Drag coefficients derived from ocean current and temperature profiles at high wind speeds

Abstract

Two bottom-up methods based on the turbulence closure and bulk model were utilised to estimate drag coefficients at high wind speeds based on ocean current and temperature profiles observed by two subsurface buoys during Typhoon Megi in the South China Sea. A numerical experiment was conducted using the turbulence closure model to test the impact of missing measurements in the upper mixed layer on the wind stress estimate and reconstruction of the upper ocean current. The results were sufficiently robust after several time steps. The wind stresses derived from the two methods were consistent with each other. Wind stress increased quickly with increasing wind force, and then was constant. A parametric typhoon wind model was applied to obtain the wind field and estimate the corresponding drag coefficient. The results showed that the drag coefficient increased to a maximum at a critical wind speed of about 30 m s −1 , and then levelled off with increasing wind speed. The uncertainty of the maximum drag coefficient was about ±0.5 due to neglect of nonlinear terms, the uncertainty of the model wind speeds and the drag coefficient. The critical wind speed for the maximum drag coefficient varied by at least ±5 m s −1 . The uncertainty of the drag coefficient parameterisation was about 24% due to wind speed. These results indicate that a bottom-up method can be used to estimate drag coefficients at the forced stage during the passage of typhoons or hurricanes.

A Review of Parameterizations for Enthalpy and Momentum Fluxes from Sea Spray in Tropical Cyclones

“…Both studies found that the drag coefficient increased and then decreased with wind speed, although the peak C D occurred at slightly different values of U 10 , about 25 m s 21 for French et al (2007) and about 32 m s 21 for Jarosz et al (2007). The results from Jarosz et al (2007) were shown to be very similar to those from a much more recent study by Zou et al (2018) that also used ocean buoy data to estimate the drag coefficient. The first direct measurements of latent heat flux from the hurricane boundary layer were published by Drennan et al (2007); profiles of specific humidity, potential temperature, and wind speed are shown in Fig.…”

Three Types of Typhoon‐Induced Upwellings Enhance Coastal Algal Blooms: A Case Study

“…These data have a six‐hourly temporal resolution and 0.205‐degree spatial resolution. We calculated wind stress according to a revised formula at high wind speeds (Zou et al., 2018): $$$\begin{array}{l}\overrightarrow{\tau }={\rho }_{a}{C}_{D}{U}_{10}{\overrightarrow{U}}_{10}\hfill \end{array}$$$ $$$\begin{array}{l}{C}_{D}=\left(0.10+0.13{U}_{10}-0.0022{U}_{10}^{2}\right)\times {10}^{-3}\hfill \end{array}$$$ where $$\overrightarrow{\tau }$$ is the wind stress, $${\rho }_{a}$$ is the air density, $${\overrightarrow{U}}_{10}$$ is the wind speed at 10 m above the sea surface, and $${C}_{D}$$ is the drag coefficient.…”

“…These data have a six-hourly temporal resolution and 0.205-degree spatial resolution. We calculated wind stress according to a revised formula at high wind speeds (Zou et al, 2018): where 𝐴𝐴 ⃖ ⃗ 𝜏𝜏 is the wind stress, 𝐴𝐴 𝐴𝐴𝑎𝑎 is the air density, 𝐴𝐴 ⃖⃖ ⃗ 𝑈𝑈 10 is the wind speed at 10 m above the sea surface, and 𝐴𝐴 𝐴𝐴𝐷𝐷 is the drag coefficient.…”

A Scheme for Estimating Time-Varying Wind Stress Drag Coefficient in the Ekman Model with Adjoint Assimilation

“…, where h is depth), which has been widely used in ocean models [32][33][34]. The initial guess value of WSDC is set as 1.2 × 10 −3 in all cases.…”