Tipping elements in the climate system are large-scale subregions of the Earth that might possess threshold behavior under global warming with large potential impacts on human societies. Here, we study a subset of five tipping elements and their interactions in a conceptual and easily extendable framework: the Greenland and West Antarctic Ice Sheets, the Atlantic Meridional Overturning Circulation (AMOC), the El-Nino Southern Oscillation (ENSO) and the Amazon rainforest. In this nonlinear and multistable system, we perform a basin stability analysis to detect its stable states and their associated Earth system resilience. Using this approach, we perform a system-wide and comprehensive robustness analysis with more than 3.5 billion ensemble members. Further, we investigate dynamic regimes where some of the states lose stability and oscillations appear using a newly developed basin bifurcation analysis methodology. Our results reveal that the state of four or five tipped elements has the largest basin volume for large levels of global warming beyond 4 °C above pre-industrial climate conditions. For lower levels of warming, states including disintegrated ice sheets on West Antarctica and Greenland have higher basin volume than other state configurations. Therefore in our model, we find that the large ice sheets are of particular importance for Earth system resilience. We also detect the emergence of limit cycles for 0.6% of all ensemble members at rare parameter combinations. Such limit cycle oscillations mainly occur between the Greenland Ice Sheet and AMOC (86%), due to their negative feedback coupling. These limit cycles point to possibly dangerous internal modes of variability in the climate system that could have played a role in paleoclimatic dynamics such as those unfolding during the Pleistocene ice age cycles.
ClimTip-GML: A global bias-corrected and downscaled dataset for assessing impacts of climate tipping events
Technical University of Munich（慕尼黑工业大学）；Potsdam Institute for Climate Impact Research（波茨坦气候影响研究所）；Ludwig-Maximilians University of Munich（慕尼黑路德维希-马克西米利安大学）；Met Office（英国气象局）；Utrecht University（乌得勒支大学）；University of Exeter（埃克塞特大学）
A stable hothouse triggered by a tipping mechanism
Brevan Howard Centre for Financial Analysis, Imperial College Business School, Imperial College London（帝国理工学院商业学院布雷文·霍华德金融分析中心）；Laboratoire de Météorologie Dynamique (CNRS & IPSL), Ecole Polytechnique（巴黎综合理工学院动力气象学实验室（法国国家科学研究中心与IPSL））；Unit of Theoretical Chronobiology, Faculty of Sciences, Université Libre de Bruxelles（布鲁塞尔自由大学理学院理论时间生物学单元）；Geosciences Department and Laboratoire de Météorologie Dynamique (CNRS & IPSL), Ecole Normale Supérieure and PSL University（巴黎高等师范学院和PSL大学地质科学系及动力气象学实验室（法国国家科学研究中心与IPSL））；Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles（加州大学洛杉矶分校大气与海洋科学系）；Department of Mathematics, Imperial College London（帝国理工学院数学系）
University of Victoria（维多利亚大学）；Palo Alto Research Center（帕洛阿尔托研究中心）；Excarta；University of California San Diego（加利福尼亚大学圣迭戈分校）；University of Washington（华盛顿大学）
Marine cloud brightening (MCB) is a proposed climate intervention technology to partially offset greenhouse gas warming and possibly avoid crossing climate tipping points. The impacts of MCB on regional climate are typically estimated using computationally expensive Earth System Model (ESM) simulations, preventing a thorough assessment of the large possibility space of potential MCB interventions. Here, we describe an AI model, named AiBEDO, that can be used to rapidly projects climate responses to forcings via a novel application of the Fluctuation-Dissipation Theorem (FDT). AiBEDO is a Multi…
Climate response metrics are used to quantify the Earth's climate response to anthropogenic changes of atmospheric CO2. Equilibrium Climate Sensitivity (ECS) is one such metric that measures the equilibrium response to CO2 doubling. However, both in their estimation and their usage, such metrics make assumptions on the linearity of climate response, although it is known that, especially for larger forcing levels, response can be nonlinear. Such nonlinear responses may become visible immediately in response to a larger perturbation, or may only become apparent after a long transient. In this pa…
Planetary climate interactions of the Qinghai-Tibetan Plateau
Beijing Normal University（北京师范大学）；Technical University of Munich（慕尼黑工业大学）；Potsdam Institute for Climate Impact Research（波茨坦气候影响研究所）；Institute of Atmospheric Physics, Chinese Academy of Sciences（中国科学院大气物理研究所）；Humboldt University（洪堡大学）；Bar-Ilan University（巴伊兰大学）；Institute of Tibetan Plateau Research, Chinese Academy of Sciences（中国科学院青藏高原研究所）；Tsinghua University（清华大学）
Several environmental tipping points and self-reinforcing feedback loops are still disregarded within the frequently used climate models. Thus, existing climate models are not very representative for providing projections of the conditions after the actual environmental tipping points are triggered. In this contribution, we discuss the presence of the Arctic sea-ice loss tipping point and its influence on global warming. Our literature search and PIOMAS sea volume observation data based projection indicate the significant acceleration of the sea-ice loss (which leads to a year around and perma…
Abrupt and irreversible winter Arctic sea-ice loss may occur under anthropogenic warming due to the collapse of a sea-ice equilibrium at a threshold value of CO$_2$, commonly referred to as a tipping point. Previous work has been unable to conclusively identify whether a tipping point in Arctic sea ice exists because fully-coupled climate models are too computationally expensive to run to equilibrium for many CO$_2$ values. Here, we explore the deviation of sea ice from its equilibrium state under realistic rates of CO$_2$ increase to demonstrate how a few time-dependent CO$_2$ experiments can…
Seasonal cycle of Precipitation over Major River Basins in South and Southeast Asia: A Review of the CMIP5 climate models data for present climate and future climate projections
Quantifying the safe operating space for the Amazon rainforest under climate change and deforestation
Potsdam Institute for Climate Impact Research（波茨坦气候影响研究所）；Utrecht University（乌得勒支大学）；Stockholm University（斯德哥尔摩大学）；Max Planck Institute of Geoanthropology（马克斯·普朗克人类geoanthropology研究所）；University of Potsdam（波茨坦大学）；Goethe University Frankfurt（法兰克福歌德大学）；Senckenberg Research Institute and Natural History Museum（森根堡自然历史博物馆研究学院）
Constructing efficient score functions for rare event simulation in high-dimensional ocean-climate models
Institute for Marine and Atmospheric research Utrecht, Department of Physics, Utrecht University（乌得勒支大学海洋与大气研究所物理系）；Utrecht University（乌得勒支大学）；Netherlands eScience Center（荷兰电子科学中心）；IMEC；Centre for Complex Systems Studies, Department of Physics, Utrecht University（乌得勒支大学复杂系统研究中心物理系）
University of Waterloo（滑铁卢大学）；University of Exeter（埃克塞特大学）；Wageningen University（瓦赫宁根大学）；McGill University（麦吉尔大学）；University of Guelph（圭尔夫大学）
The potential for complex systems to exhibit tipping points in which an equilibrium state undergoes a sudden and often irreversible shift is well established, but prediction of these events using standard forecast modeling techniques is quite difficult. This has led to the development of an alternative suite of methods that seek to identify signatures of critical phenomena in data, which are expected to occur in advance of many classes of dynamical bifurcation. Crucially, the manifestations of these critical phenomena are generic across a variety of systems, meaning that data-intensive deep le…
Climate network characterization of the AMOC edge state
University of Geneva（日内瓦大学）；Centre pour la Vie dans l’Univers (CVU)（宇宙生命中心）；Institute for Marine and Atmospheric research Utrecht（乌得勒支海洋与大气研究所）；Utrecht University（乌得勒支大学）；School of Computing and Mathematical Sciences, University of Leicester（莱斯特大学计算与数学科学学院）；Schools of Sciences, Great Bay University（大湾区大学理学院）
Multi-stability of Atlantic and Pacific overturning: The role of Freshwater Forcing Asymmetries and the Hydrological Cycle
Utrecht University（乌得勒支大学）；Institute for Marine and Atmospheric research Utrecht, Department of Physics, Utrecht University（乌得勒支大学物理系海洋与大气研究所）；Centre for Complex Systems Studies, Utrecht University（乌得勒支大学复杂系统研究中心）
Advancing Seasonal Prediction of Tropical Cyclone Activity with a Hybrid AI-Physics Climate Model
University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Google Research（谷歌研究院）；Geophysical Fluid Dynamics Laboratory, National Oceanic and Atmospheric Administration（美国国家海洋和大气管理局地球流体动力学实验室）
Selection of CMIP6 Models for Regional Precipitation Projection and Climate Change Assessment in the Jhelum and Chenab River Basins
Department of Computer Science, University of Évora（埃夫拉尔大学计算机科学系）；MED—Mediterranean Institute for Agriculture, Environment and Development & CHANGE—Global Change and Sustainability Institute, Institute for Advanced Studies and Research, University of Évora（地中海农业、环境与发展研究所及全球变化与可持续性研究所，埃夫拉尔大学高级研究学院）；NUST Institute of Civil Engineering (NICE), School of Civil and Environmental Engineering (SCEE), National University of Sciences and Technology (NUST)（国家科技大学土木工程研究所（NICE）、土木与环境工程学院（SCEE））；Institute of Geographical Information Systems (IGIS), School of Civil and Environmental Engineering (SCEE), National University of Sciences and Technology (NUST)（地理信息系统研究所（IGIS）、土木与环境工程学院（SCEE），国家科技大学）；IMT Atlantique, Lab-STICC UMR CNRS 6285（IMT Atlantic、Lab-STICC UMR CNRS 6285）
