The El Niño‐Southern Oscillation (ENSO) is a coupled ocean‐atmosphere phenomenon of variability that is a leading source of seasonal climate prediction skill across the globe. The first ENSO prediction was made in the mid‐1970s, but it was another 10–15 years before operational centers, using simple, coupled climate models, began to make routine ENSO predictions. These early forecast models were succeeded in the 1990s by more sophisticated dynamical and statistical models, which created the basis for real‐time seasonal outlooks over the globe. These models, and more recent multimodel ensembles, also inform our understanding and estimates of the predictability and prediction skill of ENSO, which varies seasonally and from decade to decade. ENSO predictability largely stems from slowly evolving oceanic conditions, with short‐term atmospheric fluctuations often limiting predictability on seasonal timescales. Despite improved models and better initializations, prediction skill remains low for forecasts passing through the boreal spring, the so‐called spring prediction barrier. Furthermore, prediction skill and predictability have varied significantly over the past couple decades. Higher skill and predictability are evident during periods of larger amplitude ENSO events (e.g., Eastern Pacific El Niño), whereas lower skill/predictability is associated with lower amplitude events (e.g., Central Pacific El Niño). These natural variations in our ability to predict ENSO, together with challenges during 2014–2016, motivate the search for understanding of how anthropogenic warming will influence seasonal ENSO prediction.

Climate-driven redistribution of tuna threatens to disrupt the economies of Pacific Small Island Developing States (SIDS) and sustainable management of the world’s largest tuna fishery. Here we show that by 2050, under a high greenhouse gas emissions scenario (RCP 8.5), the total biomass of three tuna species in the waters of ten Pacific SIDS could decline by an average of 13% (range = −5% to −20%) due to a greater proportion of fish occurring in the high seas. The potential implications for Pacific Island economies in 2050 include an average decline in purse-seine catch of 20% (range = −10% to −30%), an average annual loss in regional tuna-fishing access fees of US$90 million (range = −US$40 million to –US$140 million) and reductions in government revenue of up to 13% (range = −8% to −17%) for individual Pacific SIDS. Redistribution of tuna under a lower-emissions scenario (RCP 4.5) is projected to reduce the purse-seine catch from the waters of Pacific SIDS by an average of only 3% (range = −12% to +9%), indicating that even greater reductions in greenhouse gas emissions, in line with the Paris Agreement, would provide a pathway to sustainability for tuna-dependent Pacific Island economies. An additional pathway involves Pacific SIDS negotiating within the regional fisheries management organization to maintain the present-day benefits they receive from tuna, regardless of the effects of climate change on the distribution of the fish.

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.

Correction to: Nature Sustainability. Published online 29 July 2021. In the version of this article originally published, there was an error in Supplementary Figure 15 where the current x-axis labels for Skipjack percentage of biomass change were also applied for the Yellowfin and Bigeye graphs; x-axis labels are now revised for all graphs in the online version of the article.