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Single-forcing large ensembles are a relatively new tool for quantifying the contributions of different anthropogenic and natural forcings to the historical and future projected evolution of the climate system. This study introduces a new single-forcing large ensemble with the Community Earth System Model, version 2 (CESM2), which can be used to separate the influences of greenhouse gases, anthropogenic aerosols, biomass burning aerosols, and all remaining forcings on the evolution of the Earth system from 1850 to 2050. Here, the forced responses of global near-surface temperature and associated drivers are examined in CESM2 and compared with those in a single-forcing large ensemble with CESM2’s predecessor, CESM1. The experimental design, the imposed forcing, and the model physics all differ between the CESM1 and CESM2 ensembles. In CESM1, an “all-but-one” approach was used whereby everything except the forcing of interest is time evolving, while in CESM2 an “only” approach is used, whereby only the forcing of interest is time evolving. This experimental design choice is shown to matter considerably for anthropogenic aerosol-forced change in CESM2, due to state dependence of cryospheric albedo feedbacks and nonlinearity in the Atlantic meridional overturning circulation (AMOC) response to forcing. This impact of experimental design is, however, strongly dependent on the model physics and/or the imposed forcing, as the same sensitivity to experimental design is not found in CESM1, which appears to be an inherently less nonlinear model in both its AMOC behavior and cryospheric feedbacks.

 

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. 

The canonical index of “Atlantic Multidecadal Variability” (AMV) is the low‐pass filtered timeseries of sea surface temperature anomalies (SSTA) averaged over the North Atlantic. This index and its associated SSTA spatial pattern confound externally forced climate change and internally generated climate variability. The internal component of AMV is commonly isolated by either subtracting the global‐mean SSTA or removing the pattern of SSTA associated with the global‐mean. This study evaluates the skill of each method with regard to the spatial pattern of internal AMV, using nine coupled model Large Ensembles over the period 1940–2100 as a testbed in which the true internal AMV is knowna priori. The first method aliases the structure of forced climate change onto internal AMV, while the second method is generally robust to climate change. The models simulate realistic patterns of internal AMV, although such an assessment is hampered by the brevity of the observational record.

 

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.

 

Sudden stratospheric warmings (SSWs) are key to understanding and predicting subseasonal Northern Hemisphere winter climate variability. Here we study the uncertainty in the surface response to SSWs in reanalysis data by constructing synthetic composites based on bootstrapping the 39 events observed during the 1958–2019 period. We find that the well‐known responses in the North Atlantic and European regions following SSWs are consistently present, but their magnitude and spatial pattern vary considerably across the synthetic composites. We further find that this uncertainty is unrelated to stratospheric polar vortex strength and is instead the result of independent tropospheric variability. Our findings provide a basis for evaluating the fidelity of the surface response to SSWs in models.