Die Bedeutung der Ozean-Atmosphäre-Wechselwirkung für die natürliche Klimavariabilität in der Arktis - Kinzel, Julian (2010)
The present increase in average Arctic (60°-90°N) surface temperature is almost three times as high as the corresponding global average increase. An accelerated temperature rise was also observed at the beginning of the 20th century (1910-1940, ECW) and is referred to as "Arctic Amplication". It was followed by a sharp temperature decrease (1940-1970) with following warming. Its trend has only recently been exceeded by the current Arctic warming. The underlying mechanisms which produce such multidecadal climate variability are presently under debate. It is suggested that the ECW was driven by natural coupling mechanisms within the climate system. In this context it might have be linked to changing westerlies in the North Atlantic, anomalies of the Atlantic meridional overturning circulation as well as changes in sea surface temperatures of the tropical Pacic (NAO, MOC and NINO3, respectively). Since the Arctic climate system seems to play a crucial role with respect to global warming, further analysis is required in order to understand its origin. For the purposes of this study, three control simulations (1500 yrs. of integrations each) were analysed which dffer in complexity in sense of coupling between atmosphere and ocean components. These are a fully coupled atmospheric-seaice-ocean GCM (ECHAM5/MPI-OM), an atmospheric GCM coupled with a thermodynamical mixed-layer ocean model including a thermodynamical seaice model (ECHAM5/MLO) and an atmospheric GCM forced by prescribed lower boundary conditions (ECHAM5/xed-SST). The annual means of anomalies of Arctic surface temperature (SAT) and sea ice extent (ICE) were analysized with respect to the different runs and their links to the major possible climate variability drives such as NAO-, MOC- and NINO3-variability. The objective was to assess the impact of coupling between ocean and atmosphere concerning driving mechanisms of (multi-) decadal variability, using statistical tools like correlation, coherence and wavelet-analysis. The results show that the coupled ...