Sensitivity of cyclone produced ocean mixing to the Langmuir turbulence: a modeling study

The oceanic surface boundary layer (OSBL) is a turbulent region which acts as an intermediate layer between the lower atmosphere and the deeper ocean. This layer helps in exchanging mass and momentum. The wave driven physical process in OSBL named as, Langmuir turbulence affects the turbulent mixing. Langmuir circulations are coherent structures in the mixed layer that produce counter rotating vortices with axis parallel to the wind which creates turbulence. Turbulence boundary layer mixing processes are a sub grid scale processes in ocean general circulation model (OGCM) and so, it requires parameterization. In most of the traditional OGCM, the Langmuir turbulence are not been taking into account properly. So, this needs to be parameterized to simulate shear produced mixing properly, especially in the cyclone time. When a cyclone passes through a location the near surface ocean currents and surface waves are high. Then the large vertical shear below the developing currents generates turbulence and deepen the OSBL. Modular Ocean Model version 5 (MOM5), developed by NOAA, GFDL with .25° horizontal resolution and 50 vertical levels has been used for this study. Spin up has been done for 50 years to get the dynamic stability using the Co-ordinated ocean ice reference experiment (CORE) climatological forcing. The mixing scheme used in MOM5 is K Profile Parameterization (KPP). The diffusivity profile of temperature and momentum is estimated as the product of boundary layer depth, the vertical velocity scale and one non dimensional shape function. This non dimensional shape function is cubic by its default setup. Two different experiments have been set in MOM5 for validation using the JRA55-do forcing. JRA55-do is the Japanese Reanalysis dataset for driving ocean models. It’s horizontal resolution is .5° and temporal resolution is 3 hour. The study region is Tropical Indian Ocean (TIO: 40°E-100°E, 25°S-25°N). Control run (CTRL) has been done with the default shape function and experiment run (EXP) with the revised shape function for the period 2007-2023. Every cyclone from 2007 to 2023 has been analyzed with respect to RAMA buoy data. Previous studies have reported surface cold bias and subsurface warm bias in OGCM. The temperature bias has been decreased by 0.8\degc-0.9\degc as mean and standard deviation is 1.8\degc-2\degc near 80m-100m depth. The RMSE for temperature bias has been decreased by 0.70C-0.80C near 80m-100m depth which leads to the reduction in density profile bias 0.3-0.4(kg/m3) and the RMSE of bias has been decreased by 0.15-0.4 near 80m-100m. Reduction in temperature bias and error in subsurface leads to reduction in bias/error in density (.3/.4). This resulted into realistic representation of subsurface stratification in the model. Study concludes that incorporation of Langmuir turbulence by modifying the shape function in KPP improves mixing processes which nullify the known subsurface warming by 25%-30% under the cyclone conditions.