Climate Variability and Response in High-Resolution Earth System Models

• Main Author: Jüling, André
• Other Authors: Dijkstra, H.A., Heydt, A.S. von der
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: Utrecht University 2022
• Subjects: Physical Oceanography; Climate Change; Climate Sensitivity; Climate Variability; High-Resolution Modeling; Southern Ocean
• Online Access: https://dspace.library.uu.nl/handle/1874/416499

In times of anthropogenic climate change, refining our understanding of the climate system is crucial. Earth System Models can simulate all climate subsystems and their interactions under a variety of scenarios; they are among the most important tools of climate science. The ocean is a vital component of the climate system as it covers the majority of the Earth's surface and constitutes the largest heat, water, and carbon reservoirs. Equivalent to atmospheric high and low pressure systems, the ocean exhibits turbulence which consists of dynamic current filaments and ring-like structures, so-called mesoscale eddies, with typical length scales of 10--100~km. These mesoscale features influence the large-scale ocean mean state, its variability, and its response to forcing. A fine enough ocean model grid is needed to resolve the ocean mesoscale; this is computationally expensive and only with the increased computing power of the last years has it become feasible to perform century-long climate model simulations with strongly-eddying oceans. In this thesis, we investigate the effects of mesoscale turbulence on the large spatial and long timescale ocean and climate state. One key question of climate science is how the climate varies internally allowing us to distinguish human-caused changes in the climate. One of the many mechanisms that lead to variability is chaotic mesoscale turbulence which is associated with timescales of days to months but can affect much slower variability on decadal to multidecadal timescales. By investigating sea surface temperature patterns of multidecadal variability, we find enhanced multidecadal variability when mesoscale turbulence is simulated. As modern climate models do not generally employ eddying ocean components, multidecadal variability may be systematically underestimated in these simulations which are widely used for climate change projections. Further, we investigate the mechanisms of one particular mode of multidecadal variability, the Southern Ocean Mode, by looking at the ...