Surface Wave Effects in the NEMO Ocean Model: Forced and Coupled Experiments

TL;DR

This paper extends the NEMO ocean model to include wave-related processes, demonstrating improved temperature bias reduction and better alignment with observed ocean heat content through experiments in forced and coupled modes.

Contribution

It introduces three wave-related physical processes into NEMO and evaluates their impact in both forced and coupled ocean-atmosphere simulations.

Findings

Wave effects significantly influence ocean temperature biases.

Turbulent kinetic energy flux from breaking waves has the largest impact.

Including wave processes improves agreement with observed ocean heat content.

Abstract

The NEMO general circulation ocean model is extended to incorporate three physical processes related to ocean surface waves, namely the surface stress (modified by growth and dissipation of the oceanic wave field), the turbulent kinetic energy flux from breaking waves, and the Stokes-Coriolis force. Experiments are done with NEMO in ocean-only (forced) mode and coupled to the ECMWF atmospheric and wave models. Ocean-only integrations are forced with fields from the ERA-Interim reanalysis. All three effects are noticeable in the extra-tropics, but the sea-state dependent turbulent kinetic energy flux yields by far the largest difference. This is partly because the control run has too vigorous deep mixing due to an empirical mixing term in NEMO. We investigate the relation between this ad hoc mixing and Langmuir turbulence and find that it is much more effective than the Langmuir parameterization used in NEMO. The biases in sea surface temperature as well as subsurface temperature are reduced, and the total ocean heat content exhibits a trend closer to that observed in a recent ocean reanalysis (ORAS4) when wave effects are included. Seasonal integrations of the coupled atmosphere-wave-ocean model consisting of NEMO, the wave model ECWAM and the atmospheric model of ECMWF similarly show that the sea surface temperature biases are greatly reduced when the mixing is controlled by the sea state and properly weighted by the thickness of the uppermost level of the ocean model. These wave-related physical processes were recently implemented in the operational coupled ensemble forecast system of ECMWF.