Simulated Relationships between Regional Temperatures and Large-Scale Circulation: 125 kyr BP (Eemian) and the Preindustrial Period

To investigate relationships between large-scale circulation and regional-scale temperatures during the last (Eemian) interglacial, a simulation with a general circulation model (GCM) under orbital forcing conditions of 125 kyr BP is compared with a simulation forced with the Late Holocene preindustrial conditions. Consistent with previous GCM simulations for the Eemian, higher northern summer 2-m temperatures are found, which are directly related to the different insolation. Differences in the mean circulation are evident such as, for instance, stronger northern winter westerlies toward Europe, which are associated with warmer temperatures in central and northeastern Europe in the Eemian simulation, while the circulation variability, analyzed by means of a principal component analysis of the sea level pressure (SLP) field, is very similar in both periods. As a consequence of the differences in the mean circulation the simulated Arctic Oscillation (AO) temperature signal in the northern winter, on interannual-to-multidecadal time scales, is weaker during the Eemian than today over large parts of the Northern Hemisphere. Correlations between the AO index and the central European temperature (CET) decrease by about 0.2. The winter and spring SLP anomalies over the North Atlantic/European domain that are most strongly linearly linked to the CET cover a smaller area and are shifted westward over the North Atlantic during the Eemian. However, the strength of the connection between CET and these SLP anomalies is similar in both simulations. The simulated differences in the AO temperature signal and in the SLP anomaly, which is linearly linked to the CET, suggest that during the Eemian the link between the large-scale circulation and temperaturesensitive proxy data from Europe may differ from present-day conditions and that this difference should be taken into account when inferring large-scale climate from temperature-sensitive proxy data.

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