Fig. 4: (a) Annual mean zonal mean temperature (°C) and (b) annual mean zonal mean zonal wind (m/s) as an ensemble mean over the 5 historical realizations for 1985–2014 compared to ERA5 climatology (Copernicus Climate Change Service (C3S), 2017; Hersbach et al., 2020) from 1985–2014. Solid lines represent temperatures at or above 0°C and westerly zonal wind speeds from the ERA5 climatology, dashed lines temperatures below 0°C and easterly wind speeds, and contours represent biases.

4.3 ENSO statistics and phase locking

Sea surface temperature (SST) anomalies in the tropical Pacific associated with the El Niño-Southern Oscillation (ENSO) are of global concern. Since ENSO is the largest signal of interannual variability on Earth (e.g. Timmermann et al., 2018), the realistic simulation of these SST anomalies, both with respect to their absolute magnitude and temporal behaviour, is crucial for any global climate model.
When comparing area-weighted SST anomalies in the Niño 3.4 box (170°W–120°W, 5°S–5°N) to observations, we find that the five historical ensemble members with AWI-CM show a realistic distribution (Fig. 5). The clear asymmetry between El Niño and La Niña events seen in observations (positive skewness of Niño 3.4 SST anomalies) is also evident in the model. The skewness is 0.15 ± 0.16 (one standard deviation) in the five ensemble members while the observed skewness is 0.36 for 1870-2014. Note that all data have been linearly detrended and the seasonal cycle has been removed before computing the standard deviation. Moreover, the Niño 3.4 index has a significant broad spectral peak, both in the model and in observations for 1870-2014, at a typical period of about 4-7 years when compared to corresponding red-noise processes (Fig. 6). While the distribution of the variance over the frequencies is well reproduced in the model, the total variance is overestimated in all AWI-CM-MR ensemble members (0.75-1.01 K2 compared to the observed 0.57 K2).