A past 3-million-year transient simulation with Community Earth System Model version 1.2 reveals precessional dominance in El Ni & ntilde;o-Southern Oscillation (ENSO) variability intensity and spatial structure. Under boreal winter-solstice perihelion (like late Holocene), basin-scale ENSO variability intensifies through strengthened thermocline and zonal advective feedbacks, driven by a broad El Ni & ntilde;o-like mean surface warming and enhanced tropical Pacific rainbands. Under boreal vernal-equinox perihelion, central-Pacific ENSO variability shifts eastward moderately, primarily due to intensified zonal advective feedback, following a strengthened background South Pacific Convergence Zone (SPCZ) and interhemispherically opposing rainband changes. ENSO responses under boreal summer-solstice and autumn-equinox perihelion are contrastingly weaker. Consequently, both ENSO characteristics coevolve with the precession's magnitude set by orbital eccentricity. Precessional modulation of ENSO progressively strengthened toward the present, mediated by a gradually intensified background SPCZ under greenhouse gas and ice-sheet forcings. We suggest that sea surface warming patterns and associated tropical rainbands are paramount in past ENSO changes.

Abstract We use perfect‐model, large‐ensemble nonlinear Recharge Oscillator (RO) simulations to quantify ENSO internal variability and the detectability of forced changes in ENSO characteristics. Fixed‐parameter simulations show that linear trends in ENSO standard deviation, period, and skewness as large as those observed since 1955 can arise from internal variability in 10% of simulations. RO parameters estimated from single realizations exhibit spurious drifts even without forcing, underscoring the need for ensembles. Using 100‐member ensembles, comparable to the largest climate‐model ensembles, we identify detectable parameter trends. For ENSO amplitude, detectability thresholds for forced changes in underlying processes are 15% per century for stochastic forcing, 25% per century for basin adjustment, and 50% per century for the Bjerknes feedback. For ENSO period, the detectability threshold for forced changes in the underlying recharge–discharge processes and delayed oceanic feedback is 15% per century. These results provide a testbed for interpreting RO‐diagnosed ENSO changes in climate‐model ensembles.

The response of global dryness and vegetation to CO2 removal experiments, especially for net- negative emission is immature. Here we conducted a thorough investigation to identify hysteresis and reversibility in global dryness, as well as the vegetation productivity’s response to dry and wet episodes, considering their asymmetrical nature. The asymmetry index (AI) includes two important aspects such as positive AI indicates a dominant increase of vegetation productivity during wet episodes compared to the decline in dry episodes and negative AI implies a larger reduction of productivity in dry years compared to an increase in wet years. Aggregate results from various drought indices and vegetation productivity reveal a dominant dryness in the CO2 decrease phase. Global dryness shows strong hysteresis and irreversible behavior over half of the global land with significant regional disparity. Irreversible changes in dryness are concentrated in specific areas, i.e., hotspots, covering over 14% of the global land, particularly pronounced in Northern Africa, Southwest Russia, and Central America. Moreover, a wider spread of negative asymmetry indicates a significant decrease in vegetation productivity caused by dryness. Importantly, the potential evapotranspiration is projected to be the primary driver of global dryness as well as vegetation asymmetry. Our findings suggest only CO2 alleviation is not enough to cope with drought rather implementing advanced water management strategies is a must to mitigate the impact of drought effectively.

The Indian Ocean Dipole exhibits large variations in its evolution depending on the presence of El Ni & ntilde;o, with notable changes in intensity, duration, and peak phase. Here, using a simple Indian Ocean Dipole model and observational-reanalysis datasets, we revealed that Indian Ocean Dipole events co-evolving with El Ni & ntilde;o exhibit an early-summer growth-disruption, which results from a sudden decrease in Indian Ocean Dipole sensitivity to El Ni & ntilde;o in May and June, despite the steadily increasing El Ni & ntilde;o's amplitude. In May and June, as the Intertropical Convergence Zone migrates northward with the onset of South Asian monsoon, El Ni & ntilde;o-induced low-level cyclonic circulation causes Ekman upwelling over the western Indian Ocean, which stalls Indian Ocean Dipole development. Moist linear baroclinic model experiments verified that the Intertropical Convergence Zone modulates El Ni & ntilde;o-Southern Oscillation's impact on Indian Ocean Dipole seasonally. This study underscores the importance of understanding sub-seasonal dynamics of Indian Ocean Dipole evolution.

Drought is expected to intensify with rising CO _2 , but its behavior under CO _2 mitigation, remains uncertain. The response of the climate system to CO _2 variation exhibits hysteresis and irreversibility, highlighting the difficulty of recovery and the potential for long-lasting impacts. We investigated the hysteresis and reversibility of global drought and the associated underlying drivers. The Community Earth System Model 2 was used to simulate CO _2 changes: linear increases, decreases (i.e. net negative), and restoration to the initial level. This paper incorporates three well-established indices based on atmospheric, meteorological and soil moisture data to reflect drought. Here, we show that drought is dominant during the CO _2 decrease phase, leading to strong hysteresis with irreversible behavior over more than half of the global land cover. The robust irreversible changes in drought are concentrated in specific areas, i.e. hotspots, covering over 11% of the global land and are particularly pronounced in Northern Africa, Southwest Russia, and Central America. A decrease in precipitation drives drought during the CO _2 increase phase, while an enhanced vapor pressure deficit (VPD) exacerbates it during the CO _2 decrease phase. This increased VPD exacerbates drought hysteresis by raising potential evapotranspiration. Our findings suggest that only CO _2 reduction is not enough to effectively mitigate drought impacts, rather advanced water management strategies are essential.

Global warming is expected to be able to trigger abrupt transitions in various components of the climate system. Most studies focus on abrupt changes in the mean state of the system, while transitions in climate variability are less well understood. Here, we use multimodel simulations to show that sea-ice loss in the Arctic can trigger a critical transition in internal variability that leads to the emergence of a new climate oscillation in the Arctic Ocean. The intensified air-sea interaction due to sea-ice melt causes an oscillatory behaviour of surface temperatures on a multidecadal timescale. Our results suggest that a new mode of internal variability will emerge in the Arctic Ocean when sea ice declines below a critical threshold. Abrupt transitions in the climate system are discussed mostly in terms of mean state changes. Here, the authors use simulations to show that a decline in Arctic sea ice can lead to a new multidecadal mode of surface temperatures in the Arctic Ocean.

A novel type of climate oscillation might emerge in the Arctic Ocean owing to sea-ice melting. The air-sea coupling feedbacks occurring in the ice-free Arctic Ocean would trigger periodic warm-cold temperature oscillations, similar to El Ni & ntilde;o and La Ni & ntilde;a in the tropical Pacific Ocean.

El Ni & ntilde;o-Southern Oscillation-induced tropical Pacific precipitation anomalies have global impacts and will intensify under greenhouse warming, but the potential for mitigating these changes is less understood. Here, we identify distinct hysteresis features in the precipitation-sea surface temperature sensitivity between strong El Ni & ntilde;o and La Ni & ntilde;a phases using a large ensemble carbon removal numerical simulation. The strong El Ni & ntilde;o precipitation sensitivity exhibits a century-scale hysteretic enhancement and eastward shift, mainly due to modulated deep convection anomalies by the Intertropical Convergence Zone via cloud-longwave feedback. Instead, the strong La Ni & ntilde;a counterpart is concentrated toward the equator, mostly in the central-western Pacific, with a shorter hysteresis period of a few decades. This primarily involves changes in shallow convection and surface thermal structures during La Ni & ntilde;a, shaped by global warming-induced upper-ocean circulation changes. The distinct climate change regimes of strong El Ni & ntilde;o and La Ni & ntilde;a precipitation sensitivity hold important implications for assessing mitigation consequences.

Spatial climate analogs effectively illustrate how a location’s climate may become more similar to that of other locations from the historical period to future projections. Also, novel climates (emerging climate conditions significantly different from the past) have been analyzed as they may result in significant and unprecedented ecological and socioeconomic impacts. This study analyzes historical to future spatial climate analogs across East Asia and Europe, in the context of climatic impacts on ecology and human health, respectively. Firstly, the results of climate analogs analysis for ecological impacts indicate that major cities in East Asia and Europe have generally experienced novel climates and climate shifts originating from southern/warmer regions from the early 20th century to the current period, primarily attributed to extensive warming. In future projections, individual cities are not expected to experience additional significant climate change under a 1.5 °C global warming (warming relative to pre-industrial period), compared to the contemporary climate. In contrast, robust local climate change and climate shifts from southern/warmer regions are expected at 2.0 °C and 3.0 °C global warming levels. Specially, under the 3.0 °C global warming, unprecedented (newly emerging) climate analogs are expected to appear in a few major cities. The climate analog of future projections partially align with growing season length projections, demonstrating important implications on ecosystems. Human health-relevant climate analogs exhibit qualitatively similar results from the historical period to future projections, suggesting an increasing risk of climate-driven impacts on human health. However, distinctions emerge in the specifics of the climate analogs analysis results concerning ecology and human health, emphasizing the importance of considering appropriate climate variables corresponding to the impacts of climate change. Our results of climate analogs present extensive information of climate change signals and spatiotemporal trajectories, which provide important indicators for developing appropriate adaptaion plans as the planet warms.

This study investigates the mechanism of the hysteresis of European summer mean precipitation in a CO _2 removal (CDR) simulation. The European summer mean precipitation exhibits robust hysteresis in response to the CO _2 forcing; after decreasing substantially (∼40%) during the ramp-up period, it shows delayed recovery during the ramp-down period. We found that the precipitation hysteresis over Europe is tied to the hysteresis in the Atlantic Meridional Overturning Circulation (AMOC). During the ramp-down period, an anomalous high surface pressure circulation prevails over Europe. The anomalous high pressure system is a baroclinic response of the atmosphere to strong North Atlantic cooling associated with a weakened AMOC. This anomalous circulation suppresses summertime convective activity over the entire Europe by decreasing near-surface moist enthalpy in Central and Northern Europe while increasing lower free-tropospheric temperature in Southern Europe. Our findings underscore the need to understand complex interactions in the Earth system for reliable future projections of regional precipitation change under CDR scenarios.

The El Niño-Southern Oscillation (ENSO), the strongest interannual climate signal, has a large influence on remote sea surface temperature (SST) anomalies in all three basins. However, a missing map piece in the widespread ENSO teleconnection is the Equatorial Atlantic, where the ENSO footprint on local SST is less clear. Here, using reanalysis data and partially coupled pacemaker experiments, we show that the tropical Pacific SST anomalies, manifested as a Central Pacific (CP) ENSO-like structure, synchronize the tropical South Atlantic (40°W-10°E, 15°S-0°) SST anomalies over the last seven decades, but on a quasi-decadal (8-16 year) timescale. Such a decadal connection is most evident during the boreal spring-summer season, when the CP ENSO-like decadal SST anomalies induce a cooling of the South Atlantic SSTs through atmospheric teleconnections involving both Southern Hemisphere extratropical Rossby waves and equatorial Kelvin waves. The resulting subtropical South Atlantic low-level anticyclonic circulation and easterlies at its northern flank cause local ocean-atmosphere feedback and strengthen the Pacific-to-Atlantic teleconnections. In contrast, the concurrent tropospheric temperature teleconnection is less destructive to the above Atlantic SST response due to the weaker and more west decadal Pacific SST anomalies compared to the interannual ENSO counterpart. Pacific-driven coupled simulations reproduce key observational features fairly well, while parallel Atlantic-driven simulations show little forcing into the Pacific. Our results show that the tropical Central Pacific is an important source of decadal predictability for the tropical South Atlantic SST and the surrounding climate.

Abstract The Indian Ocean Dipole (IOD) is a major climate variability mode that substantially influences weather extremes and climate patterns worldwide. However, the response of IOD variability to anthropogenic global warming remains highly uncertain. The latest IPCC Sixth Assessment Report concluded that human influences on IOD variability are not robustly detected in observations and twenty-first century climate-model projections. Here, using millennial-length climate simulations, we disentangle forced response and internal variability in IOD change and show that greenhouse warming robustly suppresses IOD variability. On a century time scale, internal variability overwhelms the forced change in IOD, leading to a widespread response in IOD variability. This masking effect is mainly caused by a remote influence of the El Niño–Southern Oscillation. However, on a millennial time scale, nearly all climate models show a long-term weakening trend in IOD variability by greenhouse warming. Our results provide compelling evidence for a human influence on the IOD.

Understanding of extreme precipitation change in response to CO2 forcing and associated socioeconomic exposure is limited. In this study, a comprehensive analysis is conducted to explore the response of global extreme precipitation to CO2 forcing in terms of hysteresis and reversibility effect and associated population exposure. In this regard, climate outputs under two idealized CO2 scenarios such as ramp-up (RU; about +1% annually until quadrupling of present level) and ramp-down (RD; around −1% annually set back to present level) from Community Earth System Model version 1.2, and the projected population data from the five shared Socioeconomic Pathways (SSPs) are used. Extreme precipitation events are evaluated using the number of heavy precipitation days (R30 mm), maximum consecutive 5-day precipitation (Rx5day), and the precipitation of very wet days (R95pTOT) indices. Results show that the magnitude of extreme precipitation change and associated population exposure is higher in the CO2 reduction period (RD) than in RU. All the indices show substantial irreversible and hysteresis effects, ∼69% of the global land is expected to experience irreversible changes in extreme precipitation. Further, the hotspots of irreversibility (the region with irreversible change and a large hysteresis) will emerge in >20% of the global area. Spatially, strong hysteresis and irreversibility are particularly concentrated over global land monsoon regions. The leading exposure is estimated under SSP3 combined with both RU and RD periods. Under the SSP3-RD combination, the highest population exposure is estimated at ∼67.1% (globally averaged), and ∼72% (averaged over hotspots) higher than that of the present day. The exposed population is prominent in South Africa and Asia. Notably, the population change effect is the principal factor in global exposure change, while it is the climate change effect over the hotspots of irreversibility. These findings provide new insight into policymaking that only CO2 mitigation effort is not enough to cope with extreme precipitation, rather advanced adaptation planning is a must to have more socio-economic benefits.

Extreme precipitation intensification due to global warming has received significant attention; however, large uncertainties remain regarding how much it will change in the future, even under a given greenhouse gas emissions pathway. Our constraining analysis provides smaller future extreme precipitation intensification with reduced uncertainties than raw/unconstrained model simulation projections from the global to continental scales and also several sub-continental areas. Historical warming trends in climate model simulations present strong positive inter-model correlations with future annual maximum daily precipitation intensification from the global to continental scales. This emergent relationship is employed for constraining analysis. The proposed emergent constraints are mostly associated with thermodynamics (atmospheric moisture changes), with limited contribution from dynamics (atmospheric circulation variations). This constraining framework has various advantages, including lower observation uncertainty, and more robust theoretical interpretation than previously suggested constraints for extreme precipitation frequency projections. CMIP6 models generally overestimate historically observed warming, which resultantly generates weaker extreme precipitation intensification following constraining analysis than unconstrained model simulation projections from the global to individual continents, and even several mid- and high-latitude sub-continental areas. Additionally, constrained projections exhibit narrower uncertainty ranges in future extreme precipitation projections. During the late 21st century (2070–2099), under the high-emission scenario (Shared Socioeconomic Pathway 5–8.5, characterized by fossil fueled development and a radiative forcing of 8.5 W m−2 in 2100), our results present reduced global average intensity and uncertainty for future annual maximum daily precipitation intensification by 25% and 27%, respectively.

El Niño–Southern Oscillation (ENSO) is the strongest interannual climate variability with far-reaching socioeconomic consequences. Many studies have investigated ENSO-projected changes under future greenhouse warming, but its responses to plausible mitigation behaviors remain unknown. We show that ENSO sea surface temperature (SST) variability and associated global teleconnection patterns exhibit strong hysteretic responses to carbon dioxide (CO 2 ) reduction based on the 28-member ensemble simulations of the CESM1.2 model under an idealized CO 2 ramp-up and ramp-down scenario. There is a substantial increase in the ensemble-averaged eastern Pacific SST anomaly variance during the ramp-down period compared to the ramp-up period. Such ENSO hysteresis is mainly attributed to the hysteretic response of the tropical Pacific Intertropical Convergence Zone meridional position to CO 2 removal and is further supported by several selected single-member Coupled Model Intercomparison Project Phase 6 (CMIP6) model simulations. The presence of ENSO hysteresis leads to its amplified and prolonged impact in a warming climate, depending on the details of future mitigation pathways.

Indian Ocean Dipole phenomenon (IOD) refers to a dominant zonal contrast pattern of sea surface temperature anomaly (SSTA) over tropical Indian Ocean (TIO) on interannual time scales. Its positive phase, characterized by anomalously warm western TIO and anomalously cold southeastern TIO, is usually stronger than its negative phase, namely a positively skewed IOD. Here, we investigate causes for the IOD asymmetry using a prototype IOD model, of which physical processes include both linear and nonlinear feedback processes, El Nino's asymmetric impact, and a state-dependent noise. Parameters for the model were empirically obtained using various reanalysis SST data sets. The results reveal that the leading cause of IOD asymmetry without accounting seasonality is a local nonlinear process, and secondly the state-dependent noise, the direct effect by the positively skewed ENSO and its nonlinear teleconnection; the latter two have almost equal contribution. However, the contributions by each process are season dependent. For boreal summer, both local nonlinear feedback process and the state-dependent noise are major drivers of IOD asymmetry with negligible contribution from ENSO. The ENSO impacts become important in boreal fall, along with the other two processes.

El Niño-Southern Oscillation (ENSO) sea surface temperature (SST) anomaly skewness encapsulates the nonlinear processes of strong ENSO events and affects future climate projections. Yet, its response to CO 2 forcing remains not well understood. Here, we find ENSO skewness hysteresis in a large ensemble CO 2 removal simulation. The positive SST skewness in the central-to-eastern tropical Pacific gradually weakens (most pronounced near the dateline) in response to increasing CO 2 , but weakens even further once CO 2 is ramped down. Further analyses reveal that hysteresis of the Intertropical Convergence Zone migration leads to more active and farther eastward-located strong eastern Pacific El Niño events, thus decreasing central Pacific ENSO skewness by reducing the amplitude of the central Pacific positive SST anomalies and increasing the scaling effect of the eastern Pacific skewness denominator, i.e., ENSO intensity, respectively. The reduction of eastern Pacific El Niño maximum intensity, which is constrained by the SST zonal gradient of the projected background El Niño-like warming pattern, also contributes to a reduction of eastern Pacific SST skewness around the CO 2 peak phase. This study highlights the divergent responses of different strong El Niño regimes in response to climate change.

The Indian Ocean Dipole/Zonal mode (IOD) is an interannual phenomenon over the tropical Indian Ocean, causing a pronounced impact worldwide. Here, we investigate the mechanism of the change in IOD characteristics in a CO 2 removal simulation for an earth system model (ESM). As the CO 2 concentration increases, the intensity of IOD tends to increase, but at high CO 2 concentrations, further increases decrease the IOD intensity. The minimum IOD amplitude was recorded during the early decrease in CO 2 . First, we developed a conceptual model for IOD that is composed of local air-sea coupled feedback, delayed ocean dynamics, El Niño impact, and noise forcing. Then, by adopting ESM results into this simple IOD model, we revealed that the local air–sea coupled feedback is a major factor for changing IOD amplitude, while El Niño does not exert a change in IOD amplitude. The local air–sea coupled feedback including thermocline feedback, wind-evaporation feedback, and Ekman feedback is strongly modified by the air–sea coupling strength during progression of a global warming. Consequently, under the higher CO 2 concentrations, IOD amplitude is reduced due to the weakening of air-sea coupling over tropical Indian Ocean.

The El Niño – Southern Oscillation (ENSO) is a dominant mode of global climate variability. Nevertheless, future multi-model probabilistic projections of ENSO properties have not yet been made. Main roadblocks that have been hindering making these projections are climate model dependence and difficulty in quantifying historical model performance. Dependence is broadly defined as similarity between climate model output, assumptions, or physical parameterizations. Here, we propose a unifying metric of relative model performance, based on the probability density function (PDF) of ENSO paths. This metric is applied to assess the overall skill of Climate Model Intercomparison Project phase 6 (CMIP6) climate models at capturing ENSO. We then perform future multi-model probabilistic projections of changes in ENSO properties (from years 1850–1949 to 2040–2099) under the shared socioeconomic pathway scenario SSP585, accounting for model skill and dependence. We find that future ENSO will likely be more seasonally locked (89% chance), and have a longer period (67% chance). Yet, the jury is still out on future ENSO amplification. Our method reduces uncertainty by up to 37% compared to a simple approach ignoring model dependence and skill.