Abstract
AbstractThe variability of the Atlantic meridional overturning circulation (AMOC) and its governing processes during the Last Glacial Maximum (LGM) is investigated in the Kiel Climate Model. Under LGM conditions, multidecadal AMOC variability is mainly forced by the surface heat flux variability linked to the East Atlantic pattern (EAP). In contrast, the multidecadal AMOC variability under preindustrial conditions is mainly driven by the surface heat flux variability associated with the North Atlantic Oscillation. Standâalone atmosphere model experiments show that relative to preindustrial conditions, the change in AMOC forcing under LGM conditions is tightly linked to the differences in topography.
Highlights
During the Last Glacial Maximum (LGM) about 21,000 years before present, global ice volume reached its maximum (Mix et al, 2001)
The Qnet pattern associated with the North Atlantic Oscillation (NAO) (EAP) in Figure 4a (Figure 4b) and the Qnet pattern leading the Atlantic meridional overturning circulation (AMOC) by a decade shown in Figure 4c (Figure 4d) share similarities over the deep convection sites. This suggests that the Qnet anomalies associated with the NAO (EAP) drive the AMOC variations in preindustrial control run (PI) (GLAC)
This study investigates the multidecadal AMOC variability during the LGM and its driving factors by means of a version of the Kiel Climate Model (KCM)
Summary
During the Last Glacial Maximum (LGM) about 21,000 years before present, global ice volume reached its maximum (Mix et al, 2001). Under the LGM boundary conditions, large perturbations in mean atmospheric circulation and its internal variability, massively extended sea ice and shifted deep convection sites over the North Atlantic Sector are simulated by climate models. These changes can essentially affect the response of subpolar North Atlantic deep convection to the atmospheric forcing and subsequently the AMOC. We use the Kiel Climate Model (KCM; Park et al, 2009) to investigate the multidecadal AMOC variability during the LGM and compare it to that simulated under preindustrial conditions. The EOFs are orthogonal and sorted by the amount of explained variance in a descending order
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