Global Temperature Change Research Articles

Projected changes of thermal, rainfall and drought indices in Morocco from high resolution climate models

Abstract Over the past decade, global changes in temperature, average and extreme precipitation have been observed many times. The increase in temperature or even the change in precipitation systems is directly affect extreme weather events, for example, heat waves, heavy rainfall, storms, and droughts are becoming more frequent and more powerful worldwide due to climate change caused by several factors including human activity. This is why there is a necessity to monitor future changes in climate extremes. The objective of this paper is to evaluate the future changes in thermal and rainfall extremes projected by the four climate models over time horizon 2041-2060 relative to the 1981-2010 reference period, based on the 5 climate indices, including Tmm, Tx90p, WSDI, PRCPTOT and SPI. The projections are given under the RCP 4.5 medium scenario. The analysis in thermal aspect shows that Morocco could experience by 2041-2060, a significant warming, has manifested by an increase in average temperature. Future changes in rainfall indices show that the spatial distribution of rainfall in Morocco could change significantly by 2041-2060 compared to the reference period 1971-2010. The four climate models agree on a decrease in annual precipitation that could affect most of the Kingdom. In the same way to dryness, the future changes of the SPI index that characterizes the drought, indicates a move to a dry climate.

To What Extent Does Discounting ‘Hot’ Climate Models Improve the Predictive Skill of Climate Model Ensembles?

AbstractIt depends. The Intergovernmental Panel on Climate Change's (IPCC) Assessment Report Six (AR6) took a step toward ending so‐called ‘model democracy’ by discounting climate models that are too warm over the historical period (i.e., models that ‘run hot’) when making projections of global temperature change. However, the IPCC did not address whether this procedure is reliable for other quantities. Here, we explore the implications of weighting climate models according to their skill in reproducing historical global‐mean surface temperature using three other climate variables of interest: global average precipitation change, regional average temperature change, and regional average precipitation change. We find that the temperature‐based weighting scheme leads to an improved prediction of global average precipitation, though we show that this prediction could be overconfident. On regional scales, we find a heterogeneous pattern of error reduction in future regional precipitation. This stands in sharp contrast with the broad regional pattern of error reduction in future temperature projections, though we do find regions where error is not significantly reduced. Our results demonstrate that practitioners using weighted climate model ensembles for climate projections must take care when weighting by temperature alone, lest they produce unreliable climate projections that result from an inappropriate weighting procedure.

Predictive Modeling of Global Temperature Change Based on Artificial Intelligence Algorithms

As the greenhouse effect intensifies, global temperature changes are increasingly affecting all aspects of economic life. The purpose of this paper is to analyze the influencing factors of temperature to establish an analytical model of global temperature change. The Berkeley Earth Climate Database provides access to the data needed for the study. Pearson correlation analysis was used to quantify the strength of the correlations between temperature, location and other factors. After that, global temperatures were modelled and predicted by artificial intelligence algorithms such as ARIMA and linear regression prediction models, respectively. The results test that the model has good stability and can achieve accurate prediction function. The model can better help predict and respond to global temperature changes. The application of this AI algorithm can be used as a reference in other fields.

Change of global land extreme temperature in the future

Understanding future temperature extremes is pivotal to preparing for and mitigating the impacts of climate change. This study proposed machine learning techniques to develop a multi-model ensemble model for high-resolution projection of global land temperature extremes under different emission scenarios, hence providing enhanced precision over previous climate model projections. By utilizing the NEX-GDDP-CMIP6 dataset with bias adjustment and the Gradient Booster algorithm, we reduced the biases that existed in Global Climate Models. The model significantly reduces the root mean square errors (RMSEs) for both the daily maximum and daily minimum temperature extremes. A future scenario analysis revealed that global temperature extremes would substantially increase under high-emission scenarios, highlighting the urgency for stringent emission reduction commitments. This study also identified regions like Greenland, the Tibetan Plateau, and the regional Arctic Archipelago as potential hotspots of temperature extremes under these scenarios. The multi-model ensemble approach, tuned with machine learning and driven by high-resolution data, contributes to climate science by providing refined insights into future temperature extremes, thereby offering direction to climate change mitigation and adaptation strategies.

Advancing chronologies for Last Interglacial sequences

ABSTRACTStudies of the Last Interglacial (ca. 129 to 116 ka BP) provide an opportunity to study the impact of high‐latitude warm temperatures on the Earth system. To build an accurate spatio‐temporal picture of climate and environmental variability during the Last Interglacial, building robust chronologies, through which the patchwork of terrestrial, marine, and ice core archives can be correlated, is paramount. In this review, we briefly evaluate the most common approaches used to date climate and environmental archives from the Last Interglacial, as well as the chronostratigraphic tools available for direct correlation between sequences, with a focus on terrestrial archives. We then present a case study on the use of pollen biostratigraphy for correlating sequences in NW Europe, highlighting its strength as a local correlation tool, and the challenges this approach presents in comparing sequences to global records of climate and environmental change. A move towards consistently dated sequences will improve our understanding of environmental responses to Last Interglacial climate variability across different elements of the global climate system and the rates at which different elements of the climate system respond to changes in global temperatures.

Visible-Light Spectroscopy and Rock Magnetic Analyses of Iron Oxides in Mixed-Mineral Assemblages

Iron oxide assemblages are central to many pursuits, ranging from Mars exploration to environmental remediation. Oxides and oxyhydroxides of iron both carry the special properties of color and magnetism. In this paper, we use visible-light spectroscopy and rock magnetic data collected at varying temperatures (~77–973 K) to analyze the concentrations and identities of iron oxides found in natural hematite-dominated samples that were obtained from a scientific drill core of Late Triassic red beds in the American Southwest. Our results suggest that hematite colorization of Earth materials varies from red to blue/purple as crystal size increases. Second-derivative analysis of the collected visible-light spectra allows this variation to be measured through the characteristic wavelength band position. Magnetic coercivity data indicate “hardness” differences that also may suggest smaller grain sizes are associated with redder colors. Yellowish maghemite and goethite have overlapping characteristic wavelength band positions that make it challenging to distinguish their contributions to mixed assemblages from visible-light data alone. Remanent magnetizations acquired at ~77 K and room temperature suggest the presence of hematite and a low-coercivity phase that may be maghemite and/or oxidized magnetite. However, we interpret this phase as maghemite in order to explain the changes in iron oxide concentrations indicated by visible-light intensities near ~425 nm and because the thermal demagnetization data suggest that goethite is absent from the samples. Future research that increases the resolution of hematite, maghemite, and goethite detection in experimental and natural samples will provide opportunities to refine the study of past climates and constrain soil iron availability under future changes in global moisture and temperature. Multimethod datasets improve understanding of environmental conditions that cause iron oxides assemblages to shift in phase dominance, grain size, and crystallinity.

Impact of Temperature on the Growth Performance, Survival Rate, Osmoregulation, Dissolved Oxygen and Physiological Changes of Freshwater Tilapia (Oreochromis mossambicus)

For many aquatic species, any changes in water temperature affect their survival. This study was performed to investigate the effect of rising temperature on the growth parameters, protein content, dissolved oxygen content, moisture content osmoregulation, and physiological activity of freshwater Tilapia (Oreochromis mossambicus). The experiments were set in plastic fish tanks, the experimental tank placed in direct sunlight and the control tank in shade, and measuring temperature and pH daily, with proper aeration and feed was provided. The study found that increasing water temperature led to higher mortality rates and low survivability percentages in fish, with a higher growth rate in the experimental group with a pH range of 5.7 to 8.2. High dissolved oxygen levels were recorded during the experimental period, with a mean difference of 26.56 compared to the control group, possibly causing restless movement in fish. The study revealed that the alkalinity of water decreases with increasing temperature. The study found that increased salinity led to a significant increase in growth performance, indicating an increase in metabolic rate, and a decrease in alkaline nature. The difference between the mean protein value in the experimental and control groups is 0.896mg/ml. Thermal limitations may negatively impact O. mossambicus physiological responses, impacting aquaculture production due to predicted global climate change-induced water temperature changes.

Cloud Responses to Abrupt Solar and CO2 Forcing: 1. Temperature Mediated Cloud Feedbacks

AbstractThere are many uncertainties in future climate, including how the Earth may react to different types of radiative forcing, such as CO2, aerosols, and even geoengineered changes in the amount of sunlight absorbed by Earth's surface. Here, we analyze model simulations where the climate system is subjected to an abrupt change of the solar constant by ±4%, and where the atmospheric CO2 concentration is abruptly changed to quadruple and half its preindustrial value. Using these experiments, we examine how clouds respond to changes in solar forcing, compared to CO2, and feedback on global surface temperature. The total cloud response can be decomposed into those responses driven by changes in global surface temperature, called the temperature mediated cloud feedbacks, and responses driven directly by the forcing that are independent of the global surface temperature. In this paper, we study the temperature mediated cloud changes to answer two primary questions: (a) How do temperature mediated cloud feedbacks differ in response to abrupt changes in CO2 and solar forcing? And (b) Are there symmetrical (equal and opposite) temperature mediated cloud feedbacks during global warming and global cooling? We find that temperature mediated cloud feedbacks are similar in response to increasing solar and increasing CO2 forcing, and we provide a short review of recent literature regarding the physical mechanisms responsible for these feedbacks. We also find that cloud responses to warming and cooling are not symmetric, due largely to non‐linearity introduced by phase changes in mid‐to‐high latitude low clouds and sea ice loss/formation.

Climate Change Is Leading to a Convergence of Global Climate Distribution

AbstractThe impact of changes in global temperatures and precipitation on climate distribution remains unclear. Taking the annual global average temperatures and precipitation as the origin, this study determined the climate distribution with the distances of temperature and precipitation from their global averages as the X and Y axes. The results showed that during 1980–2019, the global temperature distribution converged toward the mean (convergence), while the precipitation distribution moved away from the mean (divergence). The combined effects of both led to a convergence in the global climate distribution. During 2025–2100, significant climate convergence is observed under two emission scenarios (SSP245 and SSP585). However, the climate convergence and the area of change in climate type remains insignificant only under SSP126, suggesting that the diversity of the global climate pattern can be maintained under a sustainable emission pathway (SSP126), whereas high emission pathways will lead to greater uniformity in global climate.

Factors determining tropical upper-level cloud radiative effect in the radiative-convective equilibrium framework

Investigation of the major factors determining tropical upper-level cloud radiative effect (TUCRE) is crucial for understanding cloud feedback mechanisms. We examined the TUCRE inferred from the outputs of historical runs and AMIP runs from CMIP6 models employing a radiative-convective equilibrium (RCE). In this study, we incorporated the RCE model configurations of atmospheric dynamics and thermodynamics from the climate models, while simplifying the intricate systems. Using the RCE model, we adjusted the global mean surface temperature to achieve energy balance, considering variations in tropical cloud fraction, regional reflectivity, and emission temperature corresponding to each climate model. Subsequently, TUCRE was calculated as a unit of K/%, representing the change in global mean surface temperature (K) in response to an increment in the tropical upper-level clouds (%). Our RCE model simulation indicates that the major factors determining the TUCRE are the emission temperatures of tropical moist-cloudy and moist-clear regions, as well as the fraction of tropical upper-level clouds. The higher determination coefficients between TUCRE and both the emission temperature of tropical moist regions and the upper-level cloud fraction are attributable to their contribution to the trapping effect on the outgoing longwave radiations, which predominantly determines TUCRE. Consequently, the results of this study underscore the importance of accurately representing the upper-level cloud fraction and emission temperature in tropical moist regions to enhance the representation of TUCRE in climate models.

Assessing the economic implications of carbon emissions on climate change: Estimating the impact using methane-adjusted DICE model

This study aims to highlight the importance of accurately estimating methane emissions, one of the most dangerous and important greenhouse gases in the context of climate change. By incorporating methane emissions as a variable within the integrated assessment model DICE (Dynamic Integrated Climate-Economy model), we investigate how these emissions influence temperature changes and subsequently impact economic policies, including climate economic policies, carbon pricing, and non-price factors. We use the existing DICE-2020 and DICE-2023 models as references for our analysis. In addition to industrial emissions that can be detected through satellite observations, we address the challenge of estimating natural emissions from wetlands and permafrost, which leak gradually and are difficult to detect. By considering these emissions, we account for their exogenous nature and their divergence from the current situation. Our study reveals that incorporating methane emissions into the DICE model has significant implications for global temperature outcomes and subsequent policy changes. We find that by implementing existing methane reduction policies, which includes cutting the level of methane emissions in half and increase the carbon price in 4 times to 500 USD per ton, it is possible to achieve the more ambitious goal of limiting the global temperature increase to 1.5 °C by 2100 in an optimistic scenario instead of the common target of 2 °C. More pessimistic scenarios that do not imply big change in methane emissions, but the same numerical data for carbon price, still suggests the possibility of keeping the global temperature below 2 °C. The findings of this study emphasize the importance of estimating methane emissions in efforts to mitigate climate change. Recognizing the impact of methane on global temperature change, policymakers can make informed decisions regarding economic policies, carbon pricing, to effectively address the challenges posed by climate change. This research contributes to the field by incorporating methane emissions into the DICE model, providing a more complete understanding of its influence on global climate outcomes and economic implications. Additionally, by highlighting the potential benefits of methane reduction measures, this study provides information on how to achieve more ambitious climate targets.

Impact of seasonal global land surface temperature (LST) change on gross primary production (GPP) in the early 21st century

Understanding the impact of global land surface temperature (LST) changes on gross primary production (GPP) is crucial for addressing global sustainability challenges effectively. This article explores the effects of winter and summer temperature variations on GPP from 2001 to 2020 on a global scale, employing a range of modeling techniques to investigate the complex relationship between temperature changes and GPP. The study employs various modeling approaches, including linear regression models, artificial neural networks, Random Forest (RF) models, and the XGBoost algorithm to examine both linear and non-linear relationships between global temperature changes and GPP. The results reveal that the RF and XGBoost models effectively capture the non-linear relationship between LST and GPP during both summer and winter, demonstrating a high level of statistical significance (P < 0.01) and achieving R2 values of 0.598. Furthermore, the study applies a Sen+MK trend analysis model to identify six distinct trend patterns in LST and GPP during both summer and winter seasons. In summer, the area exhibiting a non-significant increasing trend (NSI) for GPP covers 65,066,274.77 km2, whereas in winter, a strong significant decreasing trend (SSD) for GPP spans 64,537,108.31 km2. Notably, GPP patterns closely mirror those of LST, suggesting that rising high-temperature conditions during summer lead to reduced GPP, while increased low temperatures during winter promote GPP growth. Robust correlations between LST and GPP are observed under various trend conditions in both summer and winter, displaying strong statistical significance (P < 0.01), with SSD achieving a maximum R2 of 0.594. These findings contribute significantly to our comprehensive understanding of the dynamic relationship between LST and GPP and offer valuable insights for addressing the sustainable development of global climate change challenges.

Virtual Sensor for On-Line Hardness Assessment in TIG Welding of Inconel 600 Alloy Thin Plates.

Maintaining high-quality welded connections is crucial in many industries. One of the challenges is assessing the mechanical properties of a joint during its production phase. Currently, in industrial practice, this occurs through NDT (non-destructive testing) conducted after the production process. This article proposes the use of a virtual sensor, which, based on temperature distributions observed on the joint surface during the welding process, allows for the determination of hardness distribution across the cross-section of a joint. Welding trials were conducted with temperature recording, hardness measurements were taken, and then, neural networks with different hyperparameters were tested and evaluated. As a basis for developing a virtual sensor, LSTM networks were utilized, which can be applied to time series prediction, as in the analyzed case of hardness value sequences across the cross-section of a welded joint. Through the analysis of the obtained results, it was determined that the developed virtual sensor can be applied to predict global temperature changes in the weld area, in terms of both its value and geometry changes, with the mean average error being less than 20 HV (mean for model ~35 HV). However, in its current form, predicting local hardness disturbances resulting from process instabilities and defects is not feasible.

Understanding the complex dynamics of climate change in BRICS countries: Analyzing the COP26 and COP27 agendas

The urgency to address climate change becomes increasingly evident as we observe a rise in devastating natural disasters and significant changes in global temperatures. This comprehensive study critically assesses the adherence to climate targets set at COP26 and COP27, employing a dual approach encompassing theoretical and empirical aspects—basic and additional analysis. According to theoretical findings, China, Brazil, and South Africa are still experiencing an increase in climate change indicators despite their collective efforts. Notably, Brazil has shown limited progress in green financing initiatives. Moving to an empirical analysis covering 1995–2021, the study employs advanced econometric techniques, including panel ARDL, FMOLS, DOLS, CS-ARDL, and Grey forecasting models (GM (1,1) and DGM (1,1)). The past data on energy production using both renewable and non-renewable sources spanning from 2010 to 2021 to forecast energy production for the next 8 years, extending up to 2029. Results indicate that green financing, renewable energy consumption, natural resource rents, and government effectiveness significantly reduce GHG emissions. Conversely, economic growth, including its cubic form, exacerbates GHG emission trends. Moreover, the study validates the environmental N-shaped hypothesis in the examined countries, providing a complete understanding of climate change's intricate and multifaceted impacts. The grey forecasting model shows that Brazil, Russia, and South Africa are actively endeavoring to curb greenhouse gas emissions by transitioning toward renewable energy sources for energy production. This research contributes valuable insights for policymakers, emphasizing the importance of targeted interventions in green financing and sustainable practices to effectively address and mitigate climate change.

CROP IMPROVEMENT THROUGH DIFFERENT MEANS TO ADDRESS CLIMATE CHANGE AND FOOD SECURITY

This study evaluated several crop development techniques in addition to the effects of climate change on productivity in agriculture. Climate affects agricultural productivity and the distribution of crops worldwide. Given the current and projected variations in temperature, precipitation, and carbon dioxide concentrations, it is unclear whether agroecosystems will be able to produce enough food to meet the world's needs. Crop output, water productivity, and soil water balance are frequently altered by climate change. Soil moisture content and groundwater levels will be affected by the immediate effects of global warming-induced changes in temperature and precipitation patterns. Agricultural output is affected by several factors, such as crop variety, growing circumstances, soil deterioration, and water availability. Modern agricultural systems use genetics, biotechnology, plant breeding, environmental monitoring, and adjustments to management techniques to adapt to climate change. On the other hand, without a more thorough approach to agricultural systems, development cannot proceed. A strategy like this would mean growing amounts of a wider variety of superior crops and advancing equity, sustainability, nutrition, and food security in the future.

Historical and Future global warming under different RCP emission scenarios

Understanding the relationship between carbon emissions and climate change has become increasingly urgent amidst the universal endorsement of sustainable development and the establishment of net-zero carbon emission target (The Paris Agreement). In this study, model projections based on Coupled Model Intercomparison Project Phase 5 (CMIP5) are used to examine future climate change under different representative concentration pathway (RCP) emission scenarios till 2300. Besides analysis of future global average temperature change under the emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP 8.5, historical data is first collected during the past three decades (1990-2021). The results show that the simulated global warming ranges from 0.9 to 1.3 between 1990 and 2021, consistent with the observations (0.93). Carbon emissions in China arose mostly from manufacturing and construction, electricity and heat and transport. Emissions from electricity, heat and transport increase by a high ratio of 7.7 and 3.5 times due to industry development. Under different RCP scenarios, the global surface temperature anomaly will increase by 0.2-1.0, 1.2-2.0, 3.5-4.3 and 3.0-8.5 , respectively. The surface temperature anomaly values under RCP8.5 are much higher than those under other emission scenarios. Only in the RCP2.6 scenario (sustainability), the surface warming in all simulations stays below a 2 threshold at the end of the 21st century. To attain net zero emissions, it is highly demanded to develop strict emission policies, chart a course toward decarbonization, and institute effective measures aimed at realizing net zero emissions within the short to medium term. Concurrently striving for economic objectives, managing the equilibrium between economic growth and environmental sustainability emerges as a critical imperative.

Eocene Tectonic Uplifts Caused the Early Oligocene Intrusion of the Indian Monsoon Into the Tuotuohe Basin and the Increased Evaporation, Central‐Northern Tibet: Insights From the Oxygen Isotope Record

AbstractIt is not clear how the Asian monsoon evolved after leaving the spatial range of the Intertropical Convergence Zone in the Late Eocene and before the modern‐like Asian monsoon formed at ∼26 Ma. In this study, the results of a well‐dated, robust, and continuous paleoenvironmental carbonate oxygen isotope record from the Tuotuohe section in the Tuotuohe Basin on the central–northern Tibetan Plateau indicate that the carbonate oxygen isotope showed positive bias at 30.5 Ma. Evidence concerning the temperature, precipitation, paleolatitude, paleoelevation, salt mines and global temperature changes at this time suggest that the positive oxygen isotope shift was mainly due to a combination of the intrusion of the Indian monsoon into the basin and increased evaporation, both of which were ultimately induced by the tectonic uplift of the Tuotuohe Basin before 30.5 Ma and the retreat of the Paratethys Sea after the Eocene.

Stable isotope evidence for long-term stability of large-scale hydroclimate in the Neogene North American Great Plains

Abstract. The Great Plains of North America host a stark climatic gradient, separating the humid and well-watered eastern US from the semi-arid and arid western US, and this gradient shapes the region's water availability, its ecosystems, and its economies. This climatic boundary is largely set by the influence of two competing atmospheric circulation systems that meet over the Great Plains – the wintertime westerlies bring dominantly dry air that gives way to moist, southerly air transported by the Great Plains low-level jet in the warmer months. Climate model simulations suggest that, as CO2 rises, this low-level jet will strengthen, leading to greater precipitation in the spring but less in the summer and, thus, no change in mean annual precipitation. Combined with rising temperatures that will increase potential evapotranspiration, semi-arid conditions will shift eastward, with potentially large consequences for the ecosystems and inhabitants of the Great Plains. We examine how hydroclimate in the Great Plains varied in the past in response to warmer global climate by studying the paleoclimate record within the Ogallala Formation, which underlies nearly the entire Great Plains and provides a spatially resolved record of hydroclimate during the globally warmer late Miocene. We use the stable isotopes of oxygen (δ18O) as preserved in authigenic carbonates hosted within the abundant paleosol and fluvial successions that comprise the Ogallala Formation as a record of past hydroclimate. Today, and coincident with the modern aridity gradient, there is a sharp meteoric water δ18O gradient with high (−6 ‰ to 0 ‰) δ18O in the southern Great Plains and low (−12 ‰ to −18 ‰) δ18O in the northern plains. We find that the spatial pattern of reconstructed late Miocene precipitation δ18O is indistinguishable from the spatial pattern of modern meteoric water δ18O. We use a recently developed vapor transport model to demonstrate that this δ18O spatial pattern requires air mass mixing over the Great Plains between dry westerly and moist southerly air masses in the late Miocene – consistent with today. Our results suggest that the spatial extents of these two atmospheric circulation systems have been largely unchanged since the late Miocene and any strengthening of the Great Plains low-level jet in response to warming has been isotopically masked by proportional increases in westerly moisture delivery. Our results hold implications for the sensitivity of Great Plains climate to changes in global temperature and CO2 and also for our understanding of the processes that drove Ogallala Formation deposition in the late Miocene.

Projected Global Temperature Changes After Net Zero Are Small But Significant

AbstractAs more countries make net zero greenhouse gas emissions pledges, it is crucial to understand the effects on global climate after achieving net zero emissions. The climate has been found to continue to evolve even after the abrupt cessation of CO2 emissions, with some models simulating a small warming and others simulating a small cooling. In this study, we analyze if the temperature and precipitation changes post abrupt cessation of CO2 emissions are significantly different compared to natural climate variations. We find that the temperature changes are outside of natural variability for most models, whilst the precipitation changes are mostly non‐significant. We also demonstrate that post‐net zero temperature changes have implications for the remaining carbon budget. The possibility of further global warming post‐net zero adds to the evidence supporting more rapid emissions reductions in the near‐term.

Global-scale future climate projections from ACCESS model contributions to CMIP6

This paper describes projected climate evolution and outcomes simulated by the Australian Community Climate and Earth System Simulator (ACCESS) to varying future scenarios, including of socio-ecological and technological development, and land-use and land-cover change. Contributions to the Coupled Model Intercomparison Project Phase 6 (CMIP6) from the climate model version, ACCESS-CM2, and the fully coupled Earth System Model version, ACCESS-ESM1.5, are presented for the near-future (2020–2050), 21st Century (2000–2100) and longer-term (2100–2300). Scenario differentiation in the near future is aided by high-density sampling in large-ensemble ACCESS-ESM1.5, more clearly illustrating projected 2020–2050 global changes in temperature, precipitation and aerosol optical depth. Over the 21st Century, the heightened equilibrium climate sensitivity of ACCESS-CM2 relative to ACCESS-ESM1.5 results in persistently greater surface air temperature increases and larger amplified polar warming, leading to more rapid sea ice decline. Although weakening of the Atlantic meridional overturning circulation (AMOC) occurs in both models, 21st Century recovery under aggressive-mitigation and overshoot scenarios only occurs in ACCESS-ESM1.5; AMOC weakening continues under all scenarios in ACCESS-CM2 through to 2100. Longer-term climate response from simulations extending to 2300 depict opposing hemispheric responses of polar surface air temperatures and sea ice in both models under scenarios based on aggressive mitigation action, leading to a resurgence of surface ocean warming and Antarctic sea ice decline. Under a future scenario where development is driven by continued fossil fuel use, both AMOC and Antarctic Bottom Water Formation continue to weaken across 2200–2300 in both models, reaching such low levels in ACCESS-CM2 that these pivotal components of global meridional overturning circulation could be considered essentially to have ceased.