North Atlantic Ocean Circulation Response to Stochastic Mesoscale Weather Systems

Abstract:

The ocean is forced by the atmosphere on a range of spatial and temporal scales. In ocean and climate models the resolution of the atmospheric forcing sets a limit on the scales that are represented. For typical climate models this means mesoscale (< 400 km) atmospheric forcing is absent. Previous studies have demonstrated that mesoscale forcing significantly affects key ocean circulation systems such as the North Atlantic Subpolar gyre and the Atlantic Meridional Overturning Circulation (AMOC). However, the approach of these studies has either been ad hoc or limited in resolution. Here we present ocean model simulations with and without realistic mesoscale atmospheric forcing that represents scales down to 10 km. We use a novel stochastic parameterization – based on a cellular automaton algorithm that is common in weather forecasting ensemble prediction systems – to represent spatially coherent weather systems over a range of scales, including down to the smallest resolvable by the ocean grid. The parameterization is calibrated spatially and temporally using marine wind observations. The addition of mesoscale atmospheric forcing leads to coherent patterns of change in the sea surface temperature and mixed-layer depth. It also leads to statistically significant increases in the volume transport in the North Atlantic subtropical gyre (STG) and subpolar gyre (SPG) and in the AMOC. A steady-state circulation response emerges after 10 years simulation – an elevated northward heat transport across the gyre boundary, driven by the enhanced STG, slows down the SPG and slightly weakens the AMOC, revealing the importance of ocean dynamics in generating non-local ocean response to the stochastic mesoscale atmospheric forcing. Atmospheric convection-permitting regional climate simulations predict changes in the intensity and frequency of mesoscale weather systems this century, so representing these systems in coupled climate models could bring higher fidelity in future climate projections.