The imprint of marine atmospheric boundary layer (MABL) dynamical structures on sea surface roughness, as seen from Sentinel-1 Synthetic Aperture Radar (SAR) acquisitions, is investigated. We focus on February 13th, 2020, a case study of the EUREC4A (Elucidating the role of clouds-circulation coupling in climate) field campaign. For suppressed conditions, convective rolls imprint on sea surface roughness is confirmed through the intercomparison with MABL turbulent organization deduced from airborne measurements. A discretization of the SAR wide swath into 25 x 25 km$^2$ tiles then allows us to capture the spatial variability of the turbulence organization varying from rolls to cells. Secondly, we objectively detect cold pools within the SAR image and combine them with geostationary brightness temperature. The geometrical or physically-based metrics of cold pools are correlated to cloud properties. This provides a promising methodology to analyze the dynamics of convective systems as seen from below and above.

When wind blows over the ocean, short wind-waves (of wavelength smaller than 10 meters) are generated, rapidly reaching an equilibrium with the overlying turbulence (at heights lower than 10 meters). Understanding this equilibrium is key to many applications since it determines (i) air-sea fluxes of heat, momentum and gas, essential for numerical models, (ii) energy loss from wind to waves, which regulates how swell is generated and how energy is transferred to the ocean mixed layer and (iii) the ocean surface roughness, visible from remote sensing measurements. Here we review phenomenological models describing this equilibrium: those couple a TKE and wave action budget through several wave-growth processes, including airflow separation events induced by breaking waves. Even though those models aim at reproducing measurements of air-sea fluxes and wave growth, some of the observed variability is still unexplained. Hence, after reviewing several state-of-the-art phe-nomenological models, we discuss recent numerical experiments to give hints about future improvements. We suggest three main directions, which should be addressed both through dedicated experiments and theory: (i) a better quantification of the variability of wind-wave growth and of the role played by the modulation of short and breaking wind-waves by long wind-waves, (ii) an improved understanding of the imprint of wind-waves on turbulent coherent structures and (iii) a quantification of the interscale interactions for a realistic wind-waves sea, where several wind-and-waves coupling processes coexist at multiple time and space scales.

The imprint of marine atmospheric boundary layer (MABL) dynamical structures on sea surface roughness, as seen from Sentinel-1 Synthetic Aperture Radar (SAR) acquisitions, is investigated. We focus on February 13th, 2020, a case study of the EUREC4A (Elucidating the role of clouds-circulation coupling in climate) field campaign. For clear sky conditions, convective rolls and cells imprints on sea surface roughness is confirmed through the intercomparison with MABL turbulent organization deduced from airborne measurements. A discretization of the SAR wide swath into 25 x 25 km$^2$ tiles allows us to capture the spatial variability of the turbulence organization varying from rolls to cells. We then objectively detect cold pools within the SAR image and combine them with geostationary brightness temperature. The geometrical or physically-based metrics of cold pools are correlated to cloud properties. This provides a promising methodology to analyze the dynamics of convective systems as seen from below and above.

Storms propagate over the ocean and create moving patches of strong winds that generate swell systems. Here, we describe the dynamics of wave generation under a moving storm by using a simple parametric model of wave development, forced by a temporally- and spatially-varying moving wind field. This framework reveals how surface winds under moving storms determine the origin and amplitude of swell events. Swell systems are expected to originate from locations different than the moving high-wind forcing regions. This is confirmed by a physically-informed optimization method that back-triangulates the common source locations of swell using their dispersion slopes, simultaneously measured at five wave-buoy locations. Hence, the parametric moving fetch model forced with reanalysis winds can predict the displacement between the highest winds and the observed swell source area when forced with reanalysis winds. The model further shows that the storm’s peak wind speed is the key factor determining swell energy since it determines surface wind gradients that lead to the spatial convergence of wave energy into a much smaller area than the wind fetch. This spatial wave energy convergence implies enhanced wave energy dissipation in this focusing area, slightly displaced from the maximum wind locations. This analysis provides an improved understanding of fetches for extra-tropical swell systems and may help to identify biases in swell forecast models, air-sea fluxes, and upper-ocean mixing estimations.