Internal variability in the climate system confounds assessment of human-induced climate change and imposes irreducible limits on the accuracy of climate change projections, especially at regional and decadal scales. A new collection of initial-condition large ensembles (LEs) generated with seven Earth system models under historical and future radiative forcing scenarios provides new insights into uncertainties due to internal variability versus model differences. These data enhance the assessment of climate change risks, including extreme events, and offer a powerful testbed for new methodologies aimed at separating forced signals from internal variability in the observational record. Opportunities and challenges confronting the design and dissemination of future LEs, including increased spatial resolution and model complexity alongside emerging Earth system applications, are discussed.

The large-scale patterns of covariability between monthly sea surface temperature (SST) and 500-mb height anomalies (Z 500) in the Atlantic sector are investigated as a function of time lag in the NCEP-NCAR reanalysis (1958-97). In agreement with previous studies, the dominant signal is the atmospheric forcing of SST anomalies, but statistically significant covariances are also found when SST leads Z 500 by several months. In winter, a Pan-Atlantic SST pattern precedes the North Atlantic oscillation (NAO) by up to 6 months. Such long lead time covariance is interpreted in the framework of the stochastic climate model, reflecting the forcing of the NAO by persistent Atlantic SST anomalies. A separate analysis of midlatitudes (20Њ-70ЊN) and tropical (20ЊS-20ЊN) SST anomalies reveals that the bulk of the NAO signal comes from the midlatitudes. A dipolar anomaly, with warm SST southeast of Newfoundland and cold SST to the northeast and southeast, precedes a positive phase of the NAO, and it should provide a prediction of up to 15% of its monthly variance several months in advance. Since the ''forcing'' SST pattern projects significantly onto the tripole pattern generated by the NAO, these results indicate a positive feedback between the SST tripole and the NAO, with a strength of up to Ӎ25 m K Ϫ1 at 500 mb or 2-3 mb K Ϫ1 at sea level. Additionally, a warming of the tropical Atlantic (20ЊS-20ЊN), roughly symmetric about the equator, induces a negative NAO phase in early winter. This tropical forcing of the NAO is nearly uncorrelated with and weaker than that resulting from the midlatitudes, and is associated with shorter lead times and reduced predictive skill.

The concept of stochastic climate models developed in Part I of this series (Hasselmann, 1976) is applied to the investigation of the low frequency variability of the upper ocean. It is shown that large-scale, long-time sea surface temperature (SST) anomalies may be explained naturally as the response of the oceanic surface layers to short-time-scale atmospheric forcing. The whitenoise spectrum of the atmospheric input produces a red response spectrum, with most of the variance concentrated in very long periods. Without stabilizing negative feedback, the oceanic response would be nonstationary, the total SST variance growing indefinitely with time. With negative feedback, the response is asymptotically stationary. These effects are illustrated through numerical experiments with a very simple ocean-atmosphere model. The model reproduces the principal features and orders of magnitude of the observed SST anomalies in mid-latitudes. Independent support of the stochastic forcing model is provided by direct comparisons of observed sensible and latent heat flux spectra with SST anomaly spectra, and also by the structure of the cross correlation functions of atmospheric surface pressure and SST anomaly patterns. The numerical model is further used to simulate anomalies in the near-surface thermocline through Ekman pumping driven by the curl of the wind stress. The results suggest that short-time-scale atmospheric forcing should be regarded as a possible candidate for the origin of large-scale, low-period variability in the seasonal thermocline.

The mechanisms that contribute to the generation and damping of large-scale mid-latitude sea surface temperature (SST) anomalies are discussed. The SST anomalies reflect primarily the response of the upper ocean to the changes in air-sea fluxes that are associated with daily weather fluctuations. Heat flux forcing is dominant in the lower middle latitudes, while wind-driven entrainment may be most effective in the high latitudes; advection by anomalous Ekman current is generally less important, and Ekman pumping is negligible. The SST anomalies decay in part because of entrainment effects associated with mixed-layer deepening and oceanic mixing and in part because of heat exchanges with the atmosphere. The three approaches commonly used to model the evolution of SST anomalies are reviewed: case studies based on monthly or seasonal anomaly maps of the large-scale SST and atmospheric anomalies, numerical simulations with one-dimensional mixed-layer models, and stochastic forcing models. We stress the similarities in the different approaches and discuss their main advantages and limitations. The response of the atmosphere to mid-latitude SST anomalies is considered. First, we discuss the poorly known relationship between SST anomalies and diabatic heating. Using a crude assumption for the air-sea coupling, we consider a two-layer quasi-geostrophic channel model and discuss the stationary wave response to SST anomaly forcing and the resulting air-sea feedback. It is found that the back interaction of the SST anomalies onto the atmosphere causes a weak SST anomaly damping at large scales and a strong one at small scales; the air-sea coupling should also act as an eastward propagator for the SST anomalies. The response of more realistic linear wave models to prescribed diabatic heating is then reviewed, and it is suggested that realistic mid-latitude SST anomalies have a weak influence on the atmospheric circulation, corresponding to changes in the geopotential height of 10-30 m at most. This order of magnitude is consistent with the results of general circulation model experiments and with the limited climate predictability associated with mid-latitude SST anomalies.

The concept of stochastic climate models developed in Part I of this series (Hasselmann, 1976) is applied to the investigation of the low frequency variability of the upper ocean. It is shown that large‐scale, long‐time sea surface temperature (SST) anomalies may be explained naturally as the response of the oceanic surface layers to short‐time‐scale atmospheric forcing. The white‐noise spectrum of the atmospheric input produces a red response spectrum, with most of the variance concentrated in very long periods. Without stabilizing negative feedback, the oceanic response would be nonstationary, the total SST variance growing indefinitely with time. With negative feedback, the response is asymptotically stationary. These effects are illustrated through numerical experiments with a very simple ocean‐atmosphere model. The model reproduces the principal features and orders of magnitude of the observed SST anomalies in mid‐latitudes. Independent support of the stochastic forcing model is provided by direct comparisons of observed sensible and latent heat flux spectra with SST anomaly spectra, and also by the structure of the cross correlation functions of atmospheric surface pressure and SST anomaly patterns. The numerical model is further used to simulate anomalies in the near‐surface thermocline through Ekman pumping driven by the curl of the wind stress. The results suggest that short‐time‐scale atmospheric forcing should be regarded as a possible candidate for the origin of large‐scale, low‐period variability in the seasonal thermocline.

Ocean-atmosphere interaction over the Northern Hemisphere western boundary current (WBC) regions (i.e., the Gulf Stream, Kuroshio, Oyashio, and their extensions) is reviewed with an emphasis on their role in basin-scale climate variability. SST anomalies exhibit considerable variance on interannual to decadal time scales in these regions. Low-frequency SST variability is primarily driven by basin-scale wind stress curl variability via the oceanic Rossby wave adjustment of the gyre-scale circulation that modulates the latitude and strength of the WBC-related oceanic fronts. Rectification of the variability by mesoscale eddies, reemergence of the anomalies from the preceding winter, and tropical remote forcing also play important roles in driving and maintaining the low-frequency variability in these regions. In the Gulf Stream region, interaction with the deep western boundary current also likely influences the low-frequency variability. Surface heat fluxes damp the low-frequency SST anomalies over the WBC regions; thus, heat fluxes originate with heat anomalies in the ocean and have the potential to drive the overlying atmospheric circulation. While recent observational studies demonstrate a local atmospheric boundary layer response to WBC changes, the latter's influence on the large-scale atmospheric circulation is still unclear. Nevertheless, heat and moisture fluxes from the WBCs into the atmosphere influence the mean state of the atmospheric circulation, including anchoring the latitude of the storm tracks to the WBCs. Furthermore, many climate models suggest that the large-scale atmospheric response to SST anomalies driven by ocean dynamics in WBC regions can be important in generating decadal climate variability. As a step toward bridging climate model results and observations, the degree of realism of the WBC in current climate model simulations is assessed. Finally, outstanding issues concerning oceanatmosphere interaction in WBC regions and its impact on climate variability are discussed.

Extratropical sea surface temperature (SST) and surface turbulent heat flux monthly anomalies in the central and eastern part of the North Atlantic are considered for the period 1952-92 on a 5Њ ϫ 5Њ grid. In this region where the mean surface current is small, the SST anomalies are well simulated by a simple one-dimensional mixed layer model that is stochastically forced by the day-today changes in the local air-sea fluxes. A statistical signature of the stochastic model is that the cross correlation between surface heat flux and SST anomalies changes sign between negative and positive lags when the heat flux feedback is negative. This is observed at each grid point of the domain for the turbulent heat flux, which thus contributes both to generating the midlatitude SST anomalies and to damping them, once they are generated. Using properties of the lag covariance between SST and heat flux anomalies, the turbulent heat flux feedback is estimated from the observations. It averages to about 20 W m Ϫ2 K Ϫ1 in the investigated domain, increasing toward the northwest and the northeast and decreasing southward. It also varies seasonally, being generally largest in the fall and smaller and more uniform in summer. There is no indication that it can become significantly positive. A negative turbulent heat flux feedback is also suggested by the lag relation between the dominant modes of SST and turbulent heat flux variability over the whole North Atlantic, and it is found that the spatial patterns of the associated SST and turbulent heat flux anomalies are remarkably similar whether the atmosphere leads or lags, with only a change of heat flux sign between lead and lag situations. This analysis provides some observational support for the use on short timescales of a restoring condition for SST in ocean-only simulations, but the coupling coefficient should be weaker than usually assumed and a function of latitude and season. The associated SST-evaporation feedback has little effect on interannual surface salinity changes. It should be significant on longer timescales, but then the restoring temperature should be allowed to vary and nonlocal influences should be considered.

The ocean-atmosphere coupling in the North Atlantic is investigated during the twentieth century using maximum covariance analysis of sea surface temperature (SST) and 500-hPa geopotential height analyses and performing regressions on dynamical diagnostics such as Eady growth rate, wave activity flux, and velocity potential. The North Atlantic Oscillation (NAO) generates the so-called SST anomaly tripole. A rather similar SST anomaly tripole, with the subpolar anomaly displaced to the east and a more contracted subtropical anomaly, which is referred to as the North Atlantic horseshoe pattern, in turn influences the atmosphere. In the fall and early winter, the response is NAO like and primarily results from subpolar forcing centered over the Labrador Sea and off Newfoundland. In summer, the largest atmospheric response to SST resembles the east Atlantic pattern and results from a combination of subpolar and tropical forcing. To emphasize the interannual to multidecadal variability, the same analysis is repeated after low-pass filtering. The SST influence is dominated by the Atlantic multidecadal oscillation (AMO), which also has a horseshoe shape, but with larger amplitude in the subpolar basin. A warm AMO phase leads to an atmospheric warming limited to the lower troposphere in summer, while it leads to a negative phase of the NAO in winter. The winter influence of the AMO is suggested to be primarily forced by the Atlantic SSTs in the northern subtropics. Such influence of the AMO is found in winter instead of early winter because the winter SST anomalies have a larger persistence, presumably because of SST reemergence.