Jacob L. Gunnarson

El Niño–Southern Oscillation (ENSO) is a dominant driver of seasonal–interannual climate variability and has been linked to record-setting extremes such as marine heat waves (MHWs). However, quantifying the effects of ENSO on MHW characteristics remains a challenge due to data limitations. Here, we used an ensemble of tropical Pacific “pacemaker” simulations with a fully coupled Earth system model as a testbed for assessing the skill of four empirical methods aimed at isolating ENSO’s contribution to monthly SST anomalies including MHW extremes. We then applied the most skillful method to the observational record to determine ENSO’s impact on the spatial coverage, intensity, and duration of MHWs since 1960 (after removing the background warming trend). We found that El Niño of 2023–24 contributed to about half of the global coverage of record-setting MHWs, with the tropical Indian and tropical Atlantic Oceans being most clearly impacted. Our results shed light on the critical role ENSO plays in driving the most severe MHW conditions in the historical record. Significance Statement: In 2023 and early 2024, global surface ocean temperatures reached a record-breaking peak, resulting in marine heat waves that covered large areas of the global ocean. They coincided with an El Niño event, leading us to investigate the degree to which El Niño events drive global marine heat waves. To separate out El Niño’s contribution to these heat waves, we compared the effectiveness of several methods at removing the influence of El Niño from ocean surface temperature data. Using the best of these methods, we found that the 2023–24 El Niño was responsible for about half of the spatial coverage of the concurrent marine heat waves, with the remainder due to unrelated climate variability.

Marine heatwaves are periods of extreme sea surface temperatures (SSTs) which can have serious ecological and socioeconomic impacts. From a shifting baseline perspective, future changes to marine heatwaves statistics are almost entirely a result of changes to SST variance. The projected changes to SST variance in the future climate are spatially heterogeneous, with some areas experiencing less variance in the future, and others increased variance in the current generation of climate models. Moreover, the pattern of SST variance change differs between climate models. To determine the physical mechanisms behind these changes, we used a local linear stochastic-deterministic conceptual model to attribute the projected SST variance change in the extratropics to three drivers: ocean memory, El Niño-Southern Oscillation (ENSO) teleconnections, and stochastic noise forcing. We found that climate models generally agree that ocean memory will decline, resulting in decreased SST variance. Models also generally agree that the variance of the noise forcing will increase, resulting in enhanced SST variance. Changes to the ENSO teleconnection differ greatly between models, likely as a result of the substantially different future changes to ENSO in different models.

Under anthropogenic warming, future changes to climate variability beyond specific modes such as the El Niño-Southern Oscillation (ENSO) have not been well-characterized. In the Community Earth System Model version 2 Large Ensemble (CESM2-LE) climate model, the future change to sea surface temperature (SST) variability (and correspondingly marine heatwave intensity) on monthly timescales and longer is spatially heterogeneous. We examined these projected changes (between 1960–2000 and 2060–2100) in the North Pacific using a local linear stochastic-deterministic model, which allowed us to quantify the effect of changes to three drivers on SST variability: ocean “memory” (the SST damping timescale), ENSO teleconnections, and stochastic noise forcing. The ocean memory declines in most areas, but lengthens in the central North Pacific. This change is primarily due to changes in air-sea feedbacks and ocean damping, with the shallowing mixed layer depth playing a secondary role. An eastward shift of the ENSO teleconnection pattern is primarily responsible for the pattern of SST variance change.

Global climate models provide useful tools to forecast large‐scale anthropogenic trends and the impacts on ocean physics and marine biology and chemistry. Due to coarse spatial resolution, they typically lack the ability to represent important regional processes while underestimating mesoscale variability and vertical mixing. This means they provide limited value when it comes to regional climate projections. We developed a regional submesoscale‐permitting physical/biogeochemical model to dynamically downscale the output of a CMIP6 Earth System Model for three different Socioeconomic Pathways for the main Hawaiian Islands. We describe the methodology for downscaling the CMIP6 ocean physics and biogeochemistry along with atmospheric conditions in order to offline nest a regional model. We expect the large‐scale spatial and temporal features of the global model to be retained by the regional model, while adding representation of the regional processes that are crucial to understanding climate change on a local scale. We compare the regional model representation against both observed data and a regional reanalysis over the first two decades of the century. We show that the regional model maintains the large‐scale trends and interannual variability provided by the CMIP6 model while well‐representing the regional dynamics that drive the short‐term variability. To better illustrate the benefit of the downscaling, we present preliminary analysis of the downscaled results to examine climate impacts on the island corals that are not resolved by the global models. This analysis reveals that coastal corals are likely to experience unprecedented ocean acidification and substantial warming over the course of the century.

Under anthropogenic warming, future changes to climate variability beyond specific modes such as the El Niño-Southern Oscillation (ENSO) have not been well-characterized. In the Community Earth System Model version 2 Large Ensemble (CESM2-LE) climate model, the future change to sea surface temperature (SST) variability (and correspondingly marine heatwave intensity) is spatially heterogeneous. We examined these projected changes (between 1960-2000 and 2060-2100) in the North Pacific using a local linear stochastic-deterministic model, which allowed us to quantify the effect of changes to three drivers on SST variability: ocean "memory" (the SST damping timescale), ENSO teleconnections, and stochastic noise forcing. The ocean memory declines in most areas, but lengthens in the central North Pacific. This change is primarily due to changes in air-sea feedbacks and ocean damping, with the shallowing mixed layer depth playing a secondary role. An eastward shift of the ENSO teleconnection pattern is primarily responsible for the pattern of SST variance change.

Under anthropogenic warming, future changes to climate variability beyond specific modes such as the El Niño-Southern Oscillation (ENSO) have not been well-characterized. In the Community Earth System Model version 2 Large Ensemble (CESM2-LE) climate model, the future change to sea surface temperature (SST) variability is spatially heterogeneous. We examined these projected changes (between 1960-2000 and 2060-2100) in the North Pacific using a local linear stochastic-deterministic model, which allowed us to quantify the effect of changes to three drivers on SST variability: ocean “memory” (the SST damping timescale), ENSO teleconnections, and stochastic noise forcing. The ocean memory declines in most areas, but lengthens in the central North Pacific. This change is primarily due to changes in air-sea feedbacks and ocean damping, with the shallowing mixed layer depth playing a secondary role. An eastward shift of the ENSO teleconnection pattern is primarily responsible for the pattern of SST variance change.

Using images from the Cassini spacecraft, we analyzed three ribbon waves in Saturn's 42°N eastward jet at 45°N, 42°N, and 39°N planetocentric latitudes. In this report, we demonstrate that the morphology, wavelength, and propagation of the ribbon waves are consistent with barotropic Rossby waves with a smaller baroclinic component. We report on the appearance and disappearance of these waves during Cassini's mission. We suggest that the temporal evolution of these waves are related to the great Saturn storm of 2010–2011.