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  • Nature Research  (2)
  • 1
    Publication Date: 2022-01-31
    Description: Climate models generally simulate a long-term slowdown of the Pacific Walker Circulation in a warming world. However, despite increasing greenhouse forcing, there was an unprecedented intensification of the Pacific Trade Winds during 1992–2011, that co-occurred with a temporary slowdown in global surface warming. Using ensemble simulations from three different climate models starting from different initial conditions, we find a large spread in projected 20-year globally averaged surface air temperature trends that can be linked to differences in Pacific climate variability. This implies diminished predictive skill for global surface air temperature trends over decadal timescales, to a large extent due to intrinsic Pacific Ocean variability. We show, however, that this uncertainty can be considerably reduced when the initial oceanic state is known and well represented in the model. In this case, the spatial patterns of 20-year surface air temperature trends depend largely on the initial state of the Pacific Ocean.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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  • 2
    Publication Date: 2024-02-07
    Description: There is debate about slowing of the Atlantic Meridional Overturning Circulation (AMOC), a key component of the global climate system. Some focus is on the sea surface temperature (SST) slightly cooling in parts of the subpolar North Atlantic despite widespread ocean warming. Atlantic SST is influenced by the AMOC, especially on decadal timescales and beyond. The local cooling could thus reflect AMOC slowing and diminishing heat transport, consistent with climate model responses to rising atmospheric greenhouse gas concentrations. Here we show from Atlantic SST the prevalence of natural AMOC variability since 1900. This is consistent with historical climate model simulations for 1900–2014 predicting on average AMOC slowing of about 1 Sv at 30° N after 1980, which is within the range of internal multidecadal variability derived from the models’ preindustrial control runs. These results highlight the importance of systematic and sustained in-situ monitoring systems that can detect and attribute with high confidence an anthropogenic AMOC signal.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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