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.

The Recharge Oscillator (RO) is a simple mathematical model of the El Niño Southern Oscillation (ENSO). In its original form, it is based on two ordinary differential equations that describe the evolution of equatorial Pacific sea surface temperature and oceanic heat content. These equations make use of physical principles that operate in nature: (i) the air-sea interaction loop known as the Bjerknes feedback, (ii) a delayed oceanic feedback arising from the slow oceanic response to near-equatorial winds, (iii) state-dependent stochastic forcing from intraseasonal wind variations known as westerly wind bursts (WWBs), and (iv) nonlinearities such as those related to deep atmospheric convection and oceanic advection. These elements can be combined in different levels of RO complexity. The RO reproduces ENSO key properties in observations and climate models: its amplitude, dominant timescale, seasonality, and warm/cold phases amplitude asymmetry. We discuss the RO in the context of timely research questions. First, the RO can be extended to account for ENSO pattern diversity (with events that either peak in the central or eastern Pacific). Second, the core RO hypothesis that ENSO is governed by tropical Pacific dynamics is discussed from the perspective of influences from other basins. Finally, we discuss the RO relevance for studying ENSO response to climate change, and underline that accounting for ENSO diversity, nonlinearities, and better links of RO parameters to the long term mean state are important research avenues. We end by proposing important RO-based research problems.

Recent marine heatwaves in the Gulf of Alaska have had devastating and lasting impacts on species from various trophic levels. As a result of climate change, total heat exposure in the upper ocean has become longer, more intense, more frequent, and more likely to happen at the same time as other environmental extremes. The combination of multiple environmental extremes can exacerbate the response of sensitive marine organisms. Our hindcast simulation provides the first indication that more than 20 % of the bottom water of the Gulf of Alaska continental shelf was exposed to quadruple heat, positive [H+], negative Ωarag, and negative [O2] compound extreme events during the 2018-2020 marine heat wave. Natural intrusion of deep and acidified water combined with the marine heat wave triggered the first occurrence of these events in 2019. During the 2013-2016 marine heat wave, surface waters were already exposed to widespread marine heat and positive [H+] compound extreme events due to the temperature effect on the [H+]. We introduce a new Gulf of Alaska Downwelling Index (GOADI) with short-term predictive skill, which can serve as indicator of past and near-future positive [H+], negative Ωarag, and negative [O2] compound extreme events on the shelf. Our results suggest that the marine heat waves may have not been the sole environmental stressor that led to the observed ecosystem impacts and warrant a closer look at existing in situ inorganic carbon and other environmental data in combination with biological observations and model output.

Sea surface temperatures (SSTs) vary not only due to heat exchange across the air-sea interface but also due to changes in effective heat capacity as primarily determined by mixed layer depth (MLD). Here, we investigate seasonal and regional characteristics of the contribution of MLD anomalies to SST variability using observational datasets. We propose a metric called Flux Divergence Angle (FDA), which can quantify the relative contributions of surface heat fluxes and MLD anomalies to SST variability. Using this metric, we find that MLD anomalies tend to amplify SST anomalies in the extra-tropics, especially in the eastern ocean basins, during spring and summer. This amplification is explained by a positive feedback loop between SST and MLD via upper ocean stratification. In contrast, MLD anomalies tend to suppress SST anomalies in the eastern tropical Pacific. The MLD contribution in the summer hemispheres is more pronounced on seasonal timescales than on sub-monthly timescales.

The subtropical northeastern Pacific (SNEP) acts as a bridge conveying information between the North and tropical Pacific. While most studies have investigated the SNEP sea surface temperature (SST) interannual variability, less attention has been paid to the pronounced decadal variability in this region. Here, by analyzing observational data and an ensemble pacemaker simulation, we investigate SNEP SST decadal variability in terms of atmospheric forcing processes. We find that both tropical Pacific-forced and internal (independent of tropical Pacific forcing) atmospheric variability play important forcing roles. In particular, tropical Pacific-excited Aleutian low variability, whose center of action shifts southeastward compared to the climatology, contributes to forcing SNEP SST decadal variability. This contribtution could offer an important source for the predictability of SNEP SST decadal variability.

Here, we use idealized climate model simulations to elucidate the governing processes for eastern African interannual hydroclimate and vegetation changes and their relationship to the El Niño-Southern Oscillation (ENSO). Our analysis focuses on Tanzania. In the absence of ENSO-induced sea surface temperature anomalies in the Tropical Indian Ocean, El Niño causes during its peak phase negative precipitation anomalies over Tanzania due to a weakening of the tropical-wide Walker circulation. Resulting drought conditions increase wildfires and decrease vegetation cover. Subsequent wetter La Niña conditions reverse the trend, causing a gradual 1-year-long recovery phase. The 2-year-long vegetation response in Tanzania can be explained as a double-integration of local rainfall, which originates from the seasonally-modulated ENSO Pacific-SST forcing (ENSO Combination mode). In the presence of interannual TIO SST forcing, the southeast African ENSO precipitation and vegetation responses are muted due to Indian Ocean warming and the resulting anomalous upward motion in the atmosphere.