📝 SummarXiv

Abstract

Accurate representation of atmosphere-ocean boundary layers, including the interplay of turbulence, surface waves, and air-sea fluxes, remains a challenge in geophysical fluid dynamics, particularly for climate simulations. This study introduces a stochastic coupled Ekman-Stokes model (SCESM) developed within the physically consistent Location Uncertainty framework, explicitly incorporating random turbulent fluctuations and surface wave effects. The SCESM integrates established parameterizations for air-sea fluxes, turbulent viscosity, and Stokes drift, and its performance is rigorously assessed through ensemble simulations compared against observations from the LOTUS field experiment. A performance ranking analysis quantifies the impact of different model components, highlighting the critical role of explicit uncertainty representation in both oceanic and atmospheric dynamics for accurately capturing system variability. Among the tested configurations, the full model version -- including both Stokes drift and wave-induced mixing -- shows the best agreement with observations. Wave-induced mixing terms improve model performance, while wave-dependent surface roughness enhances air-sea fluxes but reduces the relative influence of wave-driven mixing. This fully coupled stochastic framework provides a foundation for advancing boundary layer parameterizations in large-scale climate models.