DOI: 10.1029/2017JC013637
Scopus记录号: 2-s2.0-85051130179
论文题名: A Modeling Study of Interannual Variability of Bay of Bengal Mixing and Barrier Layer Formation
作者: Valsala V. ; Singh S. ; Balasubramanian S.
刊名: Journal of Geophysical Research: Oceans
ISSN: 21699275
出版年: 2018
卷: 123, 期: 6 起始页码: 3962
结束页码: 3981
语种: 英语
英文关键词: barrier layer depth
; Bay of Bengal
; interannual variability of mixing
; mixed layer depth
; ocean modeling
; turbulent closure model
英文摘要: The year to year variability of surface mixing in the Bay of Bengal (BoB) is examined with the help of an Ocean Dynamic-Thermodynamic Model (ODTM) and observational data. The model embeds a conventional nonlinear primitive equation based reduced gravity model (RGM) with “N” active layers overlying a 1/2 quiescent layer. The model is coupled to a high-resolution mixed layer model (MLM) to capture the physics of the mixed layer. The MLM incorporates a level-2 turbulence closure mixing scheme based on Mellor and Yamada (1982). As a result of the coupling, our model calculates the net hydrostatic pressure as a sum of those due to the thickness of RGM layers with constant densities and due to the dynamic topography of MLM levels with variable densities. At each time step the coupling between RGM and MLM is achieved as follows: (i) a layer-averaged tendency of momentum and tracers (i.e., temperature and salinity) of the MLM is updated to the RGM, (ii) momentum and tracers of the MLM get advected by large-scale horizontal dynamics of the RGM, and (iii) horizontal layer divergence of the RGM aides for the vertical advection of the MLM. By virtue of this coupling, the model faithfully reproduces the seasonal cycle of temperature, salinity, sea surface height, thermocline, mixed and barrier layer thickness of the tropical Indian Ocean. A simulation with Coordinated Ocean-Ice Reference Experiment (CORE) forcing for 15 years (from 1995 to 2009) is used as a test case to study the interannual variability (IAV) of the mixed layer depth and barrier layer thickness (BL) in BoB. The dominant modes of IAV in the BoB mixing are governed by the correspondingly varying surface momentum, heat, and fresh water fluxes with very little contribution from entrainment of heat and/or salt at the base of the mixed layer. Further, these fluxes are controlled by El Niño-Southern Oscillation (ENSO) variability with very little influence from Indian Ocean Dipole-Zonal Mode (IODZM). The BL IAV is predominantly controlled by precipitation forcing from ENSO. A stability analysis revealed that the turbulent kinetic energy (TKE) and the stability function (SH) are negatively correlated when ENSO is the dominant forcing. Such a correlation between TKE and SH is expected since unstable stratification conditions exist during positive ENSO, where the kinetic energy production is enhanced by the unstable buoyancy forcing leading to an increased TKE. During the negative phase of ENSO, stably stratified conditions exist, where the kinetic energy production is offset by the stable buoyancy force, reducing the TKE. This is indicative of high (low) turbulent kinetic energy production, low (high) flux Richardson number based stability function (SH), and low (high) dominance of buoyancy-driven mixing during positive (negative) phases of ENSO. The results highlight that the counteracting influence of TKE and SH is a plausible reason for relatively weaker amplitude of IAV of BoB mixing compared to its normal seasonal cycle. © 2018. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/113828
Appears in Collections: 气候减缓与适应
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作者单位: Training Center, Indian Institute of Tropical Meteorology, Pune, India; Interdisciplinary Programme in Climate Studies, Indian Institute of Technology, Bombay, India; Department of Mechanical Engineering, Indian Institute of Technology, Bombay, India
Recommended Citation:
Valsala V.,Singh S.,Balasubramanian S.. A Modeling Study of Interannual Variability of Bay of Bengal Mixing and Barrier Layer Formation[J]. Journal of Geophysical Research: Oceans,2018-01-01,123(6)