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Abstract To improve understanding of ocean processes impacting monthly sea surface temperature (SST) variability, we analyze a Community Earth System Model, version 2, hierarchy in which models vary only in their degree of ocean complexity. The most realistic ocean is a dynamical ocean model, as part of a fully coupled model (FCM). The next most realistic ocean, from a mechanically decoupled model (MDM), is like the FCM but excludes anomalous wind stress–driven ocean variability. The simplest ocean is a slab ocean model (SOM). Inclusion of a buoyancy coupled dynamic ocean as in the MDM, which includes temperature advection and vertical mixing absent in the SOM, leads to dampening of SST variance everywhere and reduced persistence of SST anomalies in the high latitudes and equatorial Pacific compared to the SOM. Inclusion of anomalous wind stress–driven ocean dynamics as in the FCM leads to higher SST variance and longer persistence time scales in most regions compared to the MDM. The net role of the dynamic ocean, as an overall dampener or amplifier of anomalous SST variance and persistence, is regionally dependent. Notably, we find that efforts to reduce the complexity of the ocean models in the SOM and MDM configurations result in changes in the magnitude of the thermodynamic forcing of SST variability compared to the FCM. These changes, in part, stem from differences in the seasonally varying mixed layer depth and should be considered when attempting to quantify the relative contribution of certain ocean mechanisms to differences in SST variability between the models. 

Abstract El Niño and La Niña events show a wide range of durations over the historical record. The predictability of event duration has remained largely unknown, although multiyear events could prolong their climate impacts. To explore the predictability of El Niño and La Niña event duration, multiyear ensemble forecasts are conducted with the Community Earth System Model, version 1 (CESM1). The 10–40-member forecasts are initialized with observed oceanic conditions on 1 March, 1 June, and 1 November of each year during 1954–2015; ensemble spread is created through slight perturbations to the atmospheric initial conditions. The CESM1 predicts the duration of individual El Niño and La Niña events with lead times ranging from 6 to 25 months. In particular, forecasts initialized in November, near the first peak of El Niño or La Niña, can skillfully predict whether the event continues through the second year with 1-yr lead time. The occurrence of multiyear La Niña events can be predicted even earlier with lead times up to 25 months, especially when they are preceded by strong El Niño. The predictability of event duration arises from initial thermocline depth anomalies in the equatorial Pacific, as well as sea surface temperature anomalies within and outside the tropical Pacific. The forecast error growth, on the other hand, originates mainly from atmospheric variability over the North Pacific in boreal winter. The high predictability of event duration indicates the potential for extending 12-month operational forecasts of El Niño and La Niña events by one additional year. 

Abstract Analysis of observational data and a long control simulation of the Community Earth System Model, version 1 (CESM1), shows that El Niño events developing in boreal spring to early summer usually terminate after peaking in winter, whereas those developing after summer tend to persist into the second year. To test the predictability of El Niño duration based on the onset timing, perfect model predictions were conducted for three El Niño events developing in April or September in the CESM1 control simulation. For each event, 30-member ensemble simulations are initialized with the same oceanic conditions in the onset month but with slightly different atmospheric conditions and integrated for 2 years. The CESM1 successfully predicts the termination of El Niño after the peak in 95% of the April-initialized simulations and the continuation of El Niño into the second year in 83% of the September-initialized simulations. The predictable component of El Niño duration arises from the initial oceanic conditions that affect the timing and magnitude of negative feedback within the equatorial Pacific, as well as from the Indian and Atlantic Oceans. The ensemble spread of El Niño duration, on the other hand, originates from surface wind variability over the western equatorial Pacific in spring following the peak. The wind variability causes a larger spread in the September-initialized than the April-initialized ensemble simulations due to weaker negative feedback in spring. These results indicate potential predictability of El Niño events beyond the current operational forecasts by 1 year. 

The temporal evolution of El Niño and La Niña varies greatly from event to event. To understand the dynamical processes controlling the duration of El Niño and La Niña events, a suite of observational data and a long control simulation of the Community Earth System Model, version 1, are analyzed. Both observational and model analyses show that the duration of El Niño is strongly affected by the timing of onset. El Niño events that develop early tend to terminate quickly after the mature phase because of the early arrival of delayed negative oceanic feedback and fast adjustments of the tropical Atlantic and Indian Oceans to the tropical Pacific Ocean warming. The duration of La Niña events is, on the other hand, strongly influenced by the amplitude of preceding warm events. La Niña events preceded by a strong warm event tend to persist into the second year because of large initial discharge of the equatorial oceanic heat content and delayed adjustments of the tropical Atlantic and Indian Oceans to the tropical Pacific cooling. For both El Niño and La Niña, the interbasin sea surface temperature (SST) adjustments reduce the anomalous SST gradient toward the tropical Pacific and weaken surface wind anomalies over the western equatorial Pacific, hastening the event termination. Other factors external to the dynamics of El Niño–Southern Oscillation, such as coupled variability in the tropical Atlantic and Indian Oceans and atmospheric variability over the North Pacific, also contribute to the diversity of event duration. 

Abstract The mean-state bias and the associated forecast errors of the El Niño–Southern Oscillation (ENSO) are investigated in a suite of 2-yr-lead retrospective forecasts conducted with the Community Earth System Model, version 1, for 1954–2015. The equatorial Pacific cold tongue in the forecasts is too strong and extends excessively westward due to a combination of the model’s inherent climatological bias, initialization imbalance, and errors in initial ocean data. The forecasts show a stronger cold tongue bias in the first year than that inherent to the model due to the imbalance between initial subsurface oceanic states and model dynamics. The cold tongue bias affects not only the pattern and amplitude but also the duration of ENSO in the forecasts by altering ocean–atmosphere feedbacks. The predicted sea surface temperature anomalies related to ENSO extend to the far western equatorial Pacific during boreal summer when the cold tongue bias is strong, and the predicted ENSO anomalies are too weak in the central-eastern equatorial Pacific. The forecast errors of pattern and amplitude subsequently lead to errors in ENSO phase transition by affecting the amplitude of the negative thermocline feedback in the equatorial Pacific and tropical interbasin adjustments during the mature phase of ENSO. These ENSO forecast errors further degrade the predictions of wintertime atmospheric teleconnections, land surface air temperature, and rainfall anomalies over the Northern Hemisphere. These mean-state and ENSO forecast biases are more pronounced in forecasts initialized in boreal spring–summer than other seasons due to the seasonal intensification of the Bjerknes feedback. 

Abstract Identifying the origins of wintertime climate variations in the Northern Hemisphere requires careful attribution of the role of El Niño–Southern Oscillation (ENSO). For example, Aleutian low variability arises from internal atmospheric dynamics and is remotely forced mainly via ENSO. How ENSO modifies the local sea surface temperature (SST) and North American precipitation responses to Aleutian low variability remains unclear, as teasing out the ENSO signal is difficult. This study utilizes carefully designed coupled model experiments to address this issue. In the absence of ENSO, a deeper Aleutian low drives a positive Pacific decadal oscillation (PDO)-like SST response. However, unlike the observed PDO pattern, a coherent zonal band of turbulent heat flux–driven warm SST anomalies develops throughout the subtropical North Pacific. Furthermore, non-ENSO Aleutian low variability is associated with a large-scale atmospheric circulation pattern confined over the North Pacific and North America and dry precipitation anomalies across the southeastern United States. When ENSO is included in the forcing of Aleutian low variability in the experiments, the ENSO teleconnection modulates the turbulent heat fluxes and damps the subtropical SST anomalies induced by non-ENSO Aleutian low variability. Inclusion of ENSO forcing results in wet precipitation anomalies across the southeastern United States, unlike when the Aleutian low is driven by non-ENSO sources. Hence, we find that the ENSO teleconnection acts to destructively interfere with the subtropical North Pacific SST and southeastern United States precipitation signals associated with non-ENSO Aleutian low variability. 

A decades-long affair 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 

Abstract Teleconnection rainfall over North America may be systematically altered by tropical Pacific mean state changes. Characterizing teleconnection changes to improve prediction requires many realizations of ENSO events, but twentieth century data are temporally limited. To extend twentieth century records, we evaluate ENSO events in a new last‐millennium paleoclimate data assimilation reconstruction to deduce how mean state changes affect the magnitude/extent of ENSO‐driven rainfall in the United States. Despite global cooling during the Little Ice Age, the central‐eastern tropical Pacific warms relative to the Medieval Climate Anomaly, shifting teleconnections eastward and increasing rainfall anomalies in the southwestern United States. Teleconnections strengthen independently of ENSO amplitude; we thus suggest caution in using paleoclimate reconstructions of teleconnection rainfall as a proxy for ENSO amplitude. We demonstrate teleconnection rainfall is sensitive to the pattern of tropical Pacific mean SST changes, underscoring the importance of reducing uncertainties in future warming patterns in the tropical Pacific.