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).