The modern history of North Atlantic sea surface temperature shows variability coinciding with changes in air temperature and rainfall over the Northern Hemisphere. There is a debate about this variability and, in particular, whether it is internal to the ocean-atmosphere system or is forced by external factors (natural and anthropogenic). Here we present a temperature record, obtained using the Sr/Ca ratio measured in a skeleton of a sclerosponge, that shows agreement with the instrumental record over the past 150 years as well as multidecadal temperature variability over the last 600 years. Comparison with climate simulations of the last millennium shows that large cooling events recorded, in the sclerosponge, are consistent with natural (primarily volcanic activity) and anthropogenic forcings. There are, however, multidecadal periods not connected to current estimates of external forcing over the last millennium allowing for alternative explanations, such as internally driven changes in ocean and atmospheric circulation.

Abstract. Future changes in the El Niño–Southern Oscillation (ENSO) are uncertain, both because future projections differ between climate models and because the large internal variability of ENSO clouds the diagnosis of forced changes in observations and individual climate model simulations. By leveraging 14 single model initial-condition large ensembles (SMILEs), we robustly isolate the time-evolving response of ENSO sea surface temperature (SST) variability to anthropogenic forcing from internal variability in each SMILE. We find nonlinear changes in time in many models and considerable inter-model differences in projected changes in ENSO and the mean-state tropical Pacific zonal SST gradient. We demonstrate a linear relationship between the change in ENSO SST variability and the tropical Pacific zonal SST gradient, although forced changes in the tropical Pacific SST gradient often occur later in the 21st century than changes in ENSO SST variability, which can lead to departures from the linear relationship. Single-forcing SMILEs show a potential contribution of anthropogenic forcing (aerosols and greenhouse gases) to historical changes in ENSO SST variability, while the observed historical strengthening of the tropical Pacific SST gradient sits on the edge of the model spread for those models for which single-forcing SMILEs are available. Our results highlight the value of SMILEs for investigating time-dependent forced responses and inter-model differences in ENSO projections. The nonlinear changes in ENSO SST variability found in many models demonstrate the importance of characterizing this time-dependent behavior, as it implies that ENSO impacts may vary dramatically throughout the 21st century.

This paper attempts to enhance our understanding of the causes of Atlantic Multidecadal Variability, the AMV. Following the literature, we define the AMV as the SST averaged over the North Atlantic basin, linearly detrended and low-pass filtered. There is an ongoing debate about the drivers of the AMV, which include internal variability generated from the ocean or atmosphere (or both), and external radiative forcing. We test the role of these factors in explaining the time history, variance, and spatial pattern of the AMV using a 41-member ensemble from a fully coupled version of CESM and a 10-member ensemble of the CESM atmosphere coupled to a slab ocean. The large ensemble allows us to isolate the role of external forcing versus internal variability, and the model differences allow us to isolate the role of coupled ocean circulation. Both with and without coupled ocean circulation, external forcing explains more than half of the variance of the observed AMV time series, indicating its important role in simulating the 20th century AMV phases. In this model the net effect of ocean processes is to reduce the variance of the AMV. Dynamical ocean coupling also reduces the ability of the model to simulate the characteristic spatial pattern of the AMV, but forcing has little impact on the pattern. Historical forcing improves the time history and variance of the AMV simulation, whilst the more realistic ocean representation reduces the variance below that observed and lowers the correlation with observations.

The North Atlantic Oscillation (NAO) is predictable in climate models at near-decadal timescales. Predictive skill derives from ocean initialization, which can capture variability internal to the climate system, and from external radiative forcing. Herein, we show that predictive skill for the NAO in a very large uninitialized multi-model ensemble is commensurate with previously reported skill from a state-of-the-art initialized prediction system. The uninitialized ensemble and initialized prediction system produce similar levels of skill for northern European precipitation and North Atlantic SSTs. Identifying these predictable components becomes possible in a very large ensemble, confirming the erroneously low signal-to-noise ratio previously identified in both initialized and uninitialized climate models. Though the results here imply that external radiative forcing is a major source of predictive skill for the NAO, they also indicate that ocean initialization may be important for particular NAO events (the mid-1990s strong positive NAO), and, as previously suggested, in certain ocean regions such as the subpolar North Atlantic ocean. Overall, we suggest that improving climate models’ response to external radiative forcing may help resolve the known signal-to-noise error in climate models.

North Atlantic sea surface temperatures (SST) exhibit a lagged response to the North Atlantic Oscillation (NAO) in both models and observations, which has previously been attributed to changes in ocean heat transport. Here we examine the lagged relationship between the NAO and Atlantic multidecadal variability (AMV) in the context of the two other major components of the AMV: atmospheric noise and external forcing. In preindustrial control runs, we generally find that after accounting for spurious signals introduced by filtering, the SST response to the NAO is only statistically significant in the subpolar gyre. Further, the lagged SST response to the NAO is small in magnitude and offers a limited contribution to the AMV pattern, statistics, or predictability. When climate models include variable external forcing, the relationship between the NAO and AMV is obscured and becomes inconsistent. In these historically forced runs, knowledge of the prior NAO offers reduced predictability. The differences between the preindustrial and the historically forced ensembles suggest that we do not yet have enough observational data to surmise the true NAO–AMV relationship and add evidence that external forcing plays a substantial role in producing the AMV.