ALBERT

Description: This paper discusses severe risks to food security and nutrition that are linked to ongoing and projected climate change, particularly climate and weather extremes in global warming, drought, flooding, and precipitation. We specifically consider the impacts on populations vulnerable to food insecurity and malnutrition due to lower income, lower access to nutritious food, or social discrimination. The paper defines climate-related “severe risk” in the context of food security and nutrition, using a combination of criteria, including the magnitude and likelihood of adverse consequences, the timing of the risk and the ability to reduce the risk. Severe climate change risks to food security and nutrition are those which result, with high likelihood, in pervasive and persistent food insecurity and malnutrition for millions of people, have the potential for cascading effects beyond the food systems, and against which we have limited ability to prevent or fully respond. The paper uses internationally agreed definitions of risks to food security and nutrition to describe the magnitude of adverse consequences. Moreover, the paper assesses the conditions under which climate change-induced risks to food security and nutrition could become severe based on findings in the literature using different climate change scenarios and shared socioeconomic pathways. Finally, the paper proposes adaptation options, including institutional management and governance actions, that could be taken now to prevent or reduce the severe climate risks to future human food security and nutrition.

Description: Carbon dioxide removal (CDR) moves atmospheric carbon to geological or land-based sinks. In a first-best setting, the optimal use of CDR is achieved by a removal subsidy that equals the optimal carbon tax and marginal damages. We derive second-best policy rules for CDR subsidies and carbon taxes when no global carbon price exists but a national government implements a unilateral climate policy. We find that the optimal carbon tax differs from an optimal CDR subsidy because of carbon leakage and a balance of resource trade effect. First, the optimal removal subsidy tends to be larger than the carbon tax because of lower supply-side leakage on fossil resource markets. Second, net carbon exporters exacerbate this wedge to increase producer surplus of their carbon resource producers, implying even larger removal subsidies. Third, net carbon importers may set their removal subsidy even below their carbon tax when marginal environmental damages are small, to appropriate producer surplus from carbon exporters.

Description: Climate projections by the fossil fuel industry have never been assessed. On the basis of company records, we quantitatively evaluated all available global warming projections documented by—and in many cases modeled by—Exxon and ExxonMobil Corp scientists between 1977 and 2003. We find that most of their projections accurately forecast warming that is consistent with subsequent observations. Their projections were also consistent with, and at least as skillful as, those of independent academic and government models. Exxon and ExxonMobil Corp also correctly rejected the prospect of a coming ice age, accurately predicted when human-caused global warming would first be detected, and reasonably estimated the “carbon budget” for holding warming below 2°C. On each of these points, however, the company’s public statements about climate science contradicted its own scientific data.

Description: Climate change affects the functioning of all of the components of food systems, often in ways that exacerbate existing predicaments and inequalities among regions of the world and groups in society. At the same time, food systems are a major cause of climate change, accounting for a third of all greenhouse gas (GHG) emissions. Therefore, food systems can and should play a much bigger role in climate policies. This chapter highlights nine action points for climate change adaptation and mitigation in food systems. The chapter shows that numerous practices, technologies, knowledge and social capital already exist for climate action in food systems, with multiple synergies with other important goals, such as the conservation of biodiversity, the safeguarding of ecosystem services, sustainable land management and reducing social and gender inequalities. Many of these solutions are presently being applied at local scales around the world, even if not at sufficient levels. Hence, the major effort to unleash their potential would involve overcoming various technical, political-economic and structural barriers for their much wider application. Some other solutions require research and development investments now, but will focus on helping us meet the longer-term challenges of climate change in regard to food systems in the second half of this century, when most existing food production practices will face unprecedented challenges. In the short term, these pro-poor policy changes and support systems can have a range of positive effects well beyond food systems without delay. In the long term, investments in research will help ensure food security and ecosystem integrity for coming generations.

Description: This article focuses on the neural-network (NN)-based adaptive tracking control issue for a class of high-order nonlinear multiagent systems both subjected to the immeasurable state variables and unknown external disturbance. Combining with the radial basis function NNs (RBF NNs), the composite disturbance observer and state observer for each follower are established, respectively. The purpose of this work is to develop NN-based adaptive tracking control schemes such that the output of each follower ultimately tracks that of the leader and all the signals of the closed-loop systems are semiglobally uniformly ultimately bounded by utilizing the backstepping technique. Furthermore, so as to cope with the sparsity of the control resources, the proposed method is extended to the event-triggered case and the adaptive event-triggered tracking control protocol is formulated for nonlinear multiagent systems. Finally, the numerical example is performed to verify the efficacy of the proposed approach.

Description: Environmental catastrophes, including the increased severity and frequency of climate extremes, can act as “windows of opportunities” that challenge citizens’ mental models and motivate them to engage in reflective processes, challenging their pre-conceived ideas. Less well understood is whether experiencing changing weather conditions, common in mid-latitudes, can have a similar effect and increase the citizens’ concerns about climate change and their willingness to accept more stringent climate policies. In this paper, we investigate the effects of changing seasonal temperature on the perceived seriousness of climate change and willingness to mitigate climate change. We use data from four yearly waves of a spatially explicit representative population survey in Germany and weather records from the postal code areas in which they live. To our knowledge, this study is the first analysis to link individual perceptions towards climate change and different mitigation options with seasonal temperature changes at specific locations in Europe. The analyzed perceptions were strongly influenced by socio-demographic characteristics and broader societal changes, as well as individual experiences of seasonal temperatures. The results show that experienced seasonal temperature change influences personal climate change concerns as well as the willingness to mitigate climate change, although with a weaker effect. The results indicate that it is the absolute temperature variation experienced that is important, rather than whether it is getting colder or warmer than usual. Considering the influences identified in this study can offer a window of opportunity for more stringent and targeted climate change policy.

Description: Most large scale studies assessing climate change impacts on crops are performed with simulations of single crops and with annual reinitialization of the initial soil conditions. This is in contrast to the reality that crops are grown in rotations, often with sizable proportion of the preceding crop residue to be left in the fields and varying soil initial conditions from year to year. In this study, the sensitivity of climate change impacts on crop yield and soil organic carbon to assumptions about annual model reinitialization, specification of crop rotations and the amount of residue retained in fields was assessed for seven main crops across Europe. Simulations were conducted for a scenario period 2040-2065 relative to a baseline from 1980-2005 using the SIMPLACE1modelling framework. Results indicated across Europe positive climate change impacts on yield for C3 crops and negative impacts for maize. The consideration of simulating rotations did not have a benefit on yield variability but on relative yield change in response to climate change which slightly increased for C3 crops and decreased for C4 crops when rotation was considered. Soil organic carbon decreased under climate change in both simulations assuming a continuous monocrop and plausible rotations by between 3% and 10% depending on the residue management strategy.

Description: In this paper we discuss PyBanshee, which is a Python-based open-source implementation of the MATLAB toolbox BANSHEE. PyBanshee constitutes the first fully open-source package to quantify, visualize and validate Non-Parametric Bayesian Networks (NPBNs). The architecture of PyBanshee is heavily based on its MATLAB predecessor. It presents the full implementation of existing tools and introduces new modules. Specifically, PyBanshee allows for: (i) choosing fully parametric one-dimensional margins, (ii) choosing different sample sizes for the model-validation tests based on the Hellinger distance, (iii) drawing user-defined sample sizes of the NPBN, (iv) sample-based conditioning sampling (similarly to the closed-source proprietary package UNINET by LightTwist Software) and (v) visualizing the comparison between the histograms of the unconditional and conditional marginal distributions. New detailed examples demonstrating new features are provided.

Description: Adaptation strategies sustaining agricultural production under climate change are urgently required in Sub-Saharan Africa. To quantify the impacts of different adaptation options in Burkina Faso, this study simulated sorghum yields under current and projected climatic conditions with and without adaptation. We used the Decision Support System for Agrotechnology Transfer (DSSAT) at 0.5° spatial resolution (around 55 km) and forced the model with two climate change scenarios. Our calibrated model showed good agreement between reported and simulated yields (Pearson’s r = 0.77; out-of-sample r = 0.68). DSSAT was configured to mimic four distinct adaptation measures: integrated soil fertility management (ISFM), irrigation, an improved variety, and agroforestry. Results show that nationally averaged sorghum yields are projected to decrease by 5.5% under high emissions by 2090 without adaptation. Major yield losses (up to 35%) would occur in the southern and western parts of the country. Our assessments identify ISFM as the most effective adaptation strategy, increasing yield up to 300%, followed by agroforestry (up to 125%), an improved variety (up to 90%), and irrigation (up to 43%) at the regional scale. ISFM is effective across all regions, while irrigation and an improved variety are most effective in the northern and western parts. Agroforestry, meanwhile, is most effective in the south and eastern part of the country. We conclude that climate change in Burkina Faso could negatively affect sorghum yields, but adequate adaptation options exist to enhance agricultural resilience.

Description: The aim of this paper is to review quantitative large-N studies that investigate the effects of climate change on migration flows. Recent meta-analyses have shown that most studies find that climate change influences migration flows. There are however also many studies that find no effects or show that effects are dependent on specific contexts. To better understand this complexity, we argue that we need to discuss in more detail how to measure climate change and migration, how these measurements relate to each other and how we can conceptualise the relationship between these two phenomena. After a presentation of current approaches to measuring climate change, international and internal migration and their strengths and weaknesses we discuss ways to overcome the limitations of existing analytical frameworks.

Description: As part of the Earth4All project, collaborators have submitted this paper to delve further into the steps to be taken to widely transform our conventional agricultural system to provide food security and improve ecological resilience in a rapidly changing global climate. This article analyses the potential positive effects on soil ecology and crop yield of a global-scale transition to regenerative agriculture, while also considering social spreading dynamics that determine the adoption of such practices by farmers. The authors argue that the transition to a global regenerative agricultural system cannot be achieved without considering the deeper societal processes driving the effective dissemination and adoption of the change. Furthermore, the surrounding factors and conditions such as farmers’ political and institutional embeddedness, public opinion, the economic situation and the climate conditions they face within their region or community, as potential barriers hindering the transition, have to be taken into account. Therefore, it is not only the farmers’ responsibility to drive the change but also the politicians, institutions, companies and individual actors’ one which, all together, will support such transition processes.

Description: The Regional Atmospheric Modelling System (RAMS) driven by data from the CMIP5 Earth System Model HadGEM2-ES was used to simulate daily precipitation over the tropical Americas for both current and future climate, including distinct scenarios (representative concentration pathways 4.5 and 8.5) and different time horizons (short-term, mid-term and long-term changes). The major objective was to evaluate possible future changes in extreme events, with emphasis on the intensity of precipitation events and the duration of wet and dry spells. According to RAMS, longer dry spells are expected over most regions of the tropical Americas in the future, with indications for Northeast Brazil, Caribbean, Northern Amazon, and shorter wet spells over Central America and Amazon. With the exception of the Caribbean, there is a general tendency towards the increased frequency of intense precipitation in the tropical Americas.

Description: A deeper understanding of the intricate relationship be- tween the two components of the Asian Summer Monsoon (ASM) – the Indian Summer Monsoon (ISM) and the East Asian Summer Monsoon (EASM) – is crucial to improve the subseasonal forecasting of extreme precipitation events. Using an innovative complex network-based approach, we identify two dominant synchronization pathways between ISM and EASM – a southern mode between the Arabian Sea and south-eastern China occurring in June, and a north- ern mode between the core ISM zone and northern China which peaks in July – and their associated large-scale at- mospheric circulation patterns. Furthermore, we discover that certain phases of the Madden-Julian oscillation and the lower frequency mode of the boreal summer intrasea- sonal oscillation (BSISO) seem to favour the overall synchro- nization of extreme rainfall events between ISM and EASM while the higher frequency mode of the BSISO is likely to support the shifting between the modes of ISM-EASM con- nection.

Description: The zipped file of this repository contains code and auxiliary data to reproduce the results of the publication: Wenz et al, "DOSE - Global data set of reported sub-national economic output"

Description: Achieving sustainable development requires understanding how human behavior and the environment interact across spatial scales. In particular, knowing how to manage tradeoffs between the environment and the economy, or between one spatial scale and another, necessitates a modeling approach that allows these different components to interact. Existing integrated local and global analyses provide key insights, but often fail to capture 'meso-scale' phenomena that operate at scales between the local and the global, leading to erroneous predictions and a constrained scope of analysis. Meso-scale phenomena are difficult to model because of their complexity and computational challenges, where adding additional scales can increase model run-time exponentially. These additions, however, are necessary to make models that include sufficient detail for policy-makers to assess tradeoffs. Here, we synthesize research that explicitly includes meso-scale phenomena and assess where further efforts might be fruitful in improving our predictions and expanding the scope of questions that sustainability science can answer. We emphasize five categories of models relevant to sustainability science, including biophysical models, integrated assessment models, land-use change models, earth-economy models and spatial downscaling models. We outline the technical and methodological challenges present in these areas of research and discuss seven directions for future research that will improve coverage of meso-scale effects. Additionally, we provide a specific worked example that shows the challenges present, and possible solutions, for modeling meso-scale phenomena in integrated earth-economy models.

Description: Beaufils, T.; Berthet, E.; Ward, H.; & Wenz, L. (2023). Beyond production and consumption: Using throughflows to untangle the virtual trade of externalities. Economic Systems Research. https://doi.org/10.1080/09535314.2023.2174003 - Supporting code and data

Description: Implementing carbon pricing is essential to phase out conventional vehicles for achieving ambitious climate targets in road transport, but doing it in a socially fair way is challenging. The EU’s new system aims to addresse this challenge, but its design impairs effectiveness. Future ratcheting up requires strategic use of carbon price revenues to properly balance social compensation and green investments.

Description: Over the last decades, the natural disturbance is increasingly putting pressure on European forests. Shifts in disturbance regimes may compromise forest functioning and the continuous provisioning of ecosystem services to society, including their climate change mitigation potential. Although forests are central to many European policies, we lack the long-term empirical data needed for thoroughly understanding disturbance dynamics, modeling them, and developing adaptive management strategies. Here, we present a unique database of 〉170,000 records of ground-based natural disturbance observations in European forests from 1950 to 2019. Reported data confirm a significant increase in forest disturbance in 34 European countries, causing on an average of 43.8 million m3 of disturbed timber volume per year over the 70-year study period. This value is likely a conservative estimate due to under-reporting, especially of small-scale disturbances. We used machine learning techniques for assessing the magnitude of unreported disturbances, which are estimated to be between 8.6 and 18.3 million m3/year. In the last 20 years, disturbances on average accounted for 16% of the mean annual harvest in Europe. Wind was the most important disturbance agent over the study period (46% of total damage), followed by fire (24%) and bark beetles (17%). Bark beetle disturbance doubled its share of the total damage in the last 20 years. Forest disturbances can profoundly impact ecosystem services (e.g., climate change mitigation), affect regional forest resource provisioning and consequently disrupt long-term management planning objectives and timber markets. We conclude that adaptation to changing disturbance regimes must be placed at the core of the European forest management and policy debate. Furthermore, a coherent and homogeneous monitoring system of natural disturbances is urgently needed in Europe, to better observe and respond to the ongoing changes in forest disturbance regimes.

Description: Despite decades of increasing investment in conservation, we have not succeeded in ‘‘bending the curve’’ of biodiversity decline. Efforts to meet new targets and goals for the next three decades risk repeating this outcome due to three factors: neglect of increasing drivers of decline; unrealistic expectations and time frames of biodiversity recovery; and insufficient attention to justice within and between generations and across countries. Our Earth system justice approach identifies six sets of actions that when tackled simulta- neously address these failings: (1) reduce and reverse direct and indirect drivers causing decline; (2) halt and reverse biodiversity loss; (3) restore and regenerate biodiversity to a safe state; (4) raise minimum wellbeing for all; (5) eliminate over-consumption and excesses associated with accumulation of capital; and (6) uphold and respect the rights and responsibilities of all communities, present and future. Current conservation cam- paigns primarily address actions 2 and 3, with urgent upscaling of actions 1, 4, 5, and 6 needed to help deliver the post-2020 global biodiversity framework.

Description: Smallholder farmers have adopted diverse adaptation practices to lessen the effect of climate change. However, context-specific information about why particular adaptation strategies are adopted remains limited. This study examined the factors that facilitate the choice of farm-level adaptation strategies to climate change (CC) using data collected from 269 African indigenous vegetable (AIV) farmers in Kenya. A multivariate probit (MVP) regression model was used to evaluate the determinants of adaptation choices. The most frequently adopted strategies considered for analysis were manure application, increased pesticide use, crop rotation, irrigation, change of planting dates and terracing. The results reveal that land ownership, group membership, access to extension services and education level were some of the key drivers of adoption. This implies that policies and programmes that are designed to build the ability of smallholder AIV farmers to adapt to climate change should focus on organising farmers into groups, disseminating timely weather information, improving land tenure security, increasing off-farm employment and providing greater access to extension services.

Description: That climate variability and change can potentially force multiple simultaneous breadbasket crop yield shocks has been established. But research quantifying the mechanisms behind such simultaneous shocks has been constrained by short records of crop yields. Here we compile a dataset of subnational crop yields in 25 countries dating back to 1900 to study the frequency and trends in multiple breadbasket yield shocks and how large-scale climate anomalies on interannual timescales have affected multiple breadbasket yield shocks over the last century. We find that major simultaneous breadbasket yield shocks have occurred in at least three, four, or five of nine breadbaskets 10.3%, 2.3% and 1.1% of the time for maize and 18.4%, 4.6% and 2.3% of the time for wheat. Furthermore, we find that multiple breadbasket yield shocks decreased in frequency even as those breadbaskets experience increasingly frequent climate-related shocks. For both maize and wheat breadbaskets, there were fewer simultaneous yield shocks during the 1975–2017 time period as compared to 1931–1975. Finally, we find that interannual modes of climate variability - such as the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the North Atlantic Oscillation (NAO) - have all affected the relative probability of simultaneous yield shocks in pairs of breadbaskets by up to 20–40% in both maize and wheat breadbaskets. While past literature has focused on the effects of ENSO, we find that at the global scale the NAO affects the overall number of wheat yield shocks most strongly despite only affecting northern hemisphere breadbaskets.

Description: Background: Diarrhoeal disease is a leading cause of childhood illness and death globally, and Shigella is a major aetiological contributor for which a vaccine might soon be available. The primary objective of this study was to model the spatiotemporal variation in paediatric Shigella infection and map its predicted prevalence across low-income and middle-income countries (LMICs). - Methods: Individual participant data for Shigella positivity in stool samples were sourced from multiple LMIC-based studies of children aged 59 months or younger. Covariates included household-level and participant-level factors ascertained by study investigators and environmental and hydrometeorological variables extracted from various data products at georeferenced child locations. Multivariate models were fitted and prevalence predictions obtained by syndrome and age stratum. - Findings: 20 studies from 23 countries (including locations in Central America and South America, sub-Saharan Africa, and south and southeast Asia) contributed 66 563 sample results. Age, symptom status, and study design contributed most to model performance followed by temperature, wind speed, relative humidity, and soil moisture. Probability of Shigella infection exceeded 20% when both precipitation and soil moisture were above average and had a 43% peak in uncomplicated diarrhoea cases at 33°C temperatures, above which it decreased. Compared with unimproved sanitation, improved sanitation decreased the odds of Shigella infection by 19% (odds ratio [OR]=0·81 [95% CI 0·76–0·86]) and open defecation decreased them by 18% (OR=0·82 [0·76–0·88]). - Interpretation: The distribution of Shigella is more sensitive to climatological factors, such as temperature, than previously recognised. Conditions in much of sub-Saharan Africa are particularly propitious for Shigella transmission, although hotspots also occur in South America and Central America, the Ganges–Brahmaputra Delta, and the island of New Guinea. These findings can inform prioritisation of populations for future vaccine trials and campaigns.

Description: The planetary crises require health professionals to understand the interlinkages between health and environmental changes, and how to reduce ecological harm (ie, ecological footprint) and promote positive change (ie, ecological handprint). However, health professions’ education and training are mostly lacking these aspects. In this Viewpoint, we report findings from the evaluation of the Planetary Health Academy, the first open online lecture series for transformative planetary health education in Germany. In a retrospective online survey, 458 of 3656 Planetary Health Academy participants reported on their emotions towards climate change, attitudes towards health professionals’ responsibilities, self-efficacy, and the contribution of the Planetary Health Academy to their knowledge and actions. Additionally, motivators and barriers to acting were assessed. Our findings provide insights that can inform future efforts for transformative education. Combined with network and movement building, education could act as a social tipping element toward actions to mitigate global environmental changes.

Description: To feed the growing population, achieve the Sustainable Development Goals, and fulfil the commitments of the Paris Agreement, West African countries need to invest in agricultural development and renewable energy, among other sectors. Irrigated agriculture, feeding millions of people, and hydropower, generating clean electricity, depend on water availability and compete for the resource. In the Volta basin, the planned 105 000 ha of irrigated land in Burkina Faso and Ghana could feed hundreds of thousands of people. However, irrigation in the dry season depends on upstream dams that change the river’s flow regime from intermittent to permanent, and at the same time irrigation water is no longer available for hydropower generation. Using an integrated eco-hydrological and water management model, we investigated the water demand and supply of three planned irrigation projects and the impacts of the planned Pwalugu multi-purpose dam on the hydropower potentials and water availability in the entire Volta basin. We found that future irrigation withdrawals would reduce the hydropower potential in the Volta basin by 79 GWh a−1 and the operation of Pwalugu by another 86 GWh a−1. Hence, Pwalugu contributes only about 101 GWh a−1 of its potential of 187 GWh a−1. Under climate change simulations, using an ensemble of eight bias-adjusted and downscaled GCMs, irrigation demand surprisingly did not increase. The higher evaporation losses due to higher temperatures were compensated by increasing precipitation while favouring hydropower generation. However, water availability at the irrigation site in Burkina Faso is clearly at its limit, while capacity in Ghana is not yet exhausted. Due to hydro-climatic differences in the Volta basin, the cost of irrigating one hectare of land in terms of lost hydropower potential follows a north-south gradient from the hot and dry north to the humid south. Nevertheless, food production should have priority over hydropower, which can be compensated by other renewables energies.

Description: Many feedback loops significantly increase warming due to greenhouse gas emissions. However, not all of these feedbacks are fully accounted for in climate models. Thus, associated mitigation pathways could fail to sufficiently limit temperatures. A targeted expansion of research and an accelerated reduction of emissions are needed to minimize risks

Description: Ambitious climate mitigation policies face social and political resistance. One reason is that existing policies insufficiently capture the diversity of relevant insights from the social sciences about potential policy outcomes. We argue that agent-based models can serve as a powerful tool for integration of elements from different disciplines. Having such a common platform will enable a more complete assessment of climate policies, in terms of criteria like effectiveness, equity and public support.

Description: Bei der Energiewende auf dem Weg zur Emissionsneutralität gilt es vor allem, CO2-Emissionen so weit wie möglich zu vermeiden – durch eine zügige Umstellung auf Erneuerbare Energien, innovative klimaneutrale Produktionsverfahren etc. Für eine Netto-Null in der Emissionsbilanz reicht das allein jedoch nicht aus, denn in manchen Bereichen lassen sich Emissionen nicht oder nur sehr schwer vermeiden, zum Beispiel bei bestimmten Industrieprozessen oder in der Landwirtschaft. In dieser Analyse werden in Erweiterung des Ariadne-Szenarienreports (Luderer et al., 2021) die vielschichtigen Wechselbeziehungen zwischen Vermeidungsoptionen und CO2-Entnahmepotenzialen beleuchtet und Handlungsspielräume abgesteckt. Diese Analyse gibt Orientierungspunkte, unter welchen Bedingungen lokal in Deutschland Treibhausgasneutralität erreicht werden könnte. Es zeigt sich, dass nur die Ausnutzung aller verfügbaren Optionen, sowohl bei der Vermeidung von Restemissionen als auch bei der Entnahme von CO2 aus der Atmosphäre, Spielräume eröffnet, die gegen das hohe Risiko, dass nicht alle ambitionierten Annahmen in den Szenarien auch eintreffen werden, absichert.

Description: Zusammenfassung 1. Einleitung 2. Nach Energiewende verbleibende Restemissionen bestimmen den Bedarf an CO2-Entnahme in Deutschland in 2045 3. Angebot an CO2-Entnahme in Deutschland bis 2045 4. Diskussion der Ergebnisse Anhang Literaturangaben

Description: The question of how climatic changes and hazards affect human mobility has increasingly gained prominence in public debates over the past decade. Despite improvements in the scientific understanding of the subject and advancements in policy, major gaps remain in addressing the humanitarian and socio-economic challenges related to climate migration. In this perspectives article, we argue for a holistic approach and a closer integration of science and policy involving diverse stakeholders in the process of knowledge generation and implementation. We identify five key challenges characteristic for improving the science–policy interface: (i) conflictual political contexts and the securitization of human migration, (ii) simplistic narratives and framing of the subject, (iii) the uneven production and dissemination of knowledge, (iv) limited data and analytical capacities and (v) a selective topical and methodological focus. To address these diverse challenges, there is a need for more bridging initiatives at the science–policy interface that integrate diverse disciplines, approaches and stakeholders. A closer engagement of researchers and policymakers in the form of multi-stakeholder exchanges, capacity-building activities, co-development and co-implementation processes and integrative scientific assessments can help bridge the gap to support the inclusive generation of knowledge and the development of comprehensive policies.

Description: The observed temperature increase due to anthropogenic carbon emissions has impacted economies worldwide. National income levels in origin and destination countries influence international migration. Emigration is relatively low not only from high income countries but also from very poor regions, which is explained in current migration theory by credit constraints and lower average education levels, among other reasons. These relationships suggest a potential non-linear, indirect effect of climate change on migration through this indirect channel. Here we explore this effect through a counterfactual analysis using observational data and a simple model of migration. We show that a world without climate change would have seen less migration during the past 30 years, but that this effect is strongly reduced due to inhibited mobility. Our framework suggests that migration within the Global South has been strongly reduced because these countries have seen less economic growth than they would have experienced without climate change. Importantly, climate change has impacted international migration in the richer and poorer parts of the world very differently. In the future, climate change may keep in- creasing global migration as it slows down countries' transition across the middle-income range associated with the highest emigration rates.

Description: Um die ambitionierten Klimaschutzziele zu erreichen, braucht Deutschland effektive Instrumente und Maßnahmen auf nationaler, bundesstaatlicher und kommunaler Ebene. Der Erfolg dieser Politik wird maßgeblich davon abhängen, ob es gelingt, eine breite gesellschaftliche Akzeptanz und Unterstützung für diese Maßnahmen auf den entsprechenden Ebenen zu erreichen. Die Haltung der Bevölkerung wird jedoch in der Regel auf nationaler Ebene über Umfragen gemessen, die geographische Unterschiede dabei auf den subnationalen Ebenen außer Acht lassen. Im Rahmen dieser Analyse schätzen wir die durchschnittliche Bevölkerungszustimmung zu 26 Klimaschutzmaßnahmen in den Sektoren Wärme, Transport und Energie auf Bundesland-, Landkreis- und kommunaler Ebene zwischen 2017 und 2021 mittels eines mehrstufigen Regressions- und Poststratifizierungsmodells. Die Schätzungen basieren auf zwei bundesweit repräsentativen Panel-Umfragen, dem Sozialen Nachhaltigkeitsbarometer und dem Ariadne Wärme-& Wohnen-Panel. Durch die Analyse werden erhebliche regionale Unterschiede in der Zustimmung von Klimaschutzmaßnahmen in der deutschen Bevölkerung sichtbar. Die Befürwortung einzelner Klimaschutzmaßnahmen variiert teilweise um bis zu 60 Prozentpunkte zwischen den untersuchten geographischen Einheiten. In der Gesamtbetrachtung der räumlichen Disparitäten zeichnen sich bedeutsame Unterschiede zwischen Stadt- und Landbevölkerung sowie West- und Ostdeutschland ab. Im zeitlichen Verlauf haben sich dabei die Einstellungen gegenüber einzelnen Maßnahmen, wie beispielsweise dem Ausbau von Wind- und Solarkraftanlagen, angenähert, während die öffentliche Meinung zu anderen energiepolitischen Instrumenten, wie dem Kohleausstieg, im Laufe der Jahre polarisieren. Mittels einer zusätzlich durchgeführten räumlichen Panelanalyse können wir zudem zeigen, dass sich die Veränderungen von bestimmten Kontextfaktoren auf die Zustimmung von Klimaschutzmaßnahmen auf kommunaler Ebene auswirken. So finden wir einen positiven Zusammenhang zwischen der Befürwortung des Ausbaus von Wind- und Solarkraftanlagen und dem tatsächlichen Zubau an Solar- und Windkapazitäten in diesen Regionen. Ferner wird die Haltung gegenüber klimapolitischen Maßnahmen stark von räumlichen Diffusionseffekten, d.h. der Ausbreitung von Einstellungen im sozialen Umfeld, bestimmt, wie der Einfluss von Meinungsänderungen in einer Region auf deren Nachbarregionen veranschaulicht. Die in diesem Bericht und auf dem interaktiven Online-Dashboard zur Verfügung gestellten Schätzungen der Zustimmung zu Klimaschutzmaßnahmen, stellen eine wichtige Informationsgrundlage für politische Entscheidungsträger:innen dar, um den gesellschaftlichen Herausforderungen bei der Umsetzung von Klimaschutzmaßnahmen effektiv zu begegnen. Alle generierten Daten sind im Online-Dashboard „Lokale Klimaschutzeinstellungen in Deutschland“ unter https://hertie-school-ariadne.shinyapps.io/LocalAttitudesDashboard/ einsehbar.

Description: The quest for a theory of cities that could offer a quantitative and systematic approach to manage cities represents a top priority. If such a theory is feasible, then its formulation must be in a mathematical way. As a contribution to organizing the mathematical ideas that deal with such a systematic way of understanding urban phenomena, we review the main mathematical models present in the literature that aim at explaining the origin and emergence of urban scaling. We intend to present the models, identify similarities and connections between them, and find situations in which different models lead to the same output. In addition, we report situations in which some ideas initially introduced in a particular model can also be introduced in another model, generating more diversification and increasing the scope of the models. The models treated in this paper explain urban scaling from different premises, i.e. from gravity ideas, over densification ideas and cites’ geometry, to a hierarchical organization and social network properties. We also investigate scenarios in which these different fundamental ideas could be interpreted as similar – where the similarity is likely but not obvious. Furthermore, in what concerns the gravity idea, we propose a general framework that includes all gravity models analyzed as a particular case. We conclude the paper by discussing perspectives of this field and how future research designs and schools of thought can build on the models treated here.

Description: Rhythmic activities that alternate between coherent and incoherent phases are ubiquitous in chemical, ecological, climate, or neural systems. Despite their importance, general mechanisms for their emergence are little understood. In order to fill this gap, we present a framework for describing the emergence of recurrent synchronization in complex networks with adaptive interactions. This phenomenon is manifested at the macroscopic level by temporal episodes of coherent and incoherent dynamics that alternate recurrently. At the same time, the dynamics of the individual nodes do not change qualitatively. We identify asymmetric adaptation rules and temporal separation between the adaptation and the dynamics of individual nodes as key features for the emergence of recurrent synchronization. Our results suggest that asymmetric adaptation might be a fundamental ingredient for recurrent synchronization phenomena as seen in pattern generators, e.g., in neuronal systems. We describe a phenomenon of recurrent synchronization in complex dynamical networks with asymmetric adaptivity. The recurrent synchronization describes a generic mechanism of a repeating abrupt loss and gain of synchronization in complex dynamical networks. From an applied perspective, our results show how adaptation mechanisms can play a fundamental role for pattern generators, e.g., in neuronal systems. Methodologically, we present a framework for studying complex temporal patterns in adaptive dynamical networks. This mechanisms might be relevant for the understanding of the pathophysiology of Parkinsonian resting tremor and other impaired central pattern generators.

Description: The stickiness effect is a fundamental feature of quasi-integrable Hamiltonian systems. We propose the use of an entropy-based measure of the recurrence plots (RPs), namely, the entropy of the distribution of the recurrence times (estimated from the RP), to characterize the dynamics of a typical quasi-integrable Hamiltonian system with coexisting regular and chaotic regions. We show that the recurrence time entropy (RTE) is positively correlated to the largest Lyapunov exponent, with a high correlation coefficient. We obtain a multi-modal distribution of the finite-time RTE and find that each mode corresponds to the motion around islands of different hierarchical levels. In two-dimensional quasi-integrable Hamiltonian systems with hierarchical phase space, chaotic orbits can spend an arbitrarily long time around islands, in which they behave similarly as quasiperiodic orbits. This phenomenon is called stickiness, and it is due to the presence of partial barriers to the transport around the hierarchical levels of islands-around-islands. The stickiness affects the convergence of the Lyapunov exponents, making the task of characterizing the dynamics more difficult, especially when only short time series are known. Due to the intrinsic property of dynamical systems that quasiperiodic orbits can have at most three different return times (Slater’s theorem1,2 ), which is the time needed to the orbit return to a given region at the curve, in this paper, we propose the use of the recurrence time entropy (RTE) (estimated from the recurrence plots) to characterize the dynamics of nonlinear systems. We find that the RTE is an alternative way of detecting chaotic orbits and sticky regions. Furthermore, the finite-time RTE distribution is multi-modal when sticky regions are present in the phase space, and each mode corresponds to a different hierarchical level in the islands-around-islands structure embedded in the chaotic sea.

Description: Cyclones are among the most hazardous extreme weather events on Earth. In certain scenarios, two co-rotating cyclones in close proximity to one another can drift closer and completely merge into a single cyclonic system. Identifying the dynamic transitions during such an interaction period of binary cyclones and predicting the complete merger (CM) event are challenging for weather forecasters. In this work, we suggest an innovative approach to understand the evolving vortical interactions between the cyclones during two such CM events (Noru–Kulap and Seroja–Odette) using time-evolving induced velocity-based unweighted directed networks. We find that network-based indicators, namely, in-degree and out-degree, quantify the changes in the interaction between the two cyclones and are excellent candidates to classify the interaction stages before a CM. The network indicators also help to identify the dominant cyclone during the period of interaction and quantify the variation of the strength of the dominating and merged cyclones. Finally, we show that the network measures also provide an early indication of the CM event well before its occurrence. In some active cyclone basins, more than one cyclone can be formed concurrently. Consequently, two or more cyclones can come in close spatial proximity and start interacting with each other; this type of interaction is known as the “Fujiwhara interaction.” Such an interaction may lead to many possibilities, such as weakening of both cyclones, sudden alteration in their tracks, re-strengthening of one of the cyclones due to vorticity interaction, and, very rarely, the birth of a more intense long-lived cyclone due to complete merging between them. This binary interaction between cyclones has not been fully understood and remains a major challenge for weather forecasters. This often leads to inaccurate predictions, increasing the risk of human life and property due to unpreparedness. Most previous investigations have used the separation distance between the cyclones to classify the stages of binary interaction leading to merging and to predict their merger. However, the separation distance between the cyclones does not only influence the Fujiwhara interaction but also depends on it. In particular, the Fujiwhara effect may alter the track of cyclones, leading to elastic interaction, partial straining out, or the partial merger between two cyclones. As a result, characterizing the behavior of binary cyclones based on the separation distance may be difficult. In this study, we use a novel approach based on complex networks. We analyze the vortical interactions in the spatial domain by constructing time-evolving induced velocity networks. Using two prominent examples of complete merger events, namely, the Seroja–Odette and Noru–Kulap interactions in the Northern and Southern Hemispheres, respectively, we show that network-based measures are successful in classifying the binary interaction stages.

Description: Phase transitions in equilibrium and nonequilibrium systems play a major role in the natural sciences. In dynamical networks, phase transitions organize qualitative changes in the collective behavior of coupled dynamical units. Adaptive dynamical networks feature a connectivity structure that changes over time, coevolving with the nodes’ dynamical state. In this Letter, we show the emergence of two distinct first-order nonequilibrium phase transitions in a finite-size adaptive network of heterogeneous phase oscillators. Depending on the nature of defects in the internal frequency distribution, we observe either an abrupt single-step transition to full synchronization or a more gradual multistep transition. This observation has a striking resemblance to heterogeneous nucleation. We develop a mean-field approach to study the interplay between adaptivity and nodal heterogeneity and describe the dynamics of multicluster states and their role in determining the character of the phase transition. Our work provides a theoretical framework for studying the interplay between adaptivity and nodal heterogeneity.

Description: Agriculture is a major sector responsible for greenhouse gas emissions. Local food production can contribute to reducing transport-related emissions. Since most of the worldwide population lives in cities, locally producing food implies practicing agriculture in urban and peri-urban areas. Exemplary, we analyze the potential to produce fresh vegetables within Berlin, Germany. We investigate the spatial extent of five different urban spaces for soil-based agriculture or gardening, i.e., non-built residential areas, allotment gardens, rooftops, supermarket parking lots, and cemeteries. We also quantify inputs required for such food production in terms of water, human resources, and investment. Our findings highlight that up to 82% of Berlin’s vegetable demand could be produced within the city, based on a reasonable validation of existing areas. Meeting this potential requires 42 km of urban spaces for cultivation, a considerable amount of irrigation water, around 17 thousand gardeners, and over 750 million EUR of initial investments. The final vegetable cost would be around 2 EUR to 10 EUR per kg without any profit margin. We conclude that it is realistic to produce a significant amount of Berlin’s vegetable demand within the city, even if it comes with great challenges.

Description: Study Region: The Naryn River Basin, Kyrgyzstan. - Study Focus: We investigate the impacts of climate change in the basin based on two families of General Circulation Models (GCMs) using the hydrological model SWAT. The forcing datasets are the widely used ISIMIP2 (I2) and the newly derived ISIMIP3 (I3) data which refer to the 5th and 6th stage of the Coupled Model Intercomparison Project (CMIP). Due to notable differences in the forcing we evaluate their impacts on various hydrological components of the basin, such as discharge, evapotranspiration (ETA) and soil moisture (SM). Besides, a partial correlation (PC) analysis is used to assess the meteorological controls of the basin with special emphasize on the SM-ETA coupling. - New Hydrological Insights for the Region: Agreement in the basin’s projections is found, such as discharge shifts towards an earlier peak flow of one month, significant SM reductions and ETA increases. I3 temperature projections exceed their previous estimates and show an increase in precipitation, which differs from I2. However, the mitigating effects do not lead to an improvement in the region’s susceptibility to soil moisture deficits. The PC study reveals enhanced water-limited conditions expressed as positive SM-ETA feedback under I2 and I3, albeit slightly weaker under I3.

Description: Many modern extinction drivers are shared with past mass extinction events, such as rapid climate warming, habitat loss, pollution and invasive species. This commonality presents a key question: can the extinction risk of species during past mass extinction events inform our predictions for a modern biodiversity crisis? To investigate if it is possible to establish which species were more likely to go extinct during mass extinctions, we applied a functional trait-based model of extinction risk using a machine learning algorithm to datasets of marine fossils for the end-Permian, end-Triassic and end-Cretaceous mass extinctions. Extinction selectivity was inferred across each individual mass extinction event, before testing whether the selectivity patterns obtained could be used to ‘predict’ the extinction selectivity exhibited during the other mass extinctions. Our analyses show that, despite some similarities in extinction selectivity patterns between ancient crises, the selectivity of mass extinction events is inconsistent, which leads to a poor predictive performance. This lack of predictability is attributed to evolution in marine ecosystems, particularly during the Mesozoic Marine Revolution, associated with shifts in community structure alongside coincident Earth system changes. Our results suggest that past extinctions are unlikely to be informative for predicting extinction risk during a projected mass extinction.

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: Dynamical stability of the synchronous regime remains a challenging problem for secure functioning of power grids. Based on the symmetric circular model [Hellmann et al., Nat. Commun. 11, 592 (2020)], we demonstrate that the grid stability can be destroyed by elementary violations (motifs) of the network architecture, such as cutting a connection between any two nodes or removing a generator or a consumer. We describe the mechanism for the cascading failure in each of the damaging case and show that the desynchronization starts with the frequency deviation of the neighboring grid elements followed by the cascading splitting of the others, distant elements, and ending eventually in the bi-modal or a partially desynchronized state. Our findings reveal that symmetric topology underlines stability of the power grids, while local damaging can cause a fatal blackout. A particular complexity of the power grid stability is caused by the fact that the desired synchronous state is only locally stable, not globally. In the system phase state, it repeatedly co-exists with many other desynchronized states. In such a case, the desired grid synchrony can be secured only against small perturbations but not against large impacts, even applied to a single grid element or to a single connection. If so, the system’s dynamics can switch to another, desynchronized attractor as soon as a large perturbation is applied. The essential difficulties of the power grid studies are also induced by intricate, highly asymmetric architectures of the realistic grids, often caused by geographical and historical reasons. What is the role of asymmetry for the stability? Which grids with symmetric or asymmetric topology are more reliable? We attack this problem by examining a symmetric circular power grid model and compare its stability with the situation when the symmetry is broken by elementary violations of the network structure.

Description: In many specific scenarios, accurateand practical cooperative learning is a commonly encountered challenge in multi-agent systems. Thus, the current investigation focuses on cooperative learning algorithms for multi-agent systems and underpins an alternate data-based neural network reinforcement learning framework. To achieve the data-based learning optimization, the proposed cooperative learning framework, which comprises two layers, introduces a virtual learning objective. The followers learn the behaviors of the virtual objects in the first layer based on the adaptive neural networks (NNs). Specifically, the actor and critic NNs are applied to acquire cooperative behaviors and assess this layer's long-term utility function. Then another layer realizes the tracking performance between the virtual objects and the leader by introducing the local data-based performance index. Then, we formulate a resulting deterministic optimization problem and resolve it effectively with the policy iteration algorithm. This intuitive cooperative learning algorithm also preserves good robustness properties and eliminates the dependence on the prior knowledge of the multi-agent system model in the solution process. Finally, a multi-robot formation system demonstrates this promising development's practical appeal and highly effective outcome.

Description: The blood–brain barrier (BBB) limits the delivery of majority of cancer drugs and thereby complicates brain tumor treatment. The nasal-brain-lymphatic system is discussed as a pathway for brain drug delivery overcoming the BBB. However, in most cases, this method is not sufficient to achieve a therapeutic effect due to brain drug delivery in a short distance. Therefore, it is necessary to develop technologies to overcome the obstacles facing nose-to-brain delivery of promising pharmaceuticals. In this study, we clearly demonstrate intranasal delivery of liposomes to the mouse brain reaching glioblastoma (GBM). In the experiments with ablation of the meningeal lymphatic network, we report an important role of meningeal pathway for intranasal delivery of liposomes to the brain. Our data revealed that GBM is characterized by a dramatic reduction of intranasal delivery of liposomes to the brain that was significantly improved by near-infrared (1267 nm) photostimulation of the lymphatic vessels in the area of the cribriform plate and the meninges. These results open new perspectives for non-invasive improvement of efficiency of intranasal delivery of cancer drugs to the brain tissues using nanocarriers and near-infrared laser-based therapeutic devices, which are commercially available and widely used in clinical practice.

Description: The lymphatic drainage system of the brain (LDSB) is the removal of metabolites and wastes from its tissues. A dysfunction of LDSB is an important sign of aging, brain oncology, the Alzheimer's and Parkinson's diseases. The development of new strategies for diagnosis of LDSB injuries can improve prevention of age-related cerebral amyloid angiopathy, neurodegenerative and cerebrovascular diseases. There are two conditions, such as deep sleep and opening of the blood-brain-barrier (OBBB) associated with the LDSB activation. A promising candidate for measurement of LDSB could be electroencephalography (EEG). In this pilot study on rats, we tested the hypothesis, whether deep sleep and OBBB can be an informative platform for an effective extracting of information about the LDSB functions. Using the nonlinear analysis of EEG dynamics and machine learning technology, we discovered that the LDSB activation during OBBB and sleep is associated with similar changes in the EEG θ-activity. The OBBB causes the higher LDSB activation vs. sleep that is accompanied by specific changes in the low frequency EEG activity extracted by the power spectra analysis of the EEG dynamics combined with the coherence function. Thus, our findings demonstrate a link between neural activity associated with the LDSB activation during sleep and OBBB that is an important informative platform for extraction of the EEG-biomarkers of the LDSB activity. These results open new perspectives for the development of technology for the LDSB diagnostics that would open a novel era in the prognosis of brain diseases caused by the LDSB disorders, including OBBB.

Description: Emerging evidence suggests that an important function of the sleeping brain is the removal of wastes and toxins from the central nervous system (CNS) due to the activation of the brain waste removal system (BWRS). The meningeal lymphatic vessels (MLVs) are an important part of the BWRS. A decrease in MLV function is associated with Alzheimer’s and Parkinson’s diseases, intracranial hemorrhages, brain tumors and trauma. Since the BWRS is activated during sleep, a new idea is now being actively discussed in the scientific community: night stimulation of the BWRS might be an innovative and promising strategy for neurorehabilitation medicine. This review highlights new trends in photobiomodulation of the BWRS/MLVs during deep sleep as a breakthrough technology for the effective removal of wastes and unnecessary compounds from the brain in order to increase the neuroprotection of the CNS as well as to prevent or delay various brain diseases.

Description: The progress in brain diseases treatment is limited by the blood-brain barrier (BBB), which prevents delivery of the vast majority of drugs from the blood into the brain. In this study, we discover unknown phenomenon of opening of the BBBB (BBBO) by low-level laser treatment (LLLT, 1268 nm) in the mouse cortex. LLLT-BBBO is accompanied by activation of the brain drainage system contributing effective delivery of liposomes into glioblastoma (GBM). The LLLT induces the generation of singlet oxygen without photosensitizers (PSs) in the blood endothelial cells and astrocytes, which can be a trigger mechanism of BBBO. LLLT-BBBO causes activation of the ABC-transport system with a temporal decrease in the expression of tight junction proteins. The BBB recovery is accompanied by activation of neuronal metabolic activity and stabilization of the BBB permeability. LLLT-BBBO can be used as a new opportunity of interstitial PS-free photodynamic therapy (PDT) for modulation of brain tumor immunity and improvement of immuno-therapy for GBM in infants in whom PDT with PSs, radio- and chemotherapy are strongly limited, as well as in adults with a high allergic reaction to PSs.

Description: Correlation analysis serves as an easy-to-implement estimation approach for the quantification of the interaction or connectivity between different units. Often, pairwise correlations estimated by sliding windows are time-varying (on different window segments) and window size-dependent (on different window sizes). Still, how to choose an appropriate window size remains unclear. This paper offers a framework for studying this fundamental question by observing a critical transition from a chaotic-like state to a nonchaotic state. Specifically, given two time series and a fixed window size, we create a correlation-based series based on nonlinear correlation measurement and sliding windows as an approximation of the time-varying correlations between the original time series. We find that the varying correlations yield a state transition from a chaotic-like state to a nonchaotic state with increasing window size. This window size-dependent transition is analyzed as a universal phenomenon in both model and real-world systems (e.g., climate, financial, and neural systems). More importantly, the transition point provides a quantitative rule for the selection of window sizes. That is, the nonchaotic correlation better allows for many regression-based predictions. Complex connections between different units can be simply approximated by correlation analysis between corresponding time series. When the complete information (the entire time series) is considered for analysis, dynamic connections are aggregated into a single value, reflecting the overall macro linkage. When segmented information (a sliced time series) is combined with sliding windows, the underlying dynamic connections can be approximated by time-varying correlations. Intuitively, the longer the segments are, the more likely to capture cyclic behavior. A typical example is that in climate science, large-scale climate phenomena, such as seasonal changes induced by the annual cycle of solar radiation, are not observable on the timescale of diurnal cycles. Similarly, for correlation analysis, choosing a suitable window scale to capture the necessary patterns hidden in the time series is fundamental; yet, how to do so is unclear. We intend to address this issue in our work.

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: A waste-to-protein system that integrates a range of waste-to-protein upgrading technologies has the potential to converge innovations on zero-waste and protein security to ensure a sustainable protein future. We present a global overview of food-safe and feed-safe waste resource potential and technologies to sort and transform such waste streams with compositional quality characteristics into food-grade or feed-grade protein. The identified streams are rich in carbon and nutrients and absent of pathogens and hazardous contaminants, including food waste streams, lignocellulosic waste from agricultural residues and forestry, and contaminant-free waste from the food and drink industry. A wide range of chemical, physical, and biological treatments can be applied to extract nutrients and convert waste-carbon to fermentable sugars or other platform chemicals for subsequent conversion to protein. Our quantitative analyses suggest that the waste-to-protein system has the potential to maximise recovery of various low-value resources and catalyse the transformative solutions toward a sustainable protein future. However, novel protein regulation processes remain expensive and resource intensive in many countries, with protracted timelines for approval. This poses a significant barrier to market expansion, despite accelerated research and development in waste-to-protein technologies and novel protein sources. Thus, the waste-to-protein system is an important initiative to promote metabolic health across lifespans and tackle the global hunger crisis.

Description: African paleoanthropological studies typically focus on regions of the continent such asEastern, Southern and Northern Africa, which hold the highest density of Pleistocenearchaeological sites. Nevertheless, lesser known areas such as West Africa also feature a highnumber of sites. Here, we present a high-resolution map synthesising all well contextualisedPleistocene archaeological sites present in Sub-Saharan West Africa. A detailed elevation andecoregional map was developed and correlated with palaeoanthropological sites. This mapis supplemented with 1,000- and 2000-year interval climate reconstructions over the last120,000 years for three subregions of high archaeological interest. The presentedarchaeological sites were compiled by reviewing published literature, and selected basedon: (1) documented archaeological stratification or 〉10 characteristic artefacts, (2) publishedcoordinates, and (3) published chronometric ages or relative dating. The data presentedhere elucidates the current state of knowledge of Pleistocene West Africa, highlighting theregional potential for human evolutionary studies.

Description: Wie schon 2021 hat der Gebäudesektor auch im vergangenen Jahr die erlaubten Emissionen gemäß Bundes-Klimaschutzgesetz überschritten. Die Fernwärme kann einen Beitrag leisten, um die Trendwende hin zur angestrebten Klimaneutralität zu schaffen. Klar ist aber auch, dass die Wärmenetze der Zukunft deutlich flexibler und effizienter werden müssen, etwa um aus erneuerbaren Quellen oder Abwärme von Rechenzentren gewonnene Wärme nutzen zu können. Angesichts der hohen Lebensdauer der Wärmenetze von etwa 50 bis 60 Jahren ist ein Umbau dieser Netze auf die Erfordernisse der Wärmewende besonders kritisch. Allerding müssen für eine erfolgreiche Anpassung verschiedene Ebenen ineinandergreifen: Die kommunale Wärmewende, die Transformation der Netze sowie die Digitalisierung der Verbrauchsmessungen. Ergebnis der Ariadne-Analyse ist, dass für die erforderlichen Umrüstungen der Netze ein massives Finanzierungsproblem besteht. So bleiben Fernwärmenetzbetreiber auf etwa 90% der Investitionskosten sitzen. Durch eine Nahverdichtung der Fernwärmeanschlüsse könnten die Kosten verringert werden. Weiterhin bietet die Nachrüstung der Wärmezähler für die Fernauslesbarkeit bis Ende 2026 die Möglichkeit, Maßnahmen zu kombinieren, etwa den Austausch der Hausstation und den hydraulischen Abgleich. Eine koordinierte Einbeziehung der handelnden Akteure könnte daher zur Trendwende im Wärmesektor beitragen.

Description: Trends in flood magnitudes vary across the conterminous USA (CONUS). There have been attempts to identify what controls these regionally varying trends, but these attempts were limited to certain—for example, climatic—variables or to smaller regions, using different methods and datasets each time. Here we attribute the trends in annual maximum streamflow for 4,390 gauging stations across the CONUS in the period 1960–2010, while using a novel combination of methods and an unprecedented variety of potential controlling variables to allow large-scale comparisons and minimize biases. Using process-based flood classification and complex networks, we find 10 distinct clusters of catchments with similar flood behavior. We compile a set of 31 hydro-climatological and land use variables as predictors for 10 separate Random Forest models, allowing us to find the main controls the flood magnitude trends for each cluster. By using Accumulated Local Effect plots, we can understand how these controls influence the trends in the flood magnitude. We show that hydro-climatologic changes and land use are of similar importance for flood magnitude trends across the CONUS. Static land use variables are more important than their trends, suggesting that land use is able to attenuate (forested areas) or amplify (urbanized areas) the effects of climatic changes on flood magnitudes. For some variables, we find opposing effects in different regions, showing that flood trend controls are highly dependent on regional characteristics and that our novel approach is necessary to attribute flood magnitude trends reliably at the continental scale while maintaining sensitivity to regional controls.

Description: The analysis of event time series is in general challenging. Most time series analysis tools are limited for the analysis of this kind of data. Recurrence analysis, a powerful concept from nonlinear time series analysis, provides several opportunities to work with event data and even for the most challenging task of comparing event time series with continuous time series. Here, the basic concept is introduced, the challenges are discussed, and the future perspectives are summarized.

Description: This paper introduces the Graphics Processing Unit (GPU)-based tool Geo-Temporal eXplorer (GTX), integrating a set of highly interactive techniques for visual analytics of large geo-referenced complex networks from the climate research domain. The visual exploration of these networks faces a multitude of challenges related to the geo-reference and the size of these networks with up to several million edges and the manifold types of such networks. In this paper, solutions for the interactive visual analysis for several distinct types of large complex networks will be discussed, in particular, time-dependent, multi-scale, and multi-layered ensemble networks. Custom-tailored for climate researchers, the GTX tool supports heterogeneous tasks based on interactive, GPU-based solutions for on-the-fly large network data processing, analysis, and visualization. These solutions are illustrated for two use cases: multi-scale climatic process and climate infection risk networks. This tool helps one to reduce the complexity of the highly interrelated climate information and unveils hidden and temporal links in the climate system, not available using standard and linear tools (such as empirical orthogonal function analysis).

Description: This paper addresses the issue of dynamic mean-square consensus for second-order hybrid multi-agent systems. Time-varying delays and multiplicative noises are considered. New distributed control protocols are designed based on data-sampled information of neighbor agents. Equivalently using the error system based on Laplacian matrix, the method could make a dynamic consensus both under the fixed and switching topologies. By adopting stochastic system theory, Lyapunov stability method and linear matrix inequality theory, several sufficient conditions for the dynamic mean-square consensus are obtained. The upper bound of time delay and the discrete-time sampling period of hybrid multi-agent systems under a stochastic noises environment are inferred. Several simulations are presented to demonstrate the effectiveness of the proposed methods.

Description: Achieving the goals outlined in the Paris agreement requires significant reductions in national carbon emissions. To fairly distribute the burden of mitigation, a detailed understanding of the social realities of emitters is needed. This sector-specific and sub-regional study was carried out to examine housing energy emissions in the UK and to obtain detailed information about the socioeconomic profiles of emitters. To account for the embedded nature of individuals in social groups and the social context, we applied the conceptual approach of socio-metabolic class theory. This theory posits that carbon emissions and the level of human agency are unequally distributed within the society. As a first attempt, the theory is operationalised using CO2 emission quartiles as central units of descriptive analysis. We find significant differences between these classes, and particularly in terms of cohabitation type, home ownership, and social vulnerability factors. Complementary results from a multivariate regression analysis indicate that the main determinants of housing carbon emissions are living space, household size, and the use of heating oil. We conclude by describing the contribution of our findings to socio-metabolic class theory, outlining future directions for research at the intersection of social class and ecology, and policy implications related to a low-carbon transition.

Description: Given two dynamical systems, we quantify how similar they are with respect to their interaction with the outside world. We focus on the case where simpler systems act as a specification for a more complex one. Combining a behavioral and probabilistic perspective we define several useful notions of the distance of a system to a specification. We show that these distances can be used to tune a complex system. We demonstrate that our approach can successfully make non-linear networked systems behave like much smaller networks, allowing us to aggregate large sub-networks into one or two effective nodes. Finally, we discuss similarities and differences between our approach and H∞ model reduction.

Description: Background: Despite considerable progress made over the past 20 years in reducing the global burden of malaria, the disease remains a major public health problem and there is concern that climate change might expand suitable areas for transmission. This study investigated the relative effect of climate variability on malaria incidence after scale-up of interventions in western Kenya. - Methods: Bayesian negative binomial models were fitted to monthly malaria incidence data, extracted from records of patients with febrile illnesses visiting the Lwak Mission Hospital between 2008 and 2019. Data pertaining to bed net use and socio-economic status (SES) were obtained from household surveys. Climatic proxy variables obtained from remote sensing were included as covariates in the models. Bayesian variable selection was used to determine the elapsing time between climate suitability and malaria incidence. - Results: Malaria incidence increased by 50% from 2008 to 2010, then declined by 73% until 2015. There was a resurgence of cases after 2016, despite high bed net use. Increase in daytime land surface temperature was associated with a decline in malaria incidence (incidence rate ratio [IRR] = 0.70, 95% Bayesian credible interval [BCI]: 0.59–0.82), while rainfall was associated with increased incidence (IRR = 1.27, 95% BCI: 1.10–1.44). Bed net use was associated with a decline in malaria incidence in children aged 6–59 months (IRR = 0.78, 95% BCI: 0.70–0.87) but not in older age groups, whereas SES was not associated with malaria incidence in this population. - Conclusions: Variability in climatic factors showed a stronger effect on malaria incidence than bed net use. Bed net use was, however, associated with a reduction in malaria incidence, especially among children aged 6–59 months after adjusting for climate effects. To sustain the downward trend in malaria incidence, this study recommends continued distribution and use of bed nets and consideration of climate-based malaria early warning systems when planning for future control interventions.

Description: To satisfy the increasing global demand for agricultural products, the expansion of irrigation is an important intensification measure. At the same time, unsustainable water abstractions and cropland expansion pose a threat to biodiversity and ecosystem functioning. Irrigation potentials are influenced by local biophysical irrigation water availability and competition of different water users. Using a novel hydro-economic data processing routine that considers economic criteria of water allocation via a productivity ranking of grid cells and both land and water sustainability criteria, we estimate global irrigation potentials at a 0.5 ° spatial resolution. We show that there is considerable technical potential to expand irrigation within local water and land boundaries. In terms of potentially irrigated areas on all global land suitable for crop production, 2144 Mha could be irrigated within land and water environmental boundaries when only considering biophysical criteria. However, not all of these areas would actually be irrigated under consideration of irrigation costs. Of these, only 698 Mha (330 Mha) have a yield gain of more than 300 (600) USD ha-1 under the current crop mix valued at their current commodity price (economic irrigation potential).

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: An ensemble of bias adjusted regional climate model simulations based on EURO-CORDEX (CORDEX-EUR11). The data set covers daily temperature (minimum, average and maximum) and precipitation for historical, rcp26, rcp45 and rcp85 experiments covering a period from 1971 to 2100. In total 8 different RCMs from 8 institutes are included in the data set. ISIMIP3BASD v2.4.1 (https://doi.org/10.5281/zenodo.4686991) method was used for bias adjustment. The method is based on a parametric quantile mapping, including trend preservation of each quantile. Bias adjustment was performed for each variable separately. We used E-OBS v19.0e (https://doi.org/10.1029/2017JD028200) data to calibrate the bias adjustment transfer functions for the period 1971 to 2005. The data was developed and utilized within the Clim4Vitis project - Climate change impact mitigation for European viticulture (https://clim4vitis.eu). We acknowledge the World Climate Research Programme's Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5. We also thank the climate modelling groups (CLMcom, DMI, GERICS, IPSL-INERIS, KNMI, MPI-CSC, SMHI and UHOH) for producing and making available their model output. We also acknowledge the Earth System Grid Federation infrastructure an international effort led by the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison, the European Network for Earth System Modelling and other partners in the Global Organisation for Earth System Science Portals (GO-ESSP).

Description: The atmospheric concentration of CO2 at which global glaciation (snowball) bifurcation occurs, changes throughout 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 an important prerequisite for understanding past Snowball Earth episodes as well as the conditions for habitability on Earth and other planets. Here we use the coupled climate model CLIMBER-3α in an Aquaplanet configuration to scan for the Snowball bifurcation point for time slices spanning the last 4 billion years, thus quantifying the time evolution of the bifurcation and identifying a qualitative shift in critical state dynamics.

Description: Die Dekarbonisierung des Verkehrs- und Stromsystems ist ein weitreichender Transformationsprozess, der erhebliche Veränderungen für die Menschen mit sich bringt. Er kann nur als gesamtgesellschaftliche Aufgabe gelingen, die aus Betroffenen Beteiligte macht und Interessen sowie Vorstellungen von Bürgerinnen und Bürgern berücksichtigt. Wirksame Beteiligung im Forschungs- und Politikprozess sind bei der Verkehrs- und Stromwende deshalb unabdingbar. Unterschiedliche Formate, wie Befragungen und Deliberation erlauben es, die Einstellungen aus einem Querschnitt der Gesellschaft zu Politikoptionen zu untersuchen und Betroffene somit an der Entwicklung dieser partizipieren zu lassen. In dieser Analyse untersuchen wir in zwei parallel durchgeführten Befragungen im Rahmen der Ariadne Bürgerdeliberation und einer repräsentativen Panelbefragung die Haltung der Bürger:innen gegenüber verschiedenen Politikoptionen in den Bereichen Verkehr und Strom. Das Ziel war hierbei durch die vergleichende Betrachtung besser zu verstehen, welche Optionen gesellschaftlich mitgetragen werden (und welche nicht) und aus welchen Gründen. Die Verbindung beider Zugänge bietet eine umfassende Perspektive auf die gesellschaftliche Trägerschaft der Energie- und Verkehrswende. Die Bürgerinnen und Bürger sprachen sich in beiden Bereichen – Strom und Verkehr – für möglichst gerechte und effektive politische Optionen aus. Die Mehrheit der Befragten ist bereit, Veränderungen mitzutragen, wenn gewährleistet wird, dass alle Menschen und vulnerable Gruppen Zugang zu bezahlbarer Mobilität und Energieversorgung haben. Dies spiegelt sich in der Wahrnehmung von Stärken der verschiedenen Optionen und dem Wunsch, das Beste aus den Welten und Pfaden zu kombinieren. Für die Energie- und Verkehrswende insgesamt zeigen die Bürger:innensichten die Wichtigkeit einer Politik auf, die sich sowohl an sozialen als auch ökologischen Auswirkungen orientiert. Der klimafreundliche Umbau des Energiesystems wird von einer breiten gesellschaftlichen Mehrheit in Deutschland getragen und die Menschen sind bereit, sich bei der Umsetzung aktiv zu engagieren. Bei der Frage der Art der Gestaltung wird von den 2 Bürger:innen mehrheitlich eine dezentrale Energieversorgungsstruktur bevorzugt. Damit sind jedoch sowohl Hoffnungen als auch Sorgen verbunden. In der Verkehrswende ist den Menschen eine faire Teilhabe an Mobilität wichtig, dass also die verschiedenen Mobilitätsbedürfnisse diverser gesellschaftlicher Gruppen berücksichtigt werden. Neben der sozialen Gerechtigkeit spielt in der Verkehrswende auch die Klimawirkung – also die Effektivität von Maßnahmen – eine zentrale Rolle für die gesellschaftliche Trägerschaft. Trotz verbleibendem Diskussionsbedarf der beteiligten Bürger:innen zu konkreten Umsetzungsfragen zeigen die Ergebnisse die Bereitschaft sich mit den Auswirkungen politischer Optionen auseinanderzusetzen und dadurch Wandel nicht primär als Bedrohung und Sorge, sondern als Chance auf ein inklusiveres und attraktiveres Zusammenleben zu sehen. Eine Voraussetzung für einen wissenschaftlich informierten Lernprozess ist, das Wissen zu Politikoptionen und deren Auswirkungen für die breite Gesellschaft zugänglich und erfahrbar zu machen. Sowohl wissenschaftlich fundierte Informationsangebote als auch verständigungsorientierte Diskussionen sind effektive Formate, um dies zu ermöglichen. Letztlich lebt auch dieser Lernprozess von der Bereitschaft eigene Annahmen zu hinterfragen und sich für neue bzw. andere Argumente zu öffnen, die einem bisher als wenig relevant oder kaum nachvollziehbar erschienen. Zudem unterstreicht diese Analyse, dass in wissenschaftlich gut informierten Prozessen Bürger:innensichten eine wertvolle Ressource und Chance für eine besser gesellschaftlich abgestimmte und damit tragfähigere Klimapolitik darstellen. Aus Bürger:innensicht sollten diverse Wertvorstellungen, Bedürfnisse und Interessen bei der Umsetzung der Transformationen Eingang finden. Deswegen braucht es nach Meinung der Autorinnen und Autoren dieser Analyse einen Weg, wie die Politik über diese informiert wird – eine vielversprechende Möglichkeit hierfür ist die Befähigung von Bürger:innen zur politischen Mitbestimmung durch ein möglichst heterogenes Spektrum an Beteiligungsformen. Aus dieser Sicht stellt der Einbezug von Bürger:innensichten eine Chance für eine tragfähigere, an den Bedürfnissen der Bürger:innen orientierte

Description: Source code of LPJmL version 4 (Schaphoff et al. 2018a,b) and version 5 (von Bloh et al. 2018, Lutz et al. 2019, Herzfeld et al. 2021) as used to generate input data for MAgPIE (Dietrich et al. 2019), making use of the ISIMIP3b future climate scenarios (Lange and Büchner 2020) and the GGCMI Phase3 LPJmL setup (Jägermeyr et al. 2021).

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: Parameter table for the corrigendum of the paper "All options, not silver bullets, needed to limit global warming to 1.5 °C: a scenario appraisal" by Warszawski et al. (2021) published in Environmental Research Letters. The 50 emissions scenarios considered for analysis in this paper, including the numerical value for the 8 parameters (5 levers and 3 milestones) used in this analysis. For the individual levers, cells shaded blue stay within the high upper bounds, and cells shaded green stay within the medium upper bounds. Scenarios that stay within all high upper bounds, i.e. the filtered ensemble, are shaded blue. The SR1.5 scenarios P1-P4 are flagged on the left of the table. The P4, Shell and IEA scenarios appear at the end of the table.

Description: Klimaschutzpolitik ist eine Wette: Eine ehrgeizige Verminderung klimaschädlicher Treibhausgasemissionen kann auch dann gerechtfertigt werden, wenn die Wahrscheinlichkeit katastrophaler Folgen des Klimawandels gering ist. Je niedriger die Kosten der Vermeidung und je höher die möglichen materiellen und immateriellen Schäden eines ungebremsten Klimawandels sind, umso sinnvoller ist es, eine ambitionierte Klimapolitik umzusetzen (Edenhofer/Jakob 2017). Die Klimapolitik beschränkt dabei die zuvor freie Nutzung der Atmosphäre als Treibhausgasdeponie und macht sie zu einem regulierten globalen Gemeinschaftsgut.

Description: GDP scenarios are major drivers of climate change and climate change mitigation assessment studies. In this paper, a major update of the SSP GDP projections is presented. By using the most recent economic data and short-term projections by the World Bank and International Monetary Fund, the update captures changes in the system of national accounting and purchasing power parities, as well as the impact of the Covid 19 pandemic. Harmonization between the data and the original end-of-the century SSP projections was carried out in terms of GDP per capita in order to preserve the underlying narrative of income convergence. The result is a set of projections compatible with the most recent data and the SSP narratives. A comparison of DICE models calibrated to the original and updated SSP2 GDP per capita projections illustrates how significant the impact of an update of income data on integrated assessment results can be. The estimated global social costs of carbon in 2015 and 2030 rose by almost 30%.