ALBERT

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

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

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

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

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

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

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

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

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

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