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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.

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.

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. Focusing on the role of external forcing, an investigation of the causes of observed changes in the tropical Pacific surface warming pattern over recent decades discusses a possible shift in the drivers of this 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. The asymmetry between El Niño and La Niña episodes in the tropical Pacific is often not well represented in models. Here, the authors show that this asymmetry is related to subsurface nonlinear dynamical heating and that a realistic representation of this process can potentially improve tropical climate projections.

According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe 1 – 4 . However, verifying this prediction using observations has remained a substantial challenge owing to large natural rainfall fluctuations at regional scales 3 , 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 simulations 6 . 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. Deep learning using a convolutional neural network trained with daily precipitation fields and annual global mean surface air temperature data demonstrates that anthropogenically induced climate change has a detectable effect on daily hydrological fluctuations.

Understanding the interaction between the tropical Pacific and Atlantic Oceans has challenged the climate community for decades. Typically, boreal summer Atlantic Niño events are followed by vigorous Pacific events of opposite sign around two seasons later. However, incorporating the equatorial Atlantic information to variabilities internal to the Pacific lends no significant additional predictive skill for the subsequent El Niño‐Southern Oscillation (ENSO). Here we resolve this conundrum in a physically consistent frame, in which the nascent onset of a Pacific event rapidly induces an opposite‐signed summer equatorial Atlantic event and the lead correlation of Atlantic over Pacific is a statistical artifact of ENSO's autocorrelation. This Pacific‐to‐Atlantic impact is limited to a short window around late spring due to seasonally‐amplified Atlantic atmosphere‐ocean coupling. This new frame reconciles the discrepancies between the observed and multi‐model simulated inter‐basin relationship, providing a major advance in understanding seasonally‐modulated inter‐basin climate connections as well as their predictability. Plain Language Summary Previous studies interpreted the observed lead/lag relationship between Atlantic Niño/Niña and Pacific Niño/Niña sea surface temperature anomalies as evidence for a precursory role of the equatorial Atlantic on the development of El Niño–Southern Oscillation (ENSO) events. This study clearly demonstrates that this statistical relationship is not related to Atlantic‐to‐Pacific causality, but can rather be explained by seasonally modulated equatorial Atlantic's response to ENSO. We find that Pacific ENSO events drive equatorial Atlantic events rather than vice versa, and reconcile the apparent discrepancies between the observed and multi‐model simulated tropical Pacific/Atlantic relationship. Key Points The lead correlation of the equatorial Atlantic over the Pacific is not related to Atlantic‐to‐Pacific causality The tropical Pacific/Atlantic interaction is consistent with the nascent onset of Pacific events driving the equatorial Atlantic events The discrepancies between the observed and multi‐model simulated tropical Pacific/Atlantic relationship can be reconciled in this new frame

While significant improvements have been made in understanding how the El Niño–Southern Oscillation (ENSO) impacts both North American and Asian climate, its relationship with the North Atlantic Oscillation (NAO) remains less clear. Observations indicate that ENSO exhibits a highly complex relationship with the NAO-associated atmospheric circulation. One critical contribution to this ambiguous ENSO/NAO relationship originates from ENSO’s diversity in its spatial structure. In general, both eastern (EP) and central Pacific (CP) El Niño events tend to be accompanied by a negative NAO-like atmospheric response. However, for two different types of La Niña the NAO response is almost opposite. Thus, the NAO responses for the CP ENSO are mostly linear, while nonlinear NAO responses dominate for the EP ENSO. These contrasting extra-tropical atmospheric responses are mainly attributed to nonlinear air-sea interactions in the tropical eastern Pacific. The local atmospheric response to the CP ENSO sea surface temperature (SST) anomalies is highly linear since the air-sea action center is located within the Pacific warm pool, characterized by relatively high climatological SSTs. In contrast, the EP ENSO SST anomalies are located in an area of relatively low climatological SSTs in the eastern equatorial Pacific. Here only sufficiently high positive SST anomalies during EP El Niño events are able to overcome the SST threshold for deep convection, while hardly any anomalous convection is associated with EP La Niña SSTs that are below this threshold. This ENSO/NAO relationship has important implications for NAO seasonal prediction and places a higher requirement on models in reproducing the full diversity of ENSO.

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. It has been suggested that sea surface temperatures in the North Tropical Atlantic exert strong influence on the evolution of the El Nino Southern Oscillation (ENSO). Here, the authors argue that observed statistics are fully consistent with ENSO driving climate variations in the Atlantic and not vice versa.

Climate variability has distinct spatial patterns with the strongest signal of sea surface temperature (SST) variance residing in the tropical Pacific. This interannual climate phenomenon, the El Niño-Southern Oscillation (ENSO), impacts weather patterns across the globe via atmospheric teleconnections. Pronounced SST variability, albeit of smaller amplitude, also exists in the other tropical basins as well as in the extratropical regions. To improve our physical understanding of internal climate variability across the global oceans, we here make the case for a conceptual model hierarchy that captures the essence of observed SST variability from subseasonal to decadal timescales. The building blocks consist of the classic stochastic climate model formulated by Klaus Hasselmann, a deterministic low-order model for ENSO variability, and the effect of the seasonal cycle on both of these models. This model hierarchy allows us to trace the impacts of seasonal processes on the statistics of observed and simulated climate variability. One of the important outcomes of ENSO’s interaction with the seasonal cycle is the generation of a frequency cascade leading to deterministic climate variability on a wide range of timescales, including the near-annual ENSO Combination Mode. Using the aforementioned building blocks, we arrive at a succinct conceptual model that delineates ENSO’s ubiquitous climate impacts and allows us to revisit ENSO’s observed statistical relationships with other coherent spatio-temporal patterns of climate variability—so called empirical modes of variability. We demonstrate the importance of correctly accounting for different seasonal phasing in the linear growth/damping rates of different climate phenomena, as well as the seasonal phasing of ENSO teleconnections and of atmospheric noise forcings. We discuss how previously some of ENSO’s relationships with other modes of variability have been misinterpreted due to non-intuitive seasonal cycle effects on both power spectra and lead/lag correlations. Furthermore, it is evident that ENSO’s impacts on climate variability outside the tropical Pacific are oftentimes larger than previously recognized and that accurately accounting for them has important implications. For instance, it has been shown that improved seasonal prediction skill can be achieved in the Indian Ocean by fully accounting for ENSO’s seasonally modulated and temporally integrated remote impacts. These results move us to refocus our attention to the tropical Pacific for understanding global patterns of climate variability and their predictability.

Nonlinear interactions between ENSO and the western Pacific warm pool annual cycle generate an atmospheric combination mode (C-mode) of wind variability. The authors demonstrate that C-mode dynamics are responsible for the development of an anomalous low-level northwest Pacific anticyclone (NWP-AC) during El Niño events. The NWP-AC is embedded in a large-scale meridionally antisymmetric Indo-Pacific atmospheric circulation response and has been shown to exhibit large impacts on precipitation in Asia. In contrast to previous studies, the authors find the role of air–sea coupling in the Indian Ocean and northwestern Pacific only of secondary importance for the NWP-AC genesis. Moreover, the NWP-AC is clearly marked in the frequency domain with near-annual combination tones, which have been overlooked in previous Indo-Pacific climate studies. Furthermore, the authors hypothesize a positive feedback loop involving the anomalous low-level NWP-AC through El Niño and C-mode interactions: the development of the NWP-AC as a result of the C-mode acts to rapidly terminate El Niño events. The subsequent phase shift from retreating El Niño conditions toward a developing La Niña phase terminates the low-level cyclonic circulation response in the central Pacific and thus indirectly enhances the NWP-AC and allows it to persist until boreal summer. Anomalous local circulation features in the Indo-Pacific (e.g., the NWP-AC) can be considered a superposition of the quasi-symmetric linear ENSO response and the meridionally antisymmetric annual cycle modulated ENSO response (C-mode). The authors emphasize that it is not adequate to assess ENSO impacts by considering only interannual time scales. C-mode dynamics are an essential (extended) part of ENSO and result in a wide range of deterministic high-frequency variability.