Multi‐Scale Temporal Variability of Turbulent Mixing During a Monsoon Intra‐Seasonal Oscillation in the Bay of Bengal: An LES Study. Issue 1 (19th January 2023)

• Record Type: Journal Article
• Authors: Pham, Hieu T.; Sarkar, Sutanu; Johnson, Leah; Fox‐Kemper, Baylor; Sullivan, Peter P.; Li, Qing
• Is Part Of: Journal of geophysical research. Volume 128:Issue 1(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-01-19
• Subjects: Monsoon intra‐seasonal Oscillations -- Langmuir turbulence -- large‐eddy simulations -- ocean mixed layer -- turbulence parameterization; Oceanography -- Periodicals; 551.4605
• DOI: 10.1029/2022JC018959
• Languages: English
• ISSNs: 2169-9275

Abstract

Abstract: A process study using large‐eddy simulations is carried out to explore the dominant 1‐D processes that affect mixed layer (ML) properties during an event of summer Monsoon Intra‐seasonal Oscillations (MISO) in the Bay of Bengal (BOB). These simulations use realistic air‐sea fluxes and initial conditions that were collected during the summer 2018 MISO‐BOB field experiment to explore the roles of thermal inversion layer (TIL) and Langmuir turbulence (LT) in modulating ML properties. The simulations span an active period with heavy rain and strong winds and a break period with strong solar heat flux and little rain. The mixed layer depth (MLD), sea surface temperature (SST) and sea surface salinity (SSS) are most affected by the presence of near‐inertial oscillations, solar heating and precipitation, all of which occur at different timescales. The subsurface warming induced by the TIL reduces the SST variability at the MISO timescale when compared with the simulation without TIL. Comparison of simulations with and without LT indicates that LT enhances subsurface warming during the active phase and reduces diurnal SST modulation during the break phase. Simulations with 1‐D mixing models show a wide disparity in the evolution of MLD, SST, and SSS. Plain Language Summary: Monsoon rain affects the lives of the more than a billion people in the Indian subcontinent. Increasing the prediction skill of monsoon forecasting models requires understanding how different weather events mix heat in the upper ocean. This study evaluates the different roles of observed rain, cooling, wind, solar warming and waves on mixing for two different ocean conditions. Motivated by recent observations in the Bay of Bengal, one condition includes warm water near the surface and cooler at depth and the other condition includes anomalous heat at depth. During the monsoon onset, surface cooling, winds and waves can release the anomalous heat, causing sea surface temperature to increase rather than decrease. Warmer water at the air‐sea interface leads to stronger evaporation and thus affects the intensity of monsoon rain. Our large‐eddy simulation study suggests that resolving subsurface processes and including the enhanced mixing effect of surface waves can potentially improve the prediction skill of forecast models, and thus, warrant further attention in the future studies. Key Points: Near‐inertial oscillation, solar heating and precipitation are dominant 1D processes that set mixed layer properties during the 2018 MISO event Preconditioning by a thermal inversion inside a barrier layer during the Monsoon Intra‐seasonal Oscillations (MISO) event can reduce the sea surface temperature (SST) variability at the MISO timescale Large‐eddy simulations with and without Langmuir effects show enhanced subsurface warming and reduced SST variability in the mixed layer in the former