EGU23-7676
https://doi.org/10.5194/egusphere-egu23-7676
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Decadal Climate Variability and Predictability with a High-resolution Eddy-resolving Model 

Wei Zhang1,2,3, Ben Kirtman1, Leo Siqueira1, and Amy Clement1
Wei Zhang et al.
  • 1University of Miami, United States of America (wei.zhang@earth.miami.edu)
  • 2NOAA Global Systems Laboratory, United States of America (zhang.wei@noaa.gov)
  • 3Princeton University, United States of America (wz19@princeton.edu)

Current global climate models typically fail to fully resolve mesoscale ocean features (with length scales on the order of 10 km), such as the western boundary currents, potentially limiting climate predictability over decadal timescales. This study incorporates high-resolution eddy-resolving ocean (HR: 0.1°) in a suite of CESM model experiments that capture these important mesoscale ocean features with increased fidelity. Compared with eddy-parametrized ocean (LR: 1°) experiments, HR experiments show more realistic climatology and variability of sea surface temperature (SST) over the western boundary currents and eddy-rich regions. In the North Atlantic, the inclusion of mesoscale ocean processes produces a more realistic Gulf Stream and improves both localized rainfall patterns and large-scale teleconnections. We identify enhanced decadal SST predictability in HR over the western North Atlantic, which can be explained by the strong vertical connectivity between SST and sub-surface ocean temperature. SST is better connected with slower processes deep down in HR, making SST more persistent (and predictable). Moreover, we detect a better representation of the air-sea interactions between SST and low-level atmosphere over the Gulf Stream, thus improving low-frequency rainfall variations and extremes over the Southeast US. The results further imply that high-resolution GCMs with increased ocean model resolution may be needed in future climate prediction systems.

How to cite: Zhang, W., Kirtman, B., Siqueira, L., and Clement, A.: Decadal Climate Variability and Predictability with a High-resolution Eddy-resolving Model , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7676, https://doi.org/10.5194/egusphere-egu23-7676, 2023.