Possible shift in controls of the tropical Pacific surface warming pattern.

Changes in the sea surface temperature (SST) pattern in the tropical Pacific modulate radiative feedbacks to greenhouse gas forcing, the pace of global warming and regional climate impacts. Therefore, elucidating the drivers of the pattern is critically important for reducing uncertainties in future projections. However, the causes of observed changes over recent decades, an enhancement of the zonal SST contrast coupled with a strengthening of the Walker circulation, are still debated. Here we focus on the role of external forcing and review existing mechanisms of the forced response categorized as either an energy perspective that adopts global and hemispheric energy budget constraints or a dynamical perspective that examines the atmosphere-ocean coupled processes. We then discuss their collective and relative contributions to the past and future SST pattern changes and propose a narrative that reconciles them. Although definitive evidence is not yet available, our assessment suggests that the zonal SST contrast has been dominated by strengthening mechanisms in the past, but will shift towards being dominated by weakening mechanisms in the future. Finally, we present opportunities to resolve the model-observations discrepancy regarding the recent trends.

Explainable El Niño predictability from climate mode interactions.

The El Niño-Southern Oscillation (ENSO) provides most of the global seasonal climate forecast skill1-3, yet, quantifying the sources of skilful predictions is a long-standing challenge4-7. Different sources of predictability affect ENSO evolution, leading to distinct global effects. Artificial intelligence forecasts offer promising advancements but linking their skill to specific physical processes is not yet possible8-10, limiting our understanding of the dynamics underpinning the advancements. Here we show that an extended nonlinear recharge oscillator (XRO) model shows skilful ENSO forecasts at lead times up to 16-18 months, better than global climate models and comparable to the most skilful artificial intelligence forecasts. The XRO parsimoniously incorporates the core ENSO dynamics and ENSO's seasonally modulated interactions with other modes of variability in the global oceans. The intrinsic enhancement of ENSO's long-range forecast skill is traceable to the initial conditions of other climate modes by means of their memory and interactions with ENSO and is quantifiable in terms of these modes' contributions to ENSO amplitude. Reforecasts using the XRO trained on climate model output show that reduced biases in both model ENSO dynamics and in climate mode interactions can lead to more skilful ENSO forecasts. The XRO framework's holistic treatment of ENSO's global multi-timescale interactions highlights promising targets for improving ENSO simulations and forecasts.

Anthropogenic fingerprints in daily precipitation revealed by deep learning.

According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe1-4. However, verifying this prediction using observations has remained a substantial challenge owing to large natural rainfall fluctuations at regional scales3,4. Here we show that deep learning successfully detects the emerging climate-change signals in daily precipitation fields during the observed record. We trained a convolutional neural network (CNN)5 with daily precipitation fields and annual global mean surface air temperature data obtained from an ensemble of present-day and future climate-model simulations6. After applying the algorithm to the observational record, we found that the daily precipitation data represented an excellent predictor for the observed planetary warming, as they showed a clear deviation from natural variability since the mid-2010s. Furthermore, we analysed the deep-learning model with an explainable framework and observed that the precipitation variability of the weather timescale (period less than 10 days) over the tropical eastern Pacific and mid-latitude storm-track regions was most sensitive to anthropogenic warming. Our results highlight that, although the long-term shifts in annual mean precipitation remain indiscernible from the natural background variability, the impact of global warming on daily hydrological fluctuations has already emerged.

Sea-surface temperature pattern effects have slowed global warming and biased warming-based constraints on climate sensitivity.

The observed rate of global warming since the 1970s has been proposed as a strong constraint on equilibrium climate sensitivity (ECS) and transient climate response (TCR)-key metrics of the global climate response to greenhouse-gas forcing. Using CMIP5/6 models, we show that the inter-model relationship between warming and these climate sensitivity metrics (the basis for the constraint) arises from a similarity in transient and equilibrium warming patterns within the models, producing an effective climate sensitivity (EffCS) governing recent warming that is comparable to the value of ECS governing long-term warming under CO[Formula: see text] forcing. However, CMIP5/6 historical simulations do not reproduce observed warming patterns. When driven by observed patterns, even high ECS models produce low EffCS values consistent with the observed global warming rate. The inability of CMIP5/6 models to reproduce observed warming patterns thus results in a bias in the modeled relationship between recent global warming and climate sensitivity. Correcting for this bias means that observed warming is consistent with wide ranges of ECS and TCR extending to higher values than previously recognized. These findings are corroborated by energy balance model simulations and coupled model (CESM1-CAM5) simulations that better replicate observed patterns via tropospheric wind nudging or Antarctic meltwater fluxes. Because CMIP5/6 models fail to simulate observed warming patterns, proposed warming-based constraints on ECS, TCR, and projected global warming are biased low. The results reinforce recent findings that the unique pattern of observed warming has slowed global-mean warming over recent decades and that how the pattern will evolve in the future represents a major source of uncertainty in climate projections.

Author Correction: El Niño-Southern Oscillation complexity.

In this Review, the middle initial of author Kim M. Cobb was omitted. The original Review has been corrected online.

El Niño-Southern Oscillation complexity.

El Niño events are characterized by surface warming of the tropical Pacific Ocean and weakening of equatorial trade winds that occur every few years. Such conditions are accompanied by changes in atmospheric and oceanic circulation, affecting global climate, marine and terrestrial ecosystems, fisheries and human activities. The alternation of warm El Niño and cold La Niña conditions, referred to as the El Niño-Southern Oscillation (ENSO), represents the strongest year-to-year fluctuation of the global climate system. Here we provide a synopsis of our current understanding of the spatio-temporal complexity of this important climate mode and its influence on the Earth system.

El Niño-Southern Oscillation frequency cascade.

The El Niño-Southern Oscillation (ENSO) phenomenon, the most pronounced feature of internally generated climate variability, occurs on interannual timescales and impacts the global climate system through an interaction with the annual cycle. The tight coupling between ENSO and the annual cycle is particularly pronounced over the tropical Western Pacific. Here we show that this nonlinear interaction results in a frequency cascade in the atmospheric circulation, which is characterized by deterministic high-frequency variability on near-annual and subannual timescales. Through climate model experiments and observational analysis, it is documented that a substantial fraction of the anomalous Northwest Pacific anticyclone variability, which is the main atmospheric link between ENSO and the East Asian Monsoon system, can be explained by these interactions and is thus deterministic and potentially predictable.

Hysteresis of the El Niño-Southern Oscillation to CO2 forcing.

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.

Distinct impacts of major El Niño events on Arctic temperatures due to differences in eastern tropical Pacific sea surface temperatures.

The El Niño Southern Oscillation (ENSO) is a climate mode in the tropical Pacific. The ENSO teleconnections are known to affect Arctic temperature; however, the robustness of this relationship remains debated. We find that Arctic surface temperatures during three major El Niño events are remarkably well simulated by a state-of-the-art model when nudged to the observed pantropical sea surface temperatures (SSTs). SST perturbation experiments show that the 1982-1983 warm pan-Arctic and the 1997-1998 cold pan-Arctic during winter can be explained by far eastern equatorial Pacific SSTs being higher during 1997-1998 than 1982-1983. Consistently, during the 2017-2018 La Niña, unusually low SSTs in the same region contributed to pan-Arctic warming. These pan-Arctic responses to the SSTs are realized through latent heating anomalies over the western and eastern tropical Pacific. These results highlight the importance of accurately representing SST amplitude and pattern for Arctic climate predictions.

Spurious North Tropical Atlantic precursors to El Niño.

The El Niño-Southern Oscillation (ENSO), the primary driver of year-to-year global climate variability, is known to influence the North Tropical Atlantic (NTA) sea surface temperature (SST), especially during boreal spring season. Focusing on statistical lead-lag relationships, previous studies have proposed that interannual NTA SST variability can also feed back on ENSO in a predictable manner. However, these studies did not properly account for ENSO's autocorrelation and the fact that the SST in the Atlantic and Pacific, as well as their interaction are seasonally modulated. This can lead to misinterpretations of causality and the spurious identification of Atlantic precursors for ENSO. Revisiting this issue under consideration of seasonality, time-varying ENSO frequency, and greenhouse warming, we demonstrate that the cross-correlation characteristics between NTA SST and ENSO, are consistent with a one-way Pacific to Atlantic forcing, even though the interpretation of lead-lag relationships may suggest otherwise.

Tropical Indo-Pacific SST influences on vegetation variability in eastern Africa.

Mechanisms by which tropical Pacific and Indian Ocean sea surface temperatures (SST) influence vegetation in eastern Africa have not been fully explored. Here, we use a suite of idealized Earth system model simulations to elucidate the governing processes for eastern African interannual vegetation changes. Our analysis focuses on Tanzania. In the absence of ENSO-induced sea surface temperature anomalies in the Tropical Indian Ocean (TIO), El Niño causes during its peak phase negative precipitation anomalies over Tanzania due to a weakening of the tropical-wide Walker circulation and anomalous descending motion over the Indian Ocean and southeastern Africa. Resulting drought conditions increase the occurrence of wildfires, which leads to a marked decrease in vegetation cover. Subsequent wetter La Niña conditions in boreal winter reverse the phase in vegetation anomalies, causing a gradual 1-year-long recovery phase. The 2-year-long vegetation decline in Tanzania during an ENSO cycle can be explained as a double-integration of the local rainfall anomalies, which originate from the seasonally-modulated ENSO Pacific-SST forcing (Combination mode). In the presence of interannual TIO SST forcing, the southeast African precipitation and vegetation responses to ENSO are muted due to Indian Ocean warming and the resulting anomalous upward motion in the atmosphere.

Dynamics for El Niño-La Niña asymmetry constrain equatorial-Pacific warming pattern.

The El Niño-Southern Oscillation (ENSO) results from the instability of and also modulates the strength of the tropical-Pacific cold tongue. While climate models reproduce observed ENSO amplitude relatively well, the majority still simulates its asymmetry between warm (El Niño) and cold (La Niña) phases very poorly. The causes of this major deficiency and consequences thereof are so far not well understood. Analysing both reanalyses and climate models, we here show that simulated ENSO asymmetry is largely proportional to subsurface nonlinear dynamical heating (NDH) along the equatorial Pacific thermocline. Most climate models suffer from too-weak NDH and too-weak linear dynamical ocean-atmosphere coupling. Nevertheless, a sizeable subset (about 1/3) having relatively realistic NDH shows that El Niño-likeness of the equatorial-Pacific warming pattern is linearly related to ENSO amplitude change in response to greenhouse warming. Therefore, better simulating the dynamics of ENSO asymmetry potentially reduces uncertainty in future projections.

Publisher Correction: Dynamics for El Niño-La Niña asymmetry constrain equatorial-Pacific warming pattern.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Reduced tropical cyclone densities and ocean effects due to anthropogenic greenhouse warming.

Tropical cyclones (TCs) are extreme storms that form over warm tropical oceans. Along their tracks, TCs mix up cold water, which can further affect their intensity. Because of the adoption of lower-resolution ocean models, previous modeling studies on the TC response to greenhouse warming underestimated such oceanic feedbacks. To address the robustness of TC projections in the presence of mesoscale air-sea interactions and complex coastal topography, we conduct greenhouse warming experiments using an ultrahigh-resolution Earth System Model. We find that a projected weakening of the rising branches of the summer Hadley cells suppresses future TC genesis and TC-generated ocean cooling. The forced response is similar to recent observational trends, indicating a possible emergence of the anthropogenic signal beyond natural variability levels. In the greenhouse warming simulations, landfalling TCs intensify, both in terms of wind speed and associated rainfall. Our modeling results provide relevant information for climate change adaptation efforts.

Walker circulation response to extratropical radiative forcing.

Walker circulation variability and associated zonal shifts in the heating of the tropical atmosphere have far-reaching global impacts well into high latitudes. Yet the reversed high latitude-to-Walker circulation teleconnection is not fully understood. Here, we reveal the dynamical pathways of this teleconnection across different components of the climate system using a hierarchy of climate model simulations. In the fully coupled system with ocean circulation adjustments, the Walker circulation strengthens in response to extratropical radiative cooling of either hemisphere, associated with the upwelling of colder subsurface water in the eastern equatorial Pacific. By contrast, in the absence of ocean circulation adjustments, the Walker circulation response is sensitive to the forcing hemisphere, due to the blocking effect of the northward-displaced climatological intertropical convergence zone and shortwave cloud radiative effects. Our study implies that energy biases in the extratropics can cause pronounced changes of tropical climate patterns.

Pantropical climate interactions.

The El Niño-Southern Oscillation (ENSO), which originates in the Pacific, is the strongest and most well-known mode of tropical climate variability. Its reach is global, and it can force climate variations of the tropical Atlantic and Indian Oceans by perturbing the global atmospheric circulation. Less appreciated is how the tropical Atlantic and Indian Oceans affect the Pacific. Especially noteworthy is the multidecadal Atlantic warming that began in the late 1990s, because recent research suggests that it has influenced Indo-Pacific climate, the character of the ENSO cycle, and the hiatus in global surface warming. Discovery of these pantropical interactions provides a pathway forward for improving predictions of climate variability in the current climate and for refining projections of future climate under different anthropogenic forcing scenarios.

Revisiting the Pacific Meridional Mode.

Numerous studies demonstrated that the Pacific Meridional Mode (PMM) can excite Central Pacific (CP) El Niño-Southern Oscillation (ENSO) events and that the PMM is mostly a stochastic phenomenon associated with mid-latitude atmospheric variability and wind-evaporation-SST feedback. Here we show that CP sea surface temperature (SST) variability exhibits high instantaneous correlations both on interannual (ENSO-related) and decadal (Pacific Decadal Oscillation (PDO)-related) timescales with the PMM. By prescribing an idealized interannual equatorial CP ENSO SST forcing in a partially-coupled atmosphere/slab ocean model we are able to generate a realistic instantaneous PMM response consistent with the observed statistical ENSO/PMM relationship. This means that CP ENSO and the PMM can excite each other respectively on interannual timescales, strongly suggesting that a fast positive feedback exists between the two phenomena. Thus, we argue that they cannot be considered two independent dynamical entities. Additionally, we show that the interannual CP ENSO SST forcing generates atmospheric circulation variability that projects strongly on the Aleutian Low and North Pacific SST anomalies that exhibit the characteristic PDO pattern.

Climate variability impacts on rice production in the Philippines.

Changes in crop yield and production over time are driven by a combination of genetics, agronomics, and climate. Disentangling the role of these various influences helps us understand the capacity of agriculture to adapt to change. Here we explore the impact of climate variability on rice yield and production in the Philippines from 1987-2016 in both irrigated and rainfed production systems at various scales. Over this period, rice production is affected by variations in soil moisture, which are largely driven by the El Niño-Southern Oscillation (ENSO). We found that the climate impacts on rice production are strongly seasonally modulated and differ considerably by region. As expected, rainfed upland rice production systems are more sensitive to soil moisture variability than irrigated paddy rice. About 10% of the variance in rice production anomalies on the national level co-varies with soil moisture changes, which in turn are strongly negatively correlated with an index capturing ENSO variability. Our results show that while temperature variability is of limited importance in the Philippines today, future climate projections suggest that by the end of the century, temperatures might regularly exceed known limits to rice production if warming continues unabated. Therefore, skillful seasonal prediction will likely become increasingly crucial to provide the necessary information to guide agriculture management to mitigate the compounding impacts of soil moisture variability and temperature stress. Detailed case studies like this complement global yield studies and provide important local perspectives that can help in food policy decisions.

Strong sub-seasonal wintertime cooling over East Asia and Northern Europe associated with super El Niño events.

East Asia experienced a record-breaking cold event during the 2015/16 boreal winter, with pronounced impacts on livelihood in the region. We find that this large-scale cold spell can be attributed to the concurrent super El Niño event in the tropical Pacific. Our analysis reveals that all super El Niño winters (1982/83, 1997/98, and 2015/16) were accompanied by a rapid sub-seasonal North Atlantic Oscillation (NAO)/Arctic Oscillation (AO) phase reversal from a positive to a negative state during early January, which was largely caused by the interaction of these super El Niño events with the subtropical jet annual cycle. The NAO/AO phase transition leads to a rapidly strengthened Siberian High, which favors southward intrusions of cold air to East Asia and thus causes severe local cooling. Similar cold spells can also be detected over Northern Europe associated with the fast sub-seasonal NAO/AO phase reversal. Due to the weaker amplitude of the ENSO forcing, these sub-seasonal atmospheric responses cannot be detected for moderate El Niño events. The super El Niño associated sub-seasonal signal of the East Asian and Northern Europe wintertime temperature responses carries important implications for future predictability of regional extreme events.