A new physically based parameterization for wind-wave stresses under strong winds

Autor: Royston Fernandes, Marie-Noëlle Bouin, Jean-Luc Redelsperger
Rok vydání: 2021
Předmět:
DOI: 10.5194/egusphere-egu21-15905
Popis: The ability to estimate flux exchanges between the sea-surface and the atmosphere has tremendous importance on weather prediction and climate simulations. These exchanges are influenced by wave processes - growth and decay, and turbulent interactions at the air-sea interface. For momentum, the ensemble of these exchanges is presented as the sea-surface drag (Cd), which increases with (10-m high) wind intensity till about 20-30 m/s, and decreases thereafter. The reason for this decrease remains less understood, mainly due to (i) our inability to explicitly measure the individual wind-wave exchanges, and (ii) the inability of existing semi-empirical parameterizations to explain the Cd behavior. To this end, we developed a physically based stress parameterization for a coupled wind-wave model, capable of reproducing both wave growth and wave breaking stresses at the air-sea interface. The advantage of such a numerical approach, over field experiments, is that it allows us to investigate the different process, under different constraining environments, in-order to disentangle the factors in play on Cd. Our coupled model enables a two-way interaction between the ocean-waves and turbulent flow. and can simulate (i) the main turbulent eddies of the air-flow, and (ii) the wind-wave interactions. After evaluating the model against published field experiments we use it to explore the impact of wave growth and wave-breaking on the Cd under strong winds. Our results demonstrate that under strong winds the air-flow gets separated from the sea-surface, a process associated with wave-breaking, resulting in the turbulent flow sensing a smoother surface as against an actually rough sea surface, thereby decreasing Cd. Finally, our model allows us to investigate the sensitivity of Cd to different influencing factors under strong winds.
Databáze: OpenAIRE