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Rain in tropical cyclones is studied using eight time series of underwater ambient sound at 40–50 kHz with wind speeds up to 45 m s⁻¹beneath three tropical cyclones. At tropical cyclone wind speeds, rain- and wind-generated sound levels are comparable, and therefore rain cannot be detected by sound level alone. A rain detection algorithm that is based on the variations of 5–30-kHz sound levels with periods longer than 20 s and shorter than 30 min is proposed. Faster fluctuations (<20 s) are primarily due to wave breaking, and slower ones (>30 min) are due to overall wind variations. Higher-frequency sound (>30 kHz) is strongly attenuated by bubble clouds. This approach is supported by observations that, for wind speeds < 40 m s⁻¹, the variation in sound level is much larger than that expected from observed wind variations and is roughly comparable to that expected from rain variations. The hydrophone results are consistent with rain estimates by the Tropical Rainfall Measuring Mission (TRMM) satellite and with Stepped-Frequency Microwave Radiometer (SFMR) and radar estimates by surveillance flights. The observations indicate that the rain-generated sound fluctuations have broadband acoustic spectra centered around 10 kHz. Acoustically detected rain events usually last for a few minutes. The data used in this study are insufficient to produce useful estimation of rain rate from ambient sound because of limited quantity and accuracy of the validation data. The frequency dependence of sound variations suggests that quantitative rainfall algorithms from ambient sound may be developed using multiple sound frequencies.

Rain is an indispensable process in forecasting the intensity and path of tropical cyclones. However, its role in the air–sea interaction is still poorly understood, and its parameterization in numerical models is still in development. In this work, we analyzed sound measurements made by hydrophones on board Lagrangian floats beneath tropical cyclones. We find that wind, rain, and breaking waves each have distinctive signatures in underwater ambient sound. We suggest that the air–sea dynamic processes in tropical cyclones can be explored by listening to ambient sound using hydrophones beneath the sea surface.

 

Mixing of the ocean beneath tropical cyclones (TC) cools the surface temperature thereby modifying the storm intensity. Modeling studies predict that surface wave forcing through Langmuir turbulence (LT) increases the mixing and cooling and decreases near‐surface vertical velocity shear. However, there are very few quantitative observational validations of these model predictions, and the validation efforts are often limited by uncertainties in the drag coefficient (C_d). We combine EM‐APEX and Lagrangian float measurements of temperature, salinity, velocity, and vertical turbulent kinetic energy (VKE) from five TCs with a coupled ocean‐wave model (Modular Ocean Model 6—WAVEWATCH III) forced by the drag coefficientC_ddirectly constrained for these storms. On the right‐hand of the storms in the northern hemisphere, where wind and waves are nearly aligned, the measured VKE is consistent with predictions of models including LT and 2–3 times higher than predictions without LT. Similarly, vertical shear in the upper 20 m is small, consistent with predictions of LT models and inconsistent with the large shears predicted by models without LT. On the left‐hand of the storms, where wind and waves are misaligned, the observed VKE and cooling are reduced compared to those on the right‐hand, consistent with the measured decrease inC_d. These results confirm the importance of surface waves for ocean cooling and thus TC intensity, through bothC_dand LT effects. However, the model predictions, even with the LT parameterization, underestimate the upper ocean cooling and mixed layer deepening by 20%–30%, suggesting possible deficiency of the existing LT parameterization.

 

Abstract Acrucial region of the ocean surface boundary layer (OSBL) is the strongly-sheared and -stratified transition layer (TL) separating the mixed layer from the upper pycnocline, where a diverse range of waves and instabilities are possible. Previous work suggests that these different waves and instabilities will lead to different OSBL behaviours. Therefore, understanding which physical processes occur is key for modelling the TL. Here we present observations of the TL from a Lagrangian float deployed for 73 days near Ocean Weather Station Papa (50°N, 145°W) during Fall 2018. The float followed the vertical motion of the TL, continuously measuring profiles across it using an ADCP, temperature chain and salinity sensors. The temperature chain made depth/time images of TL structures with a resolution of 6cm and 3 seconds. These showed the frequent occurrence of very sharp interfaces, dominated by temperature jumps of O(1)°C over 6cm or less. Temperature inversions were typically small (≲ 10cm), frequent, and strongly-stratified; very few large overturns were observed. The corresponding velocity profiles varied over larger length scales than the temperature profiles. These structures are consistent with scouring behaviour rather than Kelvin-Helmholtz-type overturning. Their net effect, estimated via a Thorpe-scale analysis, suggests that these frequent small temperature inversions can account for the observed mixed layer deepening and entrainment flux. Corresponding estimates of dissipation, diffusivity, and heat fluxes also agree with previous TL studies, suggesting that the TL dynamics is dominated by these nearly continuous 10cm-scale mixing structures, rather than by less frequent larger overturns. 

Abstract Monin–Obukhov similarity theory (MOST) provides important scaling laws for flow properties in the surface layer of the atmosphere and has contributed to most of our understanding of the near-surface turbulence. The prediction of near-surface vertical mixing in most operational ocean models is largely built upon this theory. However, the validity of MOST in the upper ocean is questionable due to the demonstrated importance of surface waves in the region. Here we examine the validity of MOST in the statically unstable oceanic surface layer, using data collected from two open ocean sites with different wave conditions. The observed vertical temperature gradients are found to be about half of those predicted by MOST. We hypothesize this is attributable to either the breaking of surface waves, or Langmuir turbulence generated by the wave–current interaction. Existing turbulence closure models for surface wave breaking and for Langmuir turbulence are simplified to test these two hypotheses. Although both models predict reduced temperature gradients, the simplified Langmuir turbulence model matches observations more closely, when appropriately tuned. 

The drag coefficient under tropical cyclones and its dependence on sea states are investigated by combining upper-ocean current observations [using electromagnetic autonomous profiling explorer (EM-APEX) floats deployed under five tropical cyclones] and a coupled ocean–wave (Modular Ocean Model 6–WAVEWATCH III) model. The estimated drag coefficient averaged over all storms is around 2–3 × 10⁻³for wind speeds of 25–55 m s⁻¹. While the drag coefficient weakly depends on wind speed in this wind speed range, it shows stronger dependence on sea states. In particular, it is significantly reduced when the misalignment angle between the dominant wave direction and the wind direction exceeds about 45°, a feature that is underestimated by current models of sea state–dependent drag coefficient. Since the misaligned swell is more common in the far front and in the left-front quadrant of the storm (in the Northern Hemisphere), the drag coefficient also tends to be lower in these areas and shows a distinct spatial distribution. Our results therefore support ongoing efforts to develop and implement sea state–dependent parameterizations of the drag coefficient in tropical cyclone conditions.

 

The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with two ships: a Process Ship, focused on ecological rates, BGC fluxes, temporal changes in food web, and BGC and optical properties, that followed an instrumented Lagrangian float; and a Survey Ship that sampled BGC and optical properties in spatial patterns around the Process Ship. An array of autonomous underwater assets provided measurements over a range of spatial and temporal scales, and partnering programs and remote sensing observations provided additional observational context. The oceanographic setting was typical of late-summer conditions at Ocean Station Papa: a shallow mixed layer, strong vertical and weak horizontal gradients in hydrographic properties, sluggish sub-inertial currents, elevated macronutrient concentrations and low phytoplankton abundances. Although nutrient concentrations were consistent with previous observations, mixed layer chlorophyll was lower than typically observed, resulting in a deeper euphotic zone. Analyses of surface layer temperature and salinity found three distinct surface water types, allowing for diagnosis of whether observed changes were spatial or temporal. The 2018 EXPORTS field deployment is among the most comprehensive biological pump studies ever conducted. A second deployment to the North Atlantic Ocean occurred in spring 2021, which will be followed by focused work on data synthesis and modeling using the entire EXPORTS data set.