulation, but also to respect safe rates of environmental change to mitigate potential domino effects.

Description: The recurrence plot and the recurrence quantification analysis (RQA) are well-established methods for the analysis of data from complex systems. They provide important insights into the nature of the dynamics, periodicity, regime changes, and many more. These methods are used in different fields of research, such as finance, engineering, life, and earth science. To use them, the data have usually to be uniformly sampled, posing difficulties in investigations that provide non-uniformly sampled data, as typical in medical data (e.g., heart-beat based measurements), paleoclimate archives (such as sediment cores or stalagmites), or astrophysics (supernova or pulsar observations). One frequently used solution is interpolation to generate uniform time series. However, this preprocessing step can introduce bias to the RQA measures, particularly those that rely on the diagonal or vertical line structure in the recurrence plot. Using prototypical model systems, we systematically analyze differences in the RQA measure average diagonal line length for data with different sampling and interpolation. For real data, we show that the course of this measure strongly depends on the choice of the sampling rate for interpolation. Furthermore, we suggest a correction scheme, which is capable of correcting the bias introduced by the prepossessing step if the interpolation ratio is an integer.

Description: We present a modular framework for generating synthetic power grids that consider the heterogeneity of real power grid dynamics but remain simple and tractable. This enables the generation of large sets of synthetic grids for a wide range of applications. For the first time, our synthetic model also includes the major drivers of fluctuations on short-time scales and a set of validators that ensure the resulting system dynamics are plausible. The synthetic grids generated are robust and show good synchronization under all evaluated scenarios, as should be expected for realistic power grids. A software package that includes an efficient Julia implementation of the framework is released as a companion to the paper.

Description: To mitigate climate change, the share of renewable energies in power production needs to be increased. Renewables introduce new challenges to power grids regarding the dynamic stability due to decentralization, reduced inertia, and volatility in production. Since dynamic stability simulations are intractable and exceedingly expensive for large grids, graph neural networks (GNNs) are a promising method to reduce the computational effort of analyzing the dynamic stability of power grids. As a testbed for GNN models, we generate new, large datasets of dynamic stability of synthetic power grids and provide them as an open-source resource to the research community. We find that GNNs are surprisingly effective at predicting the highly non-linear targets from topological information only. For the first time, performance that is suitable for practical use cases is achieved. Furthermore, we demonstrate the ability of these models to accurately identify particular vulnerable nodes in power grids, so-called troublemakers. Last, we find that GNNs trained on small grids generate accurate predictions on a large synthetic model of the Texan power grid, which illustrates the potential for real-world applications.

Description: Global projections of macroeconomic climate-change damages typically consider impacts from average annual and national temperatures over long time horizons. Here we use recent empirical findings from more than 1,600 regions worldwide over the past 40 years to project sub-national damages from temperature and precipitation, including daily variability and extremes. Using an empirical approach that provides a robust lower bound on the persistence of impacts on economic growth, we find that the world economy is committed to an income reduction of 19% within the next 26 years independent of future emission choices (relative to a baseline without climate impacts, likely range of 11–29% accounting for physical climate and empirical uncertainty). These damages already outweigh the mitigation costs required to limit global warming to 2 °C by sixfold over this near-term time frame and thereafter diverge strongly dependent on emission choices. Committed damages arise predominantly through changes in average temperature, but accounting for further climatic components raises estimates by approximately 50% and leads to stronger regional heterogeneity. Committed losses are projected for all regions except those at very high latitudes, at which reductions in temperature variability bring benefits. The largest losses are committed at lower latitudes in regions with lower cumulative historical emissions and lower present-day income.

Description: Are there group decision methods which (i) give everyone, including minorities, an equal share of effective decision power even when voters act strategically, (ii) promote consensus and equality, rather than polarization and inequality, and (iii) do not favour the status quo or rely too much on chance? We describe two non-deterministic group decision methods that meet these criteria, one based on automatic bargaining over lotteries, the other on conditional commitments to approve compromise options. Using theoretical analysis, agent-based simulations and a behavioral experiment, we show that these methods prevent majorities from consistently suppressing minorities, which can happen in deterministic methods, and keeps proponents of the status quo from blocking decisions, as in other consensus-based approaches. Our simulations show that these methods achieve aggregate welfare comparable to common voting methods, while employing chance judiciously, and that the welfare costs of fairness and consensus are small compared to the inequality costs of majoritarianism. In an incentivized experiment with naive participants, we find that a sizable fraction of participants prefers to use a non-deterministic voting method over Plurality Voting to allocate monetary resources. However, this depends critically on their position within the group. Those in the majority show a strong preference for majoritarian voting methods.

Description: This paper applies a mental model approach to study the role of tenure security in farmers’ decisionmaking on agricultural investment in Uganda. We investigate the role that both perceived tenure security and formal land rights, measured by the possession of land certificates, play. Our focus is on investment in improved seeds, a widely applied strategy in agricultural development and climate change adaptation. The study design leverages the roll-out of a large land demarcation and registration project, which creates exogenous variation in farmers’ tenure security. Results show that, in contrast to expectations derived from economic theory, tenure security plays only a minor role in farmers’ decision-making process to invest in improved seeds. Out of 15 potential factors determining a farmer’s investment decision, both perceived tenure security and possession of a land certificate are among the least chosen factors, regardless of whether or not households participated in the land registration project. A heterogeneity analysis reveals that female-headed households value formalized land rights more than male-headed households.

Description: In this paper we ask: why do people in rural agrarian communities facing increasing migration pressures from changing climatic conditions, stay? We aim to understand why people stay, who stays, what are the impacts of migration on those who stay, and what are their needs for adaptation? We study a population of people who do not migrate from Himalayan communities of Uttarakhand, India, despite their livelihoods being already severely disrupted by climate change climate change and high outmigration has led to abandoned so-called ‘ghost villages’. Semi-structured interviews (n = 72) were held with affected communities, experts, and policymakers. Results show that motivations for immobility are shaped by place attachment; place-based resource advantages; social milieu; dependence on subsistence agriculture and gender roles. We find that immobility experiences are differentiated by gender, age and in situ resources. Those who stay are negatively impacted by migration via loss of labour in agriculture, changes in population size and composition, loss of community, in addition to the negative impacts of climate change. Our results are likely relevant on a global scale, to other subsistence smallholder communities who stay despite increasing climate risks. These populations will need gender-sensitive support to adapt in place.

Description: The benefits of gardening for mental and physical health are well known. Gardening is also recognized as a local-level or grassroots response to the negative effects of climate change and global warming. In urban areas, dense neighborhoods, limited green spaces, contaminated brownfield sites, and, at times, restrictive council regulations on the public use of parks and verges can act as barriers to gardening. In the 1970s, guerrilla gardening emerged as a clandestine, environmentally conscious, grassroots activity to reclaim and transform neglected or derelict urban spaces into healthy green spaces. Although not as subversive since its inception, guerrilla gardening in cities is as much a recreational activity as it is an ecological statement of urban activism, which effectively provides urban dwellers an entry point to engage with the outdoors for the planting of edible and nonedible plants in artificial places and spaces where natural life struggles to exist. Guerilla gardening has been impactful to city life through its contributions and controversies in improving urban ecosystems, educating neighbors on nutrition and food production where gardens crop up, and broadly to the health of humans (and other creatures) who live there.

Description: To address climatic risks to human security, various climate security risk assessment (CSRA) tools have been developed. We have systematically reviewed 28 such tools against state-of-the-art research to (i) define best practices in CSRAs, (ii) identify related gaps in these tools and derive recommendations on how to address them, and (iii) outline a policy-relevant research agenda. We suggest the following measures to improve CSRA tools: Global South actors need to be more strongly involved in priority setting, conceptualization, risk analysis, and intervention design. CSRA tools should offer geographically disaggregated analyses, transparently explain choices regarding tools’ temporal and geographical foci, and assess their implications for the evidence. In this regard, any type of sampling bias should be avoided. Mixed methods can offer clear advantages to study the context-specific climate security dynamics across different time scales. The main gaps in the tools’ conceptualizations evolve around comprehensive consideration of risk determinants (climatic hazards, exposure, and vulnerability) and complex climate–security linkages, communication of uncertainty, and implementation of validation routines. These factors need to be better accounted for. To advance CSRAs, future research should, for example, develop methodologies to systematically integrate quantitative and qualitative approaches, improve the performance of risk predictions, and develop conflict projections.

Description: We analyze if exposure to weather risk affects the tenure security of smallholder farmers in rural Tanzania. Drawing on a household panel survey with three waves and high-resolution weather data, our identification strategy exploits exogenous variation in precipitation across time and space. Results from household fixed effects estimations show that exposure to weather risk significantly lowers farmers’ perceived tenure security, while it increases land conflicts. Moreover, weather risk influences the likelihood that farmers acquire land certificates. These findings suggest that both land formalization and land dispute resolution mechanisms are needed to cushion the impacts of weather risk.

Description: Forestation efforts are accelerating across the globe in the fight against global climate change, in order to restore biodiversity, and to improve local livelihoods. Yet, so far the non-local effects of forestation on rainfall have largely remained a blind spot. Here we build upon emerging work to propose that targeted rainfall enhancement may also be considered in the prioritization of forestation. We show that the tools to achieve this are rapidly becoming available, but we also identify drawbacks and discuss which further developments are still needed to realize robust assessments of the rainfall effects of forestation in the face of climate change. Forestation programs may then mitigate not only global climate change itself, but also its adverse effects in the form of drying.

Description: Extreme weather events are rising at a pace which exceeds expectations based on thermodynamic arguments only, changing the way we perceive our climate system and climate change issues. Every year, heatwaves, floods and wildfires, bring death and devastation worldwide, increasing the evidence about the role of anthropogenic climate change in the increase of extremes. In this viewpoint article, we summarize some of the most recent extremes and put them in the context of the most recent research on atmospheric and climate sciences, especially focusing on changes in thermodynamics and dynamics of the atmosphere. While some changes in extremes are to be expected and are clearly attributable to rising greenhouse gas emissions, other seem counterintuitive, highlighting the need for further research in the field. In this context, research on changes in atmospheric dynamics plays a crucial role in explaining some of these extremes and more needs to be done to improve our understanding of the physical mechanisms involved.

Description: The planetary boundaries framework defines a safe operating space for humanity. To date, these boundaries have mostly been investigated separately, and it is unclear whether breaching one boundary can lead to the transgression of another. By employing a dynamic global vegetation model, we systematically simulate the strength and direction of the effects of different transgression levels of the climate change boundary (using climate output from ten phase 6 of the Coupled Model Intercomparison Project models for CO2 levels ranging from 350 ppm to 1000 ppm). We focus on climate change-induced shifts of Earth's major forest biomes, the control variable for the land-system change boundary, both by the end of this century and, to account for the long-term legacy effect, by the end of the millennium. Our simulations show that while staying within the 350 ppm climate change boundary co-stabilizes the land-system change boundary, breaching it (〉450 ppm) leads to critical transgression of the latter, with greater severity the higher the ppm level rises and the more time passes. Specifically, this involves a poleward treeline shift, boreal forest dieback (nearly completely within its current area under extreme climate scenarios), competitive expansion of temperate forest into today's boreal zone, and a slight tropical forest extension. These interacting changes also affect other planetary boundaries (freshwater change and biosphere integrity) and provide feedback to the climate change boundary itself. Our quantitative process-based study highlights the need for interactions to be studied for a systemic operationalization of the planetary boundaries framework.

Description: Today, more than 70 carbon pricing schemes have been implemented around the globe, but their contributions to emissions reductions remains a subject of heated debate in science and policy. Here we assess the effectiveness of carbon pricing in reducing emissions using a rigorous, machine-learning assisted systematic review and meta-analysis. Based on 483 effect sizes extracted from 80 causal ex-post evaluations across 21 carbon pricing schemes, we find that introducing a carbon price has yielded immediate and substantial emission reductions for at least 17 of these policies, despite the low level of prices in most instances. Statistically significant emissions reductions range between –5% to –21% across the schemes (–4% to –15% after correcting for publication bias). Our study highlights critical evidence gaps with regard to dozens of unevaluated carbon pricing schemes and the price elasticity of emissions reductions. More rigorous synthesis of carbon pricing and other climate policies is required across a range of outcomes to advance our understanding of “what works” and accelerate learning on climate solutions in science and policy.

Description: There has long been a debate about climate-damaging subsidies in the German transport sector, and the financial restrictions resulting from the Federal Constitutional Court’s budget judgement at the end of 2023 have intensified the debate. This dossier is the first to convert the level of subsidies in the transport sector into negative CO2 prices to present a scientific categorisation of their significance for climate policy. The concept of implicit negative CO2 prices shows the extent to which subsidies implicitly reward citizens for emitting a tonne of CO2, rather than paying for the emissions.

Description: Interest rates are central determinants of saving and investment decisions. Costly financial intermediation distorts these price signals by creating a spread between deposit and loan rates. This study investigates how bank spreads affect climate policy in its ambition to redirect capital. We identify various channels through which interest spreads affect carbon emissions in a dynamic general equilibrium model. Interest rate spreads increase abatement costs due to the higher relative price for capital-intensive carbon-free energy but they also tend to reduce emissions due to lower overall economic growth. For the global average interest rate spread of 5.1pp, global warming increases by 0.2°C compared to the frictionless economy. For a given temperature target to be achieved, interest rate spreads necessitate substantially higher carbon taxes. When spreads arise from imperfect competition in the intermediation sector, the associated welfare costs can be reduced by clean energy subsidies or even eliminated by economy-wide investment subsidies.

Description: Understanding the future fate of the Greenland Ice Sheet (GIS) in the context of anthropogenic CO2 emissions is crucial to predict sea level rise. With the fully coupled Earth system model of intermediate complexity CLIMBER-X, we study the stability of the GIS and its transient response to CO2 emissions over the next 10 kyr. Bifurcation points exist at global temperature anomalies of 0.6 and 1.6 K relative to pre-industrial. For system states in the vicinity of the equilibrium ice volumes corresponding to these temperature anomalies, mass loss rate and sensitivity of mass loss to cumulative CO2 emission peak. These critical ice volumes are crossed for cumulative emissions of 1000 and 2500 GtC, which would cause long-term sea level rise by 1.8 and 6.9 m respectively. In summary, we find tipping of the GIS within the range of the temperature limits of the Paris agreement.

Description: By presenting a range of outcomes which result from the impacts of a changing environment on human mobility patterns, the Foresight Report on Migration and Global Environmental Change emphasized that, whereas some people choose to stay in a specific location, others are simply unable to leave, leading to what the report termed “trapped populations”. Much understanding about both voluntary and involuntary immobility in the context of environmental or climatic change has been gained since. The IPCC's recent report on climate change impacts, vulnerabilities and adaptation further underlined that, in the decades ahead, some people will be unable or unwilling to move away from locations in which they may nevertheless be vulnerable to the impacts of climate change. What has received less attention is how climate immobility ought to be governed and which norms should underpin its governance. In this paper, we rely on select existing law and policy instruments and frameworks from Latin American and the Pacific Islands regions to outline key considerations of a governance structure suitable for (in)voluntary immobility. This will inform individuals, communities, and policy makers who seek to navigate through complex reasons and decisions for “staying put” or “getting stuck” in the face of climatic change. The analysis builds upon a review of published literature and, especially, existing policy and legal frameworks at national and regional levels. We argue that a more widespread, timely and proactive approach to policy and governance is required in support of resilience in the context of climate immobility.

Description: Ice core records from Greenland provide evidence for multiple abrupt cold–warm–cold events recurring at millennial time scales during the last glacial interval. Although climate variations resembling Dansgaard–Oeschger (DO) oscillations have been identified in climate archives across the globe, our understanding of the climate and ecosystem impacts of the Greenland warming events in lower latitudes remains incomplete. Here, we investigate the influence of DO-cold-to-warm transitions on the global atmospheric circulation pattern. We comprehensively analyze δ18O changes during DO transitions in a globally distributed dataset of speleothems and set those in context with simulations of a comprehensive high-resolution climate model featuring internal millennial-scale variations of similar magnitude. Across the globe, speleothem δ18O signals and model results indicate consistent large-scale changes in precipitation amount, moisture source, or seasonality of precipitation associated with the DO transitions, in agreement with northward shifts of the Hadley circulation. Furthermore, we identify a decreasing trend in the amplitude of DO transitions with increasing distances from the North Atlantic region. This provides quantitative observational evidence for previous suggestions of the North Atlantic region being the focal point for these archetypes of past abrupt climate changes.

Description: Subventionen im Verkehr, wie das Diesel- oder Dienstwagenprivileg, bedeuten negative CO2-Preise in Höhe von minus 70 bis zu minus 690 Euro pro Tonne CO2 und schwächen die Wirkungsweise der CO2-Bepreisung als wichtiges Instrument der Klimapolitik. Das zeigen Forschende des vom Bundesministerium für Bildung und Forschung (BMBF) geförderten Kopernikus-Projekts Ariadne in einer neuen Studie. Die Ariadne-Berechnungen unterstreichen, dass Deutschlands derzeitiges Steuer- und Abgabesystem im Verkehrssektor noch stark auf die Nutzung fossiler Energieträger ausgerichtet ist und so die Erreichung der deutschen Klimaziele erschwert.

Description: The costs of climate change are often estimated in monetary terms, but this raises ethical issues. Here we express them in terms of numbers of people left outside the ‘human climate niche’—defined as the historically highly conserved distribution of relative human population density with respect to mean annual temperature. We show that climate change has already put ~9% of people (〉600 million) outside this niche. By end-of-century (2080–2100), current policies leading to around 2.7 °C global warming could leave one-third (22–39%) of people outside the niche. Reducing global warming from 2.7 to 1.5 °C results in a ~5-fold decrease in the population exposed to unprecedented heat (mean annual temperature ≥29 °C). The lifetime emissions of ~3.5 global average citizens today (or ~1.2 average US citizens) expose one future person to unprecedented heat by end-of-century. That person comes from a place where emissions today are around half of the global average. These results highlight the need for more decisive policy action to limit the human costs and inequities of climate change.

Description: We present transient simulations of the last glacial inception using the Earth system model CLIMBER-X with dynamic vegetation, interactive ice sheets, and visco-elastic solid Earth responses. The simulations are initialized at the middle of the Eemian interglacial (125 kiloyears before present, ka) and run until 100 ka, driven by prescribed changes in Earth's orbital parameters and greenhouse gas concentrations from ice core data. CLIMBER-X simulates a rapid increase in Northern Hemisphere ice sheet area through MIS5d, with ice sheets expanding over northern North America and Scandinavia, in broad agreement with proxy reconstructions. While most of the increase in ice sheet area occurs over a relatively short period between 119 and 117 ka, the larger part of the increase in ice volume occurs afterwards with an almost constant ice sheet extent. We show that the vegetation feedback plays a fundamental role in controlling the ice sheet expansion during the last glacial inception. In particular, with prescribed present-day vegetation the model simulates a global sea level drop of only ∼ 20 m, compared with the ∼ 35 m decrease in sea level with dynamic vegetation response. The ice sheet and carbon cycle feedbacks play only a minor role during the ice sheet expansion phase prior to ∼ 115 ka but are important in limiting the deglaciation during the following phase characterized by increasing summer insolation. The model results are sensitive to climate model biases and to the parameterization of snow albedo, while they show only a weak dependence on changes in the ice sheet model resolution and the acceleration factor used to speed up the climate component. Overall, our simulations confirm and refine previous results showing that climate–vegetation–cryosphere feedbacks play a fundamental role in the transition from interglacial to glacial states characterizing Quaternary glacial cycles.

Description: Human actions compromise the many life-supporting functions provided by the freshwater cycle. Yet, scientific understanding of anthropogenic freshwater change and its long-term evolution is limited. Here, using a multi-model ensemble of global hydrological models, we estimate how, over a 145-year industrial period (1861–2005), streamflow and soil moisture have deviated from pre-industrial baseline conditions (defined by 5th–95th percentiles, at 0.5° grid level and monthly timestep over 1661–1860). Comparing the two periods, we find an increased frequency of local deviations on ~45% of land area, mainly in regions under heavy direct or indirect human pressures. To estimate humanity’s aggregate impact on these two important elements of the freshwater cycle, we present the evolution of deviation occurrence at regional to global scales. Annually, local streamflow and soil moisture deviations now occur on 18.2% and 15.8% of global land area, respectively, which is 8.0 and 4.7 percentage points beyond the ~3 percentage point wide pre-industrial variability envelope. Our results signify a substantial shift from pre-industrial streamflow and soil moisture reference conditions to persistently increasing change. This indicates a transgression of the new planetary boundary for freshwater change, which is defined and quantified using our approach, calling for urgent actions to reduce human disturbance of the freshwater cycle.

Description: While it is widely assumed that poor countries will suffer more from climate change, and that climate change will exacerbate inequalities within countries, systematic and large-scale evidence on this issue has been limited. In this systematic literature review, we examine and synthesize the evidence from the literature. Drawing from 127 individual papers, we find robust evidence that climate change impacts indeed increase economic inequality and disproportionately affect the poor, both globally and within countries on all continents. This result is valid across a wide range of physical impacts, types of economic inequality, economic sectors, and assessment methods. Furthermore, we highlight the channels through which climate change increases economic inequality. While the diversity of different approaches and metrics in the existing literature base precludes extracting a universal quantitative relation between climate change and economic inequality for use in future modelling, our systematic analysis provides an important stepping stone in that direction.

Description: Observations are increasingly used to detect critical slowing down (CSD) to measure stability changes in key Earth system components. However, most datasets have non-stationary missing-data distributions, biases and uncertainties. Here we show that, together with the pre-processing steps used to deal with them, these can bias the CSD analysis. We present an uncertainty quantification method to address such issues. We show how to propagate uncertainties provided with the datasets to the CSD analysis and develop conservative, surrogate-based significance tests on the CSD indicators. We apply our method to three observational sea-surface temperature and salinity datasets and to fingerprints of the Atlantic Meridional Overturning Circulation derived from them. We find that the properties of these datasets and especially the specific gap filling procedures can in some cases indeed cause false indication of CSD. However, CSD indicators in the North Atlantic are still present and significant when accounting for dataset uncertainties and non-stationary observational coverage.

Description: Die Änderungen wichtiger Klimakenngrößen wie Temperatur und Niederschlag sowie der Konzentration von Spurengasen in der Atmosphäre beeinflussen unmittelbar physiologische Prozesse in Kulturpflanzen und damit die Ernte und die Landwirtschaft insgesamt. Zudem wirken sich Klimaänderungen indirekt auf die Pflanzenproduktion aus, indem sie strukturelle und funktionelle Eigenschaften von Agrarökosystemen verändern. Zu erwarten sind sowohl negative als auch positive Konsequenzen für die deutsche Landwirtschaft. Betrachtet werden neben direkten Auswirkungen auch mögliche Folgen für Schadorganismen und Nutztiere sowie die zu erwartende Entwicklung der Agrarproduktion. Entscheidend dafür, wie diese Effekte ausfallen, sind zum einen die Art und Intensität der Klimaveränderungen selbst, zum anderen die Empfindlichkeit der jeweils betrachteten Produktionssysteme und die Implementierung von Anpassungsmaßnahmen, mit deren Hilfe sich die Folgen des Klimawandels nutzen, vermeiden oder mildern lassen.

Description: Der Wissenschaftszweig der Klimaattribution analysiert den Zusammenhang zwischen beobachteten Aspekten des Klimas und menschlichen Klimaeinflussfaktoren. Mit formalen, statistisch sorgfältigen Nachweis- und Attributionsmethoden sind globale Veränderungen im Klima unzweifelhaft nachgewiesen und erhöhten Treibhausgaskonzentrationen zugeordnet. Auch auf kontinentaler und nationaler Ebene ist dieser Nachweis für Änderungen in Temperaturmitteln sowie -extremen und manchen Niederschlagsindizes erbracht. Mit verwandten Methoden, vor allem denen der probabilistischen Ereignisattribution, werden beobachtete Ereignisse wie eine einzelne Hitzewelle oder ein einzelner Sturm untersucht. Dabei wird typischerweise quantifiziert, ob und wie sich die Auftrittswahrscheinlichkeit der Ereignisse durch den menschengemachten Klimawandel geändert hat. Attributionsergebnisse können Bewusstsein für den Klimawandel schaffen und für Fragen der Klimagerechtigkeit und möglicher Entschädigungen für Klimafolgen relevant sein.

Description: We study the impact of recent global warming on extreme climatic events in Central Asia (CA) for 1901-2019 by comparing the composite representation of the observational climate with a hypothetical counterfactual one that does not include the long-term global warming trend. The counterfactual climate data are produced based on a simple detrending approach, using the global mean temperature (GMT) as the independent variable and removing the long-term trends from the climate variables of the observational data. This trend elimination is independent of causality, and the day-to-day variability in the counterfactual climate remains preserved. The analysis done in the paper shows that the increase in frequency and magnitude of extreme temperature and precipitation events can be attributed to global warming. Specifically, the probability of experiencing a +7 K temperature anomaly event in CA increases by up to a factor of seven in some areas due to global warming. The analysis reveals a significant increase in heatwave occurrences in Central Asia, with the observational climate dataset GSWP3-W5E5 (later called also factual) showing more frequent and prolonged extreme heat events than hypothetical scenarios without global warming. This trend, evident in the disparity between factual and counterfactual data, underscores the critical impact of recent climatic changes on weather patterns, highlighting the urgent need for robust adaptation and mitigation strategies. Additionally, using the self-calibrated Palmer drought severity index (scPDSI), the sensitivity of dry and wet events to the coupled precipitation and temperature changes is analyzed. The areas under dry and wet conditions are enhanced under the observational climate compared to a counterfactual scenario, especially over the largest deserts in CA. The expansion of the dry regions aligns well with the pattern of desert development observed in CA in recent decades.

Description: In der Vergangenheit haben sich Wälder an die geringen Veränderungen des am Wuchsort herrschenden Klimas angepasst. Die gegenwärtige Geschwindigkeit des Klimawandels in Verbindung mit der aktuellen Verteilung der Baumarten überfordert jedoch die natürliche Anpassungsfähigkeit. Vegetationszonen, Verbreitungsgebiete der Baumarten und Artzusammensetzung der Wälder verschieben sich. Das Kapitel charakterisiert die Folgen, die der Klimawandel für die Wälder mit sich bringt, stellt Schadfaktoren im Einzelnen vor und schildert die Auswirkungen auf die Produktivität. Darüber hinaus wird detailliert auf die Rolle des Waldes als Kohlenstoffspeicher eingegangen, denn Wälder produzieren nicht nur den nachwachsenden Rohstoff Holz, sondern sie leisten auch viel für die Umwelt und wirken ausgleichend auf das Klima. Auch mögliche Anpassungsoptionen werden dargestellt.

Description: This study investigates the attribution of climate change to trends in river discharge during six decades from 1955 until 2014 in 12 selected river catchments across six Central Asian countries located upstream of the main rivers. For this purpose, the semi-distributed eco-hydrological model SWIM (Soil and Water Integrated Model) was firstly calibrated and validated for all study catchments. Attributing climate change to streamflow simulation trends was forced by factual (reanalysis) and counterfactual climate data (assuming the absence of anthropogenic influence) proposed in the framework of the ISIMIP (Inter-Sectoral Impact Model Intercomparison Project) or ESM without anthropogenic forcing that were firstly tested and then compared. The trend analysis was performed for three variables: mean annual discharge and high flow (Q5) and low flow (Q95) indices. The results show that trends in the annual and seasonal discharge could be attributed to climate change for some of the studied catchments. In the three northern catchments (Derkul, Shagan, and Tobol), there are positive trends, and in two catchments (Sarysu and Kafirnigan), there are negative streamflow trends under the factual climate, which could be attributed to climate change. Also, our analysis shows that the average level of discharge in Murghab has increased during the historical study period due to climate change, despite the overall decreasing trend during this period. In addition, the study reveals a clear signal of shifting spring streamflow peaks in all catchments across the study area.

Description: Hochwasser in Flussgebieten werden in lokale und plötzliche Sturzfluten in kleinen Gebieten und in Hochwasser an größeren Flüssen unterschieden. Für verschiedene Hochwasserindikatoren und Flusseinzugsgebiete ergeben sich erhebliche Unterschiede, wobei sowohl überwiegend aus Regen als auch überwiegend aus Schmelzwasser gespeiste Hochwasserereignisse betrachtet werden. Besondere Aufmerksamkeit finden Hochwasserereignisse in den großen Flussgebieten von Rhein, Donau, Elbe, Weser und Ems in Deutschland sowie die Entwicklung von Sturzfluten infolge von Extremniederschlägen kurzer Dauer, wobei die Beobachtungen und Trends zu Modellierungsergebnissen in Beziehung gesetzt werden. Auch die Notwendigkeit von Anpassungsmaßnahmen wird diskutiert.

Description: Klimarelevante Naturgefahren sind auf vielfältige Faktoren zurückzuführen, deren Zusammenwirken in der Gesamtheit betrachtet werden muss. Die vorbereitenden, auslösenden und kontrollierenden Faktoren werden in unterschiedlichster Weise vom Klimawandel beeinflusst. Der Beitrag beschreibt verschiedene Arten von Dürren und damit verbundene Folgen und Risiken. Es wird diskutiert, inwieweit Waldbrände tatsächlich ausschließlich dem Klimawandel zuzuschreiben sind, wie sich der Trend bei Waldbränden in der Vergangenheit darstellt und wie sich der Klimawandel in Zukunft auf die Häufigkeit von Waldbränden auswirken könnte.

Description: Wasser ist für den Menschen und seine Umwelt von zentraler Bedeutung. Seine jahreszeitliche Verfügbarkeit prägt Ökosysteme wie auch Kulturen und Gesellschaften. Die Herausforderung, zu viel, zu wenig oder zu schmutziges Wasser zu bewältigen, begleitet den Menschen seit Jahrtausenden. Mit der globalen Klimaänderung verändert sich auch der Wasserkreislauf, insbesondere die Quelle erneuerbaren Süßwassers, nämlich der Niederschlag. Grund ist die mit der globalen Erwärmung einhergehende Intensivierung des Wasserkreislaufs, die zu vergrößerten atmosphärischen Energieumsätzen führt. Aufgrund der Wechselwirkung von Atmosphärendynamik und Landoberflächen sind so in manchen Regionen heftigere Niederschläge, in anderen Regionen aber entgegengesetzte Extreme, wie längere und häufigere Trockenperioden und Dürren, möglich. Die Abschätzung der zukünftigen räumlichen und zeitlichen Verteilung der terrestrischen Wasserverfügbarkeit gehört zu den zentralen wissenschaftlichen Herausforderungen des 21. Jahrhunderts.

Description: As a variant of Support Vector Machine (SVM), Large Margin Distribution Machine (LDM) has been validated to outperform SVM both theoretically and experimentally. Due to the inevitable noise in real applications, the credibility of different samples is not necessarily the same, which is neglected by most existing LDM models. To tackle the above problem, this paper first introduces fuzzy set theory into LDM, and proposes a Fuzzy Large Margin Distribution Machine (FLDM) with better robustness and performance. Considering the noise and uncertainty in datasets, sample points farther from the center of homogenous class are less reliable. Therefore, a fuzzy membership function based on the distance to the class center is utilized to characterize the confidence of each sample, i.e., the degree to which the sample belongs to a certain category. Furthermore, different strategies are developed to obtain class centers for linearly separable and linearly inseparable problems. Experiments conducted on both artificial and UCI datasets verified the superiority of FLDM from different perspectives.

Description: The problem of network disintegration, such as suppression of an epidemic spread and destabilization of terrorist networks, possesses extensive applications and has lately been the focus of growing interest. Many real-world complex systems are represented by spatial networks in which nodes and edges are spatially embedded. However, existing disintegration approaches for spatial network disintegration focus on singular aspects such as geospatial information or network topography, with insufficient modeling granularity. In this paper, we propose an effective and computationally efficient virtual node model that essentially integrates the geospatial information and topology of the network by modeling edges as virtual nodes with weights. Moreover, we employ Kernel Density Estimation, a well-known non-parametric technique for estimating the underlying probability density function of samples, to fit all nodes, comprising both network and virtual nodes, to identify the critical region of the spatial network, which is also the circular geographic region where disintegration occurs. Extensive numerical experiments on synthetic and real-world networks demonstrate that our method outperforms existing methods in terms of both effectiveness and efficiency, which provides a fresh perspective for modeling spatial networks.

Description: Bioenergy with carbon capture and storage (BECCS) can help stabilize the climate by extracting carbon dioxide from the atmosphere while producing renewable energy. However, biomass availability would limit the potential of BECCS, and biomass cropland expansion may threaten biodiversity, food security, and water supply. Replacing land-intensive foods can help unlock sustainable biomass production. Here, we estimated BECCS energy and negative emissions using biomass grown on freed-up land when replacing animal-source foods. Biomass production excludes agricultural expansion to protect biodiversity, ensures enough food supply globally to safeguard food security, and constrains irrigation to secure water for people and ecosystems. Negative emissions consider supply chain emissions and the forgone sequestration from natural revegetation. Results show that replacing 50% of animal products by 2050 could release enough land for BECCS to generate 26.4–39.5 EJelec/year, the scale of coal power today, while removing 5.9–9.3 GtCO2e/year from the atmosphere, almost what coal power emits today.

Description: We investigated the influence of the El Niño-Southern Oscillation (ENSO) on inter-annual precipitation variability in the far-eastern Pacific (FEP) and northern South America (NSA) using an approach based on phase synchronization (PS). First, we carried out a detailed analysis of observational data to define the inter-annual variability, eliminate the seasonal residual frequencies in hydro-climatic anomalies, and assess the statistical significance of PS. Additionally, we characterized the seasonality of regional patterns of sea surface temperature, surface pressure levels, low-level winds and precipitation anomalies associated with the ENSO states. We found that the positive (negative) precipitation anomalies experienced in the FEP and NSA differ from those previously reported in the literature. In particular, the Guianas (northeastern Amazon) and the Caribbean constitute two regions with negative (positive) rainfall anomalies during El Niño (La Niña), separated by a zone of non-significant anomalies along the Orinoco Low-level Jet corridor. Moreover, we showed that the ENSO signal is phase-locked with inter-annual rainfall and low-level wind variability in most of the study regions. Furthermore, we found consistency in the PS between the Central and Eastern Pacific El Niño indices and hydroclimatic anomalies over the Pacific. However, some areas exhibited PS, although they did not show significant precipitation anomalies, suggesting that the influence of ENSO on tropical climatology manifests not only in terms of the magnitude of anomalies but also in terms of the phases only. Our approach advances the understanding of climatic anomalies in tropical regions and provides new insights into the non-linear interactions between ENSO and hydroclimatic processes in tropical Americas.

Description: Lack of nitrogen limits food production in poor countries while excessive nitrogen use in industrial countries has led to transgression of the planetary boundary. However, the potential of spatial redistribution of nitrogen input for food security when returning to the safe boundary has not been quantified in a robust manner. Using an emulator of a global gridded crop model ensemble, we found that redistribution of current nitrogen input to major cereals among countries can double production in the most food insecure countries, while increasing global production of these crops by 12% with no notable regional loss or reducing the nitrogen input to the current production by one third. Redistribution of the input within the boundary increased production by 6–8% compared to the current relative distribution, increasing production in the food insecure countries by two thirds. Our findings provide georeferenced guidelines for redistributing nitrogen use to enhance food security while safeguarding the planet.

Description: Oil seed crops are the second most important field crops after cereals in the agricultural economy globally. The use and demand for oilseed crops such as groundnut, soybean and sunflower have grown significantly, but climate change is expected to alter the agroecological conditions required for oilseed crop production. This study aims to present an approach that utilizes decision-making tools to assess the potential climate change impacts on groundnut, soybean and sunflower yields and the greenhouse gas emissions from the management of the crops. The Decision Support Tool for Agrotechnology Transfer (DSSAT v4.7), a dynamic crop model and the Cool Farm Tool, a GHG calculator, was used to simulate yields and estimate GHG emissions from these crops, respectively. Four representative concentration pathways (RCPs 2.6, 4.5, 6.0, and 8.5), three nitrogen (0, 75, and 150 kg/ha) and phosphorous (0, 30 and 60 P kg/ha) fertilizer rates at three sites in Limpopo, South Africa (Ofcolaco, Syferkuil and Punda Maria) were used in field trials for calibrating the models. The highest yield was achieved by sunflower across all crops, years and sites. Soybean yield is projected to decrease across all sites and scenarios by 2030 and 2050, except at Ofcolaco, where yield increases of at least 15.6% is projected under the RCP 4.5 scenario. Positive climate change impacts are predicted for groundnut at Ofcolaco and Syferkuil by 2030 and 2050, while negative impacts with losses of up to 50% are projected under RCP 8.5 by 2050 at Punda Maria. Sunflower yield is projected to decrease across all sites and scenarios by 2030 and 2050. A comparison of the climate change impacts across sites shows that groundnut yield is projected to increase under climate change while notable yield losses are projected for sunflower and soybean. GHG emissions from the management of each crop showed that sunflower and groundnut production had the highest and lowest emissions across all sites respectively. With positive climate change impacts, a reduction of GHG emissions per ton per hectare was projected for groundnuts at Ofcolaco and Syferkuil and for sunflower in Ofcolaco in the future. However, the carbon footprint from groundnut is expected to increase by 40 to 107% in Punda Maria for the period up to 2030 and between 70-250% for 2050, with sunflower following a similar trend. We conclude that climate change will potentially reduce yield for oilseed crops while management will increase emissions. Therefore, in designing adaptation measures, there is a need to consider emission effects to gain a holistic understanding of how both climate change impacts on crops and mitigation efforts could be targeted.

Description: The planetary boundaries framework defines a safe operating space for humanity. To date, these boundaries have mostly been investigated separately, and it is unclear whether breaching one boundary can lead to the transgression of another. By employing a dynamic global vegetation model, we systematically simulate the strength and direction of the effects of different transgression levels of the climate change boundary (using climate output from ten CMIP6 models for CO2 levels ranging from 350 ppm to 1000 ppm). We focus on climate change-induced shifts of Earth’s major forest biomes, the control variable for the land-system change boundary, both by the end of this century and, to account for the long-term legacy effect, by the end of the millennium. Our simulations show that while staying within the 350 ppm climate change boundary co-stabilizes the land-system change boundary, breaching it (〉450 ppm) leads to its critical transgression with greater severity, the higher the ppm level rises and the more time passes. Specifically, this involves a poleward treeline shift, boreal forest dieback (nearly completely within its current area under extreme climate scenarios), competitive expansion of temperate forest into today’s boreal zone, and a slight tropical forest extension. These interacting changes also affect other planetary boundaries (freshwater change and biosphere integrity) and provide feedback to the climate change boundary itself. Our quantitative process-based study highlights the need for interactions to be studied for a systemic operationalization of the framework.

Description: Ecosystems are under multiple stressors and impacts can be measured with multiple variables. Humans have altered mass and energy flows of basically all ecosystems on Earth towards dangerous levels. However, integrating the data and synthesizing conclusions is becoming more and more complicated. Here we present an automated and easy to apply R package to assess terrestrial biosphere integrity which combines 2 complementary metrics: The BioCol metric quantifies the human colonization pressure exerted on the biosphere through alteration and extraction (appropriation) of net primary productivity, whereas the EcoRisk metric quantifies biogeochemical and vegetation structural changes as a proxy for the risk of ecosystem destabilization. Applied to simulations with the dynamic global vegetation model LPJmL5 for 1500–2016, we find that presently (period 2007–2016), large regions show modification and extraction of 〉25 % of the preindustrial potential net primary production, leading to drastic alterations in key ecosystem properties and suggesting a high risk for ecosystem destabilization. In consequence of these dynamics, EcoRisk shows particularly high values in regions with intense land use and deforestation, but also in regions prone to impacts of climate change such as the arctic and boreal zone. The metrics presented here enable global-scale, spatially explicit evaluation of historical and future states of the biosphere and are designed for use by the wider scientific community, not only limited to assessing biosphere integrity, but also to benchmark model performance. The package will be maintained on GitHub and through that we encourage application also to other models and data sets.

Description: Collective risk social dilemmas are at the heart of the most pressing global challenges we are facing today, including climate change mitigation and the overuse of natural resources. Previous research has framed this problem as a public goods game (PGG), where a dilemma arises between short-term interests and long-term sustainability. In the PGG, subjects are placed in groups and asked to choose between cooperation and defection, while keeping in mind their personal interests as well as the commons. Here, we explore how and to what extent the costly punishment of defectors is successful in enforcing cooperation by means of human experiments. We show that an apparent irrational underestimation of the risk of being punished plays an important role, and that for sufficiently high punishment fines, this vanishes and the threat of deterrence suffices to preserve the commons. Interestingly, however, we find that high fines not only avert freeriders, but they also demotivate some of the most generous altruists. As a consequence, the tragedy of the commons is predominantly averted due to cooperators that contribute only their “fair share” to the common pool. We also find that larger groups require larger fines for the deterrence of punishment to have the desired prosocial effect.