1,081 results match your criteria: "Potsdam Institute for Climate Impact Research[Affiliation]"

Stock trend prediction is a significant challenge due to the inherent uncertainty and complexity of stock market time series. In this study, we introduce an innovative dual-branch network model designed to effectively address this challenge. The first branch constructs recurrence plots (RPs) to capture the nonlinear relationships between time points from historical closing price sequences and computes the corresponding recurrence quantifification analysis measures.

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Multiple tipping points in the Earth system could be triggered when global warming exceeds specific thresholds. However, the degree of their impact on the East Asian hydroclimate remains uncertain due to the lack of quantitative rainfall records. Here we present an ensemble reconstruction of East Asian summer monsoon (EASM) rainfall since the Last Glacial Maximum (LGM) using nine statistical and machine learning methods based on multi-proxy records from a maar lake in southern China.

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Addressing urban tree loss and inequality in the USA: the need for targeted policies.

Sci Bull (Beijing)

December 2024

Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China.

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Degrowth as a plausible pathway for food systems transformation.

Nat Food

January 2025

Department of Global Development, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY, USA.

Food systems require urgent transformation towards social and ecological sustainability. Degrowth posits a radical pathway of transformation to reduce ecological impacts while increasing well-being and reducing inequality. Here we highlight that degrowth and food systems-albeit both linked to transformation-are not well integrated.

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Agricultural production costs represent less than half of total food prices for higher-income countries and will likely further decrease globally. Added-value components such as transport, processing, marketing and catering show increasing importance in food value chains, especially as countries undergo a nutrition transition towards more complex and industrial food systems. Here, using a combined statistical and process-based modelling framework, we derive and project the value-added component of food prices for 136 countries and 11 different food groups, for food-at-home and food-away-from-home.

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Article Synopsis
  • The risk of disruptions in national food supply is influenced by both local production and imports, yet most assessments overlook the climate effects on producing regions.
  • Using global crop modeling and current trade flows, the study compares domestic production impacts to broader consumption impacts that include climate effects from all supplying regions.
  • The findings indicate that climate change exacerbates supply risks for wealthier countries while potentially mitigating risks for lower-income nations, highlighting the critical need for a global perspective in food security strategies.
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Global mean sea-level (GMSL) change can shed light on how the Earth system responds to warming. Glaciological evidence indicates that Earth's ice sheets retreated inland of early industrial (1850 CE) extents during the Holocene (11.7-0 ka), yet previous work suggests that Holocene GMSL never surpassed early industrial levels.

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Adaptive dynamical networks are ubiquitous in real-world systems. This paper aims to explore the synchronization dynamics in networks of adaptive oscillators based on a paradigmatic system of adaptively coupled phase oscillators. Our numerical observations reveal the emergence of synchronization cluster bursting, characterized by periodic transitions between cluster synchronization and global synchronization.

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Canard cascading (CC) is observed in dynamical networks with global adaptive coupling. It is a slow-fast phenomenon characterized by a recurrent sequence of fast transitions between distinct and slowly evolving quasistationary states. In this Letter, we uncover the dynamical mechanisms behind CC, using an illustrative example of globally and adaptively coupled semiconductor lasers, where CC represents sequential switching on and off the lasers.

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Identifying complex periodic windows surrounded by chaos in the two or higher dimensional parameter space of certain dynamical systems is a challenging task for time series analysis based on complex network approaches. This holds particularly true for the case of shrimp structures, where different bifurcations occur when crossing different domain boundaries. The corresponding dynamics often exhibit either period-doubling when crossing the inner boundaries or, respectively, intermittency for outer boundaries.

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Capturing the intricate dynamics of partially coherent patterns in coupled oscillator systems is vibrant and one of the crucial areas of nonlinear sciences. Considering higher-order Fourier modes in the coupling, we discover a novel type of clustered coherent state in phase models, where inside the coherent region oscillators are further split into q dynamically equivalent subgroups with a 2π/q phase difference between two neighboring subgroups, forming a multicoherent-phase (MUP) chimera state. Both a self-consistency analysis and the Ott-Antonsen dimension reduction techniques are used to theoretically derive these solutions, whose stability are further demonstrated by spectral analysis.

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Extreme precipitation events are projected to intensify with global warming, threatening ecosystems and amplifying flood risks. However, observation-based estimates of extreme precipitation-temperature (EP-T) sensitivities show systematic spatio-temporal variability, with predominantly negative sensitivities across warmer regions. Here, we attribute this variability to confounding cloud radiative effects, which cool surfaces during rainfall, introducing covariation between rainfall and temperature beyond temperature's effect on atmospheric moisture-holding capacity.

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Crop-Specific Emission Projection Suggests Peaking of Agricultural NO by the Middle Century.

Environ Sci Technol

December 2024

State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China.

Agriculture is the largest anthropogenic source of NO emissions and plays a crucial role in global greenhouse gas mitigation. In an increasingly populated world with growing food demands, a precise and high-resolution spatial prediction of agricultural NO emissions becomes essential in reducing global emissions. In this study, an integrated assessment model coupled with the land cover downscaling module is employed to predict crop-specific NO emissions at a 0.

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The One Health (OH) approach, integrating aspects of human, animal, and environmental health, still lacks robustly quantified insights into its complex relationships. To fill this knowledge gap, we devised a comprehensive assessment scheme for OH to assess its progress, synergies, trade-offs, and priority targets. From 2000 to 2020, we find evidence for global progress toward OH, albeit uneven, with its average score rising from 61.

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Resilience Indicators for Tropical Rainforests in a Dynamic Vegetation Model.

Glob Chang Biol

December 2024

Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany.

Article Synopsis
  • * Research using a dynamic global vegetation model (LPJmL) reveals that drier climates exhibit higher autocorrelation values—suggesting a decline in resilience—due to population dynamics and carbon allocation processes unique to these environments.
  • * The study suggests that local ecological mechanisms may explain resilience variations in tropical forests, implying that the Amazon could be adapting to climate change on a localized scale, even though the possibility of a larger tipping point remains.
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Article Synopsis
  • - This study focuses on birhythmic oscillators, which have two stable limit cycles with different properties, and examines how stochastic (random) disturbances affect their movement.
  • - The researchers used a path integral method to find the most probable paths that these oscillators can take when starting from various initial states, revealing how they transition between their stable cycles.
  • - By analyzing noise-induced transitions, the study aims to enhance understanding of complex stochastic systems, presenting a new way to visualize and track the behavior of these oscillators in response to outside influences.
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Improved alternate wetting and drying irrigation increases global water productivity.

Nat Food

December 2024

National Key Laboratory of Water Disaster Prevention, Jiangsu Key laboratory of Soil and Water Processes in Watershed, College of Geography and Remote Sensing, Hohai University, Nanjing, China.

Rice is the staple food for half of the world's population but also has the largest water footprint among cereal crops. Alternate wetting and drying (AWD) is a promising irrigation strategy to improve paddy rice's water productivity-defined as the ratio of rice yield to irrigation water use. However, its global adoption has been limited due to concerns about potential yield losses and uncertainties regarding water productivity improvements.

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This paper investigates the stochastic response of a classical model of the birhythmic Van der Pol oscillator under Poisson white noise excitation. The improved path integration (PI) method is comprehensively derived in this paper and the probability density of the system is calculated using this method. Monte Carlo simulations are employed to validate the accuracy of the improved PI method.

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Article Synopsis
  • Statistical physics and dynamical systems theory are essential for understanding high-impact geophysical events, like temperature extremes and cyclones, which arise from deviations in typical geophysical system behaviors.
  • Traditional statistical techniques can predict the likelihood of these events but struggle to connect them to the underlying physics of anomalous geophysical regimes.
  • The paper discusses this gap in knowledge, highlighting challenges and proposing new approaches, particularly stochastic methods, to improve our understanding of extreme geophysical phenomena.
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Bridging the gender, climate, and health gap: the road to COP29.

Lancet Planet Health

December 2024

Barcelona Supercomputing Center, Barcelona, Spain; Centre on Climate Change and Planetary Health and Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Catalan Institution for Research and Advanced Studies, Barcelona, Spain.

Article Synopsis
  • This text discusses the importance of intersectional approaches in climate policy to address the unique health impacts of climate change on women, girls, and gender-diverse individuals, who often face compounded vulnerabilities due to systemic oppression.
  • It highlights the lack of meaningful gender and health representation in international climate governance, emphasizing that despite some progress, men still dominate decision-making roles in climate policy.
  • The text advocates for promoting gender-responsiveness in climate strategies to enhance inclusivity and effectiveness, leading to more resilient and equitable societies.
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The ecological importance of great apes is widely recognised, yet few studies have highlighted the role of protecting great apes' habitats in mitigating climate change, particularly through carbon sequestration. This study used GIS tools to extract data from various sources, including the International Union for Conservation of Nature database, to examine carbon quantity and great ape abundance in African great ape habitats. Subsequently, we employed a generalised linear model to assess the relationship between locally measured great ape populations abundance and carbon storage across areas with different levels of protection.

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Data-sampled time-varying formation for singular multi-agent systems with multiple leaders.

Neural Netw

January 2025

Department of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, 14473, Germany; Institute of Physics, Humboldt University of Berlin, Berlin, 12489, Germany.

The time-varying formation problem of singular multi-agent systems under sampled data with multiple leaders is investigated in this paper. Firstly, a data-sampled time-varying formation control protocol is proposed in the current study where the communication among followers merely occurred at sampling instants, which can save the controller communication energy significantly. Secondly, necessary and sufficient conditions for the feasibility of the formation function are provided.

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Historically, economic growth has been closely coupled to carbon emissions responsible for climate change, but to stabilize global mean temperature, net-zero carbon emissions are necessary. Some economies have begun to reduce emissions while continuing to grow, but this decoupling is not fast enough to achieve global climate targets. Subnational climate actions seem to be crucial for the achievement of these targets.

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