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The El Niño–Southern Oscillation (ENSO) provides most of the global seasonal climate forecast skill, yet, quantifying the sources of skilful predictions is a long-standing challenge. 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 possible, 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. 

Tropical Cyclones (TCs) are devastating natural disasters. Analyzing four decades of global TC data, here we find that among all global TC-active basins, the South China Sea (SCS) stands out as particularly difficult ocean for TCs to intensify, despite favorable atmosphere and ocean conditions. Over the SCS, TC intensification rate and its probability for a rapid intensification (intensification by ≥ 15.4 m s⁻¹day⁻¹) are only 1/2 and 1/3, respectively, of those for the rest of the world ocean. Originating from complex interplays between astronomic tides and the SCS topography, gigantic ocean internal tides interact with TC-generated oceanic near-inertial waves and induce a strong ocean cooling effect, suppressing the TC intensification. Inclusion of this interaction between internal tides and TC in operational weather prediction systems is expected to improve forecast of TC intensity in the SCS and in other regions where strong internal tides are present.

 

Abstract Marine heatwaves (MHWs), episodic periods of abnormally high sea surface temperature, severely affect marine ecosystems. Large marine ecosystems (LMEs) cover ~22% of the global ocean but account for 95% of global fisheries catches. Yet how climate change affects MHWs over LMEs remains unknown because such LMEs are confined to the coast where low-resolution climate models are known to have biases. Here, using a high-resolution Earth system model and applying a ‘future threshold’ that considers MHWs as anomalous warming above the long-term mean warming of sea surface temperatures, we find that future intensity and annual days of MHWs over the majority of the LMEs remain higher than in the present-day climate. Better resolution of ocean mesoscale eddies enables simulation of more realistic MHWs than low-resolution models. These increases in MHWs under global warming pose a serious threat to LMEs, even if resident organisms could adapt fully to the long-term mean warming. 

El Niño’s intensity change under anthropogenic warming is of great importance to society, yet current climate models’ projections remain largely uncertain. The current classification of El Niño does not distinguish the strong from the moderate El Niño events, making it difficult to project future change of El Niño’s intensity. Here we classify 33 El Niño events from 1901 to 2017 by cluster analysis of the onset and amplification processes, and the resultant 4 types of El Niño distinguish the strong from the moderate events and the onset from successive events. The 3 categories of El Niño onset exhibit distinct development mechanisms. We find El Niño onset regime has changed from eastern Pacific origin to western Pacific origin with more frequent occurrence of extreme events since the 1970s. This regime change is hypothesized to arise from a background warming in the western Pacific and the associated increased zonal and vertical sea-surface temperature (SST) gradients in the equatorial central Pacific, which reveals a controlling factor that could lead to increased extreme El Niño events in the future. The Coupled Model Intercomparison Project phase 5 (CMIP5) models’ projections demonstrate that both the frequency and intensity of the strong El Niño events will increase significantly if the projected central Pacific zonal SST gradients become enhanced. If the currently observed background changes continue under future anthropogenic forcing, more frequent strong El Niño events are anticipated. The models’ uncertainty in the projected equatorial zonal SST gradients, however, remains a major roadblock for faithful prediction of El Niño’s future changes. 

Decadal climate variability and change affects nearly every aspect of our world, including weather, agriculture, ecosystems, and the economy. Predicting its expression is thus of critical importance on multiple fronts. Poweret al. review what is known about tropical Pacific decadal climate variability and change, the degree to which it can be simulated and predicted, and how we might improve our understanding of it. More accurate projections will require longer and more detailed instrumental and paleoclimate records, improved climate models, and better data assimilation methods. —HJS