ALBERT

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

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

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

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

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

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

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

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

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

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