ABSTRACT
The deep ocean, a vast thermal reservoir, absorbs excess heat under greenhouse warming, which ultimately regulates the Earth's surface climate. Even if CO2 emissions are successfully reduced, the stored heat will gradually be released, resulting in a particular pattern of ocean warming. Here, we show that deep ocean warming will lead to El Niño-like ocean warming and resultant increased precipitation in the tropical eastern Pacific with southward shift of the intertropical convergence zone. Consequently, the El Niño-Southern Oscillation shifts eastward, intensifying Eastern Pacific El Niño events. In particular, the deep ocean warming could increase convective extreme El Niño events by 40 to 80% relative to the current climate. Our findings suggest that anthropogenic greenhouse warming will have a prolonged impact on El Niño variability through delayed deep ocean warming, even if CO2 stabilization is achieved.
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.
ABSTRACT
Over the past decade, an unexpected cooling trend has been observed in East Asia and North America during winter. Climate model simulations suggest that this pattern of stalled warming, besides accelerated warming, will repeat throughout the course of global warming, influenced by the natural decade-long variations in the climate system. However, understanding the exact factors affecting the pace of warming remains a challenge. Here we show that a pause in warming over continental areas-namely, local warming hiatus-can be accompanied by excessive heat accumulation north of the ocean fronts. This oceanic condition, often manifesting in the form of marine heatwaves, constrains the subseasonal growth of atmospheric planetary waves, significantly increasing the likelihood of cold extremes in downstream continents. Our results underscore the importance of closely monitoring changing ocean fronts in response to human-induced warming, which can potentially reshape the inherent decade-long fluctuations within regional climates over the long term.
ABSTRACT
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 (CO2) reduction based on the 28-member ensemble simulations of the CESM1.2 model under an idealized CO2 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 CO2 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.
ABSTRACT
A poleward shift of the Hadley cell (HC) edge in a warming climate, which contributes to the expansion of drought-prone subtropical regions, has been widely documented. The question addressed here is whether this shift is reversible with CO2 removal. By conducting large-ensemble experiments where CO2 concentrations are systematically increased and then decreased to the present-day level, we show that the poleward-shifted HC edge in a warming climate does not return to its present-day state when CO2 concentrations are reduced. While the Southern Hemisphere HC edge remains poleward of its present-day state, the Northern Hemisphere HC edge ends up farther equatorward of its present-day state. Such hemispherically asymmetric HC edge changes are closely associated with the changes in vertical wind shear in the subtropical atmosphere, which result from the long adjustment time of the ocean response to CO2 removal. Our findings suggest that CO2 removal may not guarantee the recovery of the subtropical dryness associated with the HC changes.
ABSTRACT
Convective extreme El Niño (CEE) events, characterized by strong convective events in the eastern Pacific, are known to have a direct link to anomalous climate conditions worldwide, and it has been reported that CEE will occur more frequently under greenhouse warming. Here, using a set of CO2 ramp-up and ramp-down ensemble experiments, we show that frequency and maximum intensity of CEE events increase further in the ramp-down period from the ramp-up period. These changes in CEE are associated with the southward shift of the intertropical convergence zone and intensified nonlinear rainfall response to sea surface temperature change in the ramp-down period. The increasing frequency of CEE has substantial impacts on regional abnormal events and contributed considerably to regional mean climate changes to the CO2 forcings.
ABSTRACT
Understanding the regional hydrological response to varying CO2 concentration is critical for cost-benefit analysis of mitigation and adaptation polices in the near future. To characterize summer monsoon rainfall change in East Asia in a changing CO2 pathway, we used the Community Earth System Model (CESM) with 28 ensemble members in which the CO2 concentration increases at a rate of 1% per year until its quadrupling peak, i.e., 1468 ppm (ramp-up period), followed by a decrease of 1% per year until the present-day climate conditions, i.e., 367 ppm (ramp-down period). Although the CO2 concentration change is symmetric in time, the amount of summer rainfall anomaly in East Asia is increased 42% during a ramp-down period than that during a ramp-up period when the two periods of the same CO2 concentration are compared. This asymmetrical rainfall response is mainly due to an enhanced El Niño-like warming pattern as well as its associated increase in the sea surface temperature in the western North Pacific during a ramp-down period. These sea surface temperature patterns enhance the atmospheric teleconnections and the local meridional circulations around East Asia, resulting in more rainfall over East Asia during a ramp-down period. This result implies that the removal of CO2 does not guarantee the return of regional rainfall to the previous climate state with the same CO2 concentration.
Subject(s)
Carbon Dioxide , El Nino-Southern Oscillation , Seasons , Asia, Eastern , TemperatureABSTRACT
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.
Subject(s)
El Nino-Southern OscillationABSTRACT
In 2016, the westerly quasi-biennial oscillation (WQBO) in the equatorial stratosphere was unprecedentedly disrupted by westward forcing near 40 hPa; this was followed by another disruption in 2020. Strong extratropical Rossby waves propagating toward the tropics were considered the main cause of the disruptions, but why the zonal wind is reversed only in the middle of the WQBO remains unclear. Here, we show that strong westerly winds in the equatorial lower stratosphere (70 to 100 hPa) help to disrupt the WQBO by hindering the wind reversal at its base. They also help equatorial westward waves propagate further upward, increasing the negative forcing at around 40 hPa that drives the QBO disruptions. Tropical westerly winds have been increasing in the past and are projected to increase in a warmer climate. These background wind changes may allow more frequent QBO disruptions in the future, leading to less predictability in atmospheric weather and climate systems.
ABSTRACT
To investigate the response of the general circulation and global transport of heat through both atmosphere and ocean to two-types of carbon dioxide removal scenario, we performed an earth system model experiment in which we imposed a pulse-type quadrupling of CO2 forcing for 50 years and a gradual peak-and-decline of four-time CO2 forcing. We found that the results from two experiments are qualitatively similar to each other. During the forcing-on period, a dominant warming in the upper troposphere over the tropics and on the surface at high latitudes led to a slowdown in the Hadley circulation, but the poleward atmospheric energy transport was enhanced due to an increase in specific humidity. This counteracted the reduction in poleward oceanic energy transport owing to the suppression of the meridional overturning circulation in both Hemispheres. After returning the original CO2 level, the hemispheric thermal contrast was reversed, causing a southward shift of the intertropical convergence zone. To reduce the hemispheric thermal contrast, the northward energy transports in the atmosphere and ocean surface were enhanced while further weakening of the global-scale Atlantic meridional overturning circulation led to southward energy transport in the deep ocean.
ABSTRACT
Over the past half a century, both the Indian Ocean (IO) and the North Atlantic Ocean (NA) exhibit strong warming trends like a global mean surface temperature (SST). Here, we show that not only simply as a result of increased greenhouse gases, but the IO-NA interaction through atmospheric teleconnection boosts up their warming trends. Climate model simulations demonstrate that the IO warming increases the NA SST by enhancing the longwave radiation through atmospheric teleconnection, subsequently, the warmer NA SST-induced atmospheric teleconnection leads to IO warming by reducing evaporative cooling with weakened surface winds. This two-way interaction (i.e., IO-NA warming chain) acts as positive feedback that reinforces warming over both ocean basins. The Pacific Ocean is partly involved in this warming chain as a modulator in an interdecadal timescale. These results highlight the importance of understanding ocean-basin interactions that may provide a more accurate future projection of warming.
ABSTRACT
Model simulations of El Niño-Southern Oscillation (ENSO) are usually evaluated by comparing them to observations using a multitude of metrics. However, this approach cannot provide an objective summary metric of model performance. Here, we propose that such an objective model evaluation should involve comparing the full joint probability density functions (pdf's) of ENSO. For simplicity, ENSO state is defined here as sea surface temperature anomalies over the Niño 3 region and equatorial Pacific thermocline depth anomalies. We argue that all ENSO metrics are a function of the joint pdf, the latter fully specifying the underlying stochastic process. Unfortunately, there is a lack of methods to recover the joint ENSO pdf from climate models or observations. Here, we develop a data-driven stochastic model for ENSO that allows for an analytic solution of the non-Markov non-Gaussian cyclostationary ENSO pdf. We show that the model can explain relevant ENSO features found in the observations and can serve as an ENSO simulator. We demonstrate that the model can reasonably approximate ENSO in most GCMs and is useful at exploring the internal ENSO variability. The general approach is not limited to ENSO and could be applied to other cyclostationary processes.
ABSTRACT
El Niño profoundly impacts precipitation in high-population regions. This demands an advanced understanding of the changes in El Niño-induced precipitation under the future global warming scenario. However, thus far, consensus is lacking regarding future changes in mid-latitude precipitation influenced by El Niño. Here, by analyzing the Coupled Model Intercomparison Project simulations, we show that future precipitation changes are tightly linked to the response of each type of El Niño to the tropical Pacific mean sea surface temperature (SST) change. A La Niña-like mean SST change intensifies basin-wide El Niño events causing approximately 20% more precipitation over East Asia and North America via enhancing moisture transport. Meanwhile, an El Niño-like mean SST change generates more frequent eastern Pacific El Niño events, enhancing precipitation in North American. Our findings highlight the importance of the mean SST projection in selectively influencing the types of El Niño and their remote impact on precipitation.
ABSTRACT
Stochastic differential equations (SDEs) are ubiquitous across disciplines, and uncovering SDEs driving observed time series data is a key scientific challenge. Most previous work on this topic has relied on restrictive assumptions, undermining the generality of these approaches. We present a novel technique to uncover driving probabilistic models that is based on kernel density estimation. The approach relies on few assumptions, does not restrict underlying functional forms, and can be used even on non-Markov systems. When applied to El Niño-Southern Oscillation (ENSO), the fitted empirical model simulations can almost perfectly capture key time series properties of ENSO. This confirms that ENSO could be represented as a two-variable stochastic dynamical system. Our experiments provide insights into ENSO dynamics and suggest that state-dependent noise does not play a major role in ENSO skewness. Our method is general and can be used across disciplines for inverse and forward modeling, to shed light on structure of system dynamics and noise, to evaluate system predictability, and to generate synthetic datasets with realistic properties.
ABSTRACT
Characteristics of sea ice extent (SIE) have been rapidly changing in the Pacific Arctic sector (PAS) in recent years. The SIE variability in PAS during the late spring and early summer (i.e., April-May-June, AMJ) plays a key role in determining the SIE during the following fall when SIE is at a minimum. We find that the Pacific Decadal Oscillation (PDO), which is the most dominant variability of sea surface temperature (SST) on the low-frequency timescales, differently influences the SIE in PAS during AMJ before and after the mid-1990s. While a positive phase of PDO during the previous winter acts to increases SIE during AMJ before the mid-1990s, it acts to decrease SIE during AMJ after the mid-1990s. Further analysis indicates that atmospheric circulation associated with PDO differently influences the variability of SIE in the PAS during AMJ by modulating poleward moisture transport across the Alaska or the Far East Asia peninsula. This results in the change in the relationship of PDO and SIE in the PAS before and after the mid-1990s.
ABSTRACT
The asymmetric nature of the El Niño-Southern Oscillation (ENSO) is explored by using a probabilistic model (PROM) for ENSO. Based on a Fokker-Planck Equation (FPE), PROM describes the dynamics of a nonlinear stochastic ENSO recharge oscillator model for eastern equatorial Pacific temperature anomalies and equatorial Pacific basin-averaged thermocline depth changes. Eigen analyses of PROM provide new insights into the stationary and oscillatory solutions of the stochastic dynamical system. The first probabilistic eigenmode represents a stationary mode, which exhibits the asymmetric features of ENSO, in case deterministic nonlinearities or multiplicative noises are included. The second mode is linked to the oscillatory nature of ENSO and represents a cyclic asymmetric probability distribution, which emerges from the key dynamical processes. Other eigenmodes are associated with the temporal evolution of higher order statistical moments of the ENSO system. The model solutions demonstrate that the deterministic nonlinearity plays a stronger role in establishing the observed asymmetry of ENSO as compared to the multiplicative stochastic part.
ABSTRACT
Recent Antarctic surface climate change has been characterized by greater warming trends in West Antarctica than in East Antarctica. Although this asymmetric feature is well recognized, its origin remains poorly understood. Here, by analyzing observation data and multimodel results, we show that a west-east asymmetric internal mode amplified in austral winter originates from the harmony of the atmosphere-ocean coupled feedback off West Antarctica and the Antarctic terrain. The warmer ocean temperature over the West Antarctic sector has positive feedback, with an anomalous upper-tropospheric anticyclonic circulation response centered over West Antarctica, in which the strength of the feedback is controlled by the Antarctic topographic layout and the annual cycle. The current west-east asymmetry of Antarctic surface climate change is undoubtedly of natural origin because no external factors (e.g., orbital or anthropogenic factors) contribute to the asymmetric mode.
ABSTRACT
Observational analysis shows that there is a predominant global-scale multidecadal variability (GMV) of sea-surface temperature (SST). Its horizontal pattern resembles that of the interdecadal Pacific oscillation (IPO) in the Pacific and the Atlantic multidecadal oscillation (AMO) in the Atlantic Ocean, which could affect global precipitation and temperature over the globe. Here, we demonstrate that the GMV could be driven by the AMO through atmospheric teleconnections and atmosphere-ocean coupling processes. Observations reveal a strong negative correlation when AMO leads GMV by approximately 4-8 years. Pacemaker experiments using a climate model driven by observed AMO signals reveal that the tropical Atlantic warm SST anomalies of AMO initiate anomalous cooling in the equatorial central-eastern Pacific through atmospheric teleconnections. Anticyclonic anomalies in the North and South Pacific induce equatorward winds along the coasts of North and South America, contributing to further cooling. The upper-ocean dynamics plays a minor role in GMV formation but contributes to a delayed response of the IPO to the AMO forcing. The possible impact of the GMV on AMO was also tested by prescribing only Pacific SST in the model; however, the model could not reproduce the observed phase relationship between the AMO and the GMV. These results support the hypothesis that the Atlantic Ocean plays a key role in the multidecadal variability of global SST.
ABSTRACT
We present a novel quasi-Bayesian method to weight multiple dynamical models by their skill at capturing both potentially non-linear trends and first-order autocorrelated variability of the underlying process, and to make weighted probabilistic projections. We validate the method using a suite of one-at-a-time cross-validation experiments involving Atlantic meridional overturning circulation (AMOC), its temperature-based index, as well as Korean summer mean maximum temperature. In these experiments the method tends to exhibit superior skill over a trend-only Bayesian model averaging weighting method in terms of weight assignment and probabilistic forecasts. Specifically, mean credible interval width, and mean absolute error of the projections tend to improve. We apply the method to a problem of projecting summer mean maximum temperature change over Korea by the end of the 21st century using a multi-model ensemble. Compared to the trend-only method, the new method appreciably sharpens the probability distribution function (pdf) and increases future most likely, median, and mean warming in Korea. The method is flexible, with a potential to improve forecasts in geosciences and other fields.
Subject(s)
Climate Change , Climate , Computer Simulation , Water Movements , Algorithms , Bayes Theorem , Calibration , Forecasting , Nonlinear Dynamics , Oceans and Seas , Probability , Programming Languages , Reproducibility of Results , Republic of Korea , Seasons , Software , Stochastic Processes , TemperatureABSTRACT
In this Review, the middle initial of author Kim M. Cobb was omitted. The original Review has been corrected online.