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<p>The impact of intense turbulence-driven upper ocean mixing during tropical cyclones plays a crucial role in shaping the upper ocean’s thermohaline structure. Achieving appropriate mixing processes in the ocean general circulation model to accurately simulate the thermohaline structure is a challenging task. Modular Ocean Model version 5 (MOM5) based two experiments are carried out. In the first experiment (CTRL) default K profile parameterization (KPP) scheme is used and in the second experiment (EXP), upgraded KPP scheme is utilized by modified diffusivity profile using higher order shape function. This enable us to examine the impact of upgraded KPP on upper ocean thermohaline structure simulation associated with tropical cyclone, the Hudhud that occurred during October 2014. Both experiments are conducted using the JRA55-do forcing for the period of 2009–2023 and model simulations are compared with RAMA buoy data. Results showed a reduction in biases for surface and subsurface temperature, mixed layer depth, oceanic heat content, thermocline depth when used modified shape function. The enhanced diffusivity in the upper ocean and its suppression in deeper layers improve temperature stratification. This, along with improved vertical shear of horizontal currents, enhances the representation of vertical heat advection, leading to a more accurate simulation of temperature tendency. Variance of vertical turbulence heat flux confirms that CTRL overestimates turbulence than EXP, leads to excess mixing resulted a warm bias about 4 to 5&#xa0;°C in CTRL around 90 to 110&#xa0;m depth, which is reduced to 2 to 2.5&#xa0;°C in EXP. Thus, modified shape function effectively reduced the overestimation of upper ocean mixing and typically lowered the subsurface warmer bias in Bay of Bengal even during cyclone. This case study brought out the importance of the revised KPP formulation to reduce the subsurface warm bias under the cyclonic conditions.</p>

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Simulation of upper ocean temperature under the cyclone condition: a sensitivity to shape function in KPP mixing parameterisation

  • 期刊论文

  • 发表日期：

    2026年3月13日

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  • Soma Mishra,
  • Anant Parekh,
  • Krishna R Phani Murali,
  • Jasti S. Chowdary

摘要

The impact of intense turbulence-driven upper ocean mixing during tropical cyclones plays a crucial role in shaping the upper ocean’s thermohaline structure. Achieving appropriate mixing processes in the ocean general circulation model to accurately simulate the thermohaline structure is a challenging task. Modular Ocean Model version 5 (MOM5) based two experiments are carried out. In the first experiment (CTRL) default K profile parameterization (KPP) scheme is used and in the second experiment (EXP), upgraded KPP scheme is utilized by modified diffusivity profile using higher order shape function. This enable us to examine the impact of upgraded KPP on upper ocean thermohaline structure simulation associated with tropical cyclone, the Hudhud that occurred during October 2014. Both experiments are conducted using the JRA55-do forcing for the period of 2009–2023 and model simulations are compared with RAMA buoy data. Results showed a reduction in biases for surface and subsurface temperature, mixed layer depth, oceanic heat content, thermocline depth when used modified shape function. The enhanced diffusivity in the upper ocean and its suppression in deeper layers improve temperature stratification. This, along with improved vertical shear of horizontal currents, enhances the representation of vertical heat advection, leading to a more accurate simulation of temperature tendency. Variance of vertical turbulence heat flux confirms that CTRL overestimates turbulence than EXP, leads to excess mixing resulted a warm bias about 4 to 5 °C in CTRL around 90 to 110 m depth, which is reduced to 2 to 2.5 °C in EXP. Thus, modified shape function effectively reduced the overestimation of upper ocean mixing and typically lowered the subsurface warmer bias in Bay of Bengal even during cyclone. This case study brought out the importance of the revised KPP formulation to reduce the subsurface warm bias under the cyclonic conditions.