Exploring the upper ocean characteristics of a bay using coastal and regional ocean community model

Jaishree, D.; Ravichandran, P.T.

doi:10.22034/gjesm.2024.01.08

Document Type : ORIGINAL RESEARCH ARTICLE

Authors

Department of Civil Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur 603203, Chengalpattu District, Tamil Nadu, India

https://doi.org/10.22034/gjesm.2024.01.08

Abstract

BACKGROUND AND OBJECTIVES: The innovativeness of this study lies in achieving a comprehensive understanding of the seasonal variations and oceanic characteristics of the Bay of Bengal by addressing the complex interplay of large-scale ocean-atmosphere dynamics. The study aimed to understand the upper ocean characteristics of the Bay of Bengal by analyzing the surface variables such as salinity and temperature using a high-resolution model simulation. To accomplish this, advanced high-resolution numerical simulations were employed, utilizing the coastal and regional ocean community model. This model was crucial for investigating and analyzing the circulation features throughout the entire Bay of Bengal, contributing knowledge and insights about the coastal and regional oceanographic community.
METHODS: To investigate the temporal variability of the upper ocean in the Bay of Bengal, climatological simulations were performed over eight years using the coastal and regional ocean community model. Including a three-year spin-up phase facilitated the adjustment of the model to initial conditions and the attainment of equilibrium, ensuring its fidelity to real-world conditions. The follow-up analyses and comparisons were performed five years after the spin-up phase. The primary objective of this study was to examine the temporal evolution of the kinetic energy throughout the eight-year simulation. The volume-averaged kinetic energy was computed, revealing a gradual increase throughout the simulation, with particularly pronounced enhancements observed during the monsoon period. A Taylor diagram was used for predicting the model with the other data sets.
FINDINGS: The analysis is performed above the surface and sub-surface oceanic layers with prominent dynamics. The temperature and salinity for the surface and sub-surface layers were validated and analyzed for their seasonal variations. The simulations were validated against the existing satellite, reanalysis, and in situ data.
CONCLUSIONS: The innovativeness of this study lies in its successful demonstration of the seasonal variability of temperature and salinity in the Bay of Bengal. Through extensive validations, it establishes the model to accurately simulate the climatological surface features of the Bay of Bengal. This study highlights the effectiveness of numerical models when combined with observations, and the data were reanalyzed, showcasing their utility as valuable tools for studying oceanic conditions. The utilization of a Taylor diagram further supports the validation and excellent performance of the model compared to other available datasets. During the simulation, there is a high correlation (0.96) between the evolution of the salinity and temperature values obtained from the model and the corresponding data from the World Ocean Atlas. This indicates a strong agreement between the model-based simulations and the assimilated data, as supported by the notable correlation values of 0.96 for salinity and temperature. These findings reinforce the existing knowledge regarding the influential role of monsoon winds in shaping the circulation patterns within the Bay of Bengal. Overall, this study contributes to advancing our understanding of the ocean dynamics of the region and underscores the importance of considering seasonal variations for comprehensive oceanographic research, coastal management, climate modeling, and future studies in the Bay of Bengal.

Graphical Abstract

Highlights

During the Winter and post-monsoon, the open bay of the southern area has high salinity distribution ranging from 34 to 35 psu;
Based on the correlation coefficient values, it is evident that the CROCO model demonstrates a robust positive correlation (0.95) with the WOA dataset, which is considered the benchmark for comparison;
The CROCO model analysis shows that the temperature in the western boundary has a higher range of 27℃ to 28℃ during winter;
Summer heat subsides, the water temperature starts to decrease, particularly with a more pronounced cooling effect observed along the northern side of the bay during post-monsoon.

Keywords

Main Subjects

Marine and coastal environmental pollution and management

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References

Akhter, S.; Qiao, F.; Wu, K.; Yin, X.; Chowdhury, K.M.A.; Chowdhury, N.U.M.K., (2021). Seasonal and long-term sea-level variations and their forcing factors in the northern Bay of Bengal: A statistical analysis of temperature, salinity, wind stress curl, and regional climate index data. Dyn. Atmos. Oceans., 95: 1-23 (23 Pages).

Akhil, V.P.; Durand, F.; Lengaigne, M.; Jerome Vialard, J.; Keerthi, M.G.; Gopalakrishna, V.V.; Deltel, C.; Papa, F.; Ement De Boyer, C.; Egut, M., (2014). A modeling study of the processes of surface salinity seasonal cycle in the Bay of Bengal. J. Geophys. Res. C: Ocean. 119(6): 3926 – 3947 (22 Pages).

Ali, M.M.; Jagadeesh, P.S.V.; Jain, S., (2007). Effects of eddies on Bay of Bengal cyclone intensity. Eos, Trans. Am. Geophys. Union. 88(8): 93-104 (12 Pages).

Amsalia, N.; Haditiar, Y.; Wafdan, R.; Ikhwan, M.; Chaliluddin, M.A.; Sugianto, S.; Rizal, S., (2022). The currents, sea surface temperature, and salinity patterns in the Bay of Bengal. E3S Web of Conferences. 339 02001: 1–7 (7 Pages).

Anandh, T.S.; Das, B.K.; Kumar, B.; Kuttippurath, J.; Chakraborty, A., (2018). Analyses of the oceanic heat content during 1980–2014 and satellite-era cyclones over Bay of BengaI. Int. J. Climatol., 38(15): 5619 –5632 (14 Pages).

Anandh, T. S.; Das, B. K.; Kuttippurath, J.; and Chakraborty, A., (2020). A Comparative Analysis of the Bay of Bengal Ocean State Using Standalone and Coupled Numerical Models. Asia-Pac. J. Atmos. Sci., 57(2), 347–359. (13 Pages).

Chakraborty, A.; Gangopadhyay, A., (2016). Development of a high-resolution multiscale modeling and prediction system for Bay of Bengal, Part I: climatology-based simulations. Open J. Mar. Sci., 6: 145–176 (32 Pages).

Chi, N., (2013). The mixed layer salinity budget in the Central Equatorial Indian Ocean. J. Geophys. Res. C: Oceans., 1–18 (18 Pages).

Collins, M.; An, S.Il, Cai, W.; Ganachaud, A.; Guilyardi, E.; Jin, F.F.; Jochum, M.; Lengaigne, M.; Power, S.; Timmermann, A.; Vecchi, G.; and Wittenberg, A., (2010). The impact of global warming on the tropical Pacific Ocean and El Nĩo. Nat. Geosci., 3(6): 391–397 (17 Pages).

Cherian, D.A.; Shroyer, E.L.; Wijesekera, H.W.; Moum, J.N., (2020). The seasonal cycle of upper-ocean mixing at 8°N in the Bay of Bengal. J. Phys. Oceanogr., 50(2): 323–342 (20 Pages).

Dandapat, S.; Chakraborty, A.; Kuttippurath, J.; Bhagawati, C.; Sen, R., (2021). A numerical study on the role of atmospheric forcing on mixed layer depth variability in the Bay of Bengal using a regional ocean model. Ocean Dyn., 71: 963–979 (17 Pages).

Das, B.K.; Anandh, T.S.; Kuttippurath, J.; Chakraborty, A., (2019). Characteristics of the discontinuity of western boundary current in the Bay of Bengal. J. Geophys. Res. C: Oceans. 124(7): 4464–4479 (16 Pages).

Dey, D.; Sil, S.; Jana, S.; Pramanik, S.; Pandey, P.C., (2017). An assessment of tropflux and NCEP air-sea fluxes on ROMS simulations over the Bay of Bengal region. Dyn. Atmos. Oceans., 80: 47–61 (15 Pages).

Dyn, C., (2010). The Indian summer monsoon pre-onset land surface processes and ‘internal’ interannual variabilities of the Indian summer monsoon. Clim. Dyn., 36: 2077–2089 (13 Pages).

Goswami, B.N.; Ajayamohan, R.S.; Xavier, P.K.; Sengupta, D., (2003). Clustering of synoptic activity by Indian summer monsoon intraseasonal oscillations. Geophys. Res. Lett., 30(8): 1-4 (4 Pages).

Gao, Z.; Hu, Z.Z.; Zhu, J.; Yang, S.; Zhang, R.H.; Xiao, Z.; Jha, B., (2014). Variability of summer rainfall in Northeast China and its connection with spring rainfall variability in the Huang-Huai region and Indian Ocean SST. J. Clim., 27(18): 7086–7101 (16 Pages).

Gordon, A.L.; Mahadevan, A.; Hole, W.; Sengupta, D., (2016). Bay of Bengal: 2013 northeast monsoon upper-ocean circulation. Oceanography. 29(2): 82-91 (10 Pages)

Jana, S.; Gangopadhyay, A.; Chakraborty, A., (2015). Impact of seasonal river input on the Bay of Bengal simulation. Cont Shelf Res 104:45–62(18 Pages).

Jourdain, N.C.; Lengaigne, M.; Vialard, J.R.; Madec, G.; Menkes, C.E.; Vincent, E.M.; Jullien, S.; Barnier, B., (2013). Observation-based estimates of surface cooling inhibition by heavy rainfall under tropical cyclones. J. Phys. Oceanogr., 3(1): 1-17 (17 Pages).

Kikuchi, K.; Wang, B.; Fudeyasu, H., (2009). Genesis of tropical cyclone nargis revealed by multiple satellite observations. Geophys. Res. Lett., 36(6): 1–5 (5 Pages).

Lee, C.M.; Jones, B.H.; Brink, K.H.; Fischer, A.S., (2000). The upper-ocean response to monsoonal forcing in the Arabian Sea: seasonal and spatial variability. Deep Sea Res. Part II. 47(7-8): 1177–1226 (50 Pages).

Lin, I.I.; Chen, C.H.; Pun, I.F.; Liu, W.T.; Wu, C.C., (2009). Warm ocean anomaly, air sea fluxes, and the rapid intensification of tropical cyclone Nargis (2008). Geophys. Res. Lett., 36(3): 2–6 (5 Pages).

Levitus, S.; Antonov, J.I.; Boyer, T.P.; Baranova, O.K.; Garcia, H.E.; Locarnini, R.A.; Mishonov, A.V.; Reagan, J.R.; Seidov, D.; Yarosh, E.S.; Zweng, M.M., (2012). World ocean heat content and thermosteric sea level change (0-2000m), 1955-2010. Geophysical Res. Lett., 39(10): 1–5 (5 Pages).

Liebmann, B.; Hendon, H.; Glick, D., (1994). The relationship and Indian between oceans tropical and the cyclones of the western oscillation pacific by brant liebmann cooperative institute for research in environmental sciences (CIRES), Campus Box 449, University of Colorado, Boulder, Colorado. J. Meteorolog. Soc. Jpn., 72(3): 401–411 (11 Pages).

Maneesha, K.; Ravichandran, M.; Yu, W., (2012). Upper ocean variability in the Bay of Bengal during the tropical cyclones Nargis and Laila. Prog. Oceanogr., 106: 49-61 (13 Pages).

Masumoto, Y.; Hase, H.; Kuroda, Y.; Matsuura, H.; Takeuchi, K., (2005). Intraseasonal variability in the upper layer currents observed in the eastern equatorial Indian Ocean. Geophys. Res. Lett., 32(2): 1–4 (4 Pages).

Mahadevan, A. Hole, W.; Asaro, E.D., (2016). Variability of near-surface circulation and sea surface salinity observed from lagrangian drifters in the northern Bay of Bengal during the waning 2015 southwest monsoon. Oceanography. 29(2): 125-133 (9 Pages).

Rao, S.A.; Saha, S.K.; Pokhrel, S.; Sundar, D.; Dhakate, A.R.; Mahapatra, S.; Ali, S.; Chaudhari, H.S.; Shreeram, P.; Vasimalla, S.; Srikanth, A.S.; Suresh, R.R.V., (2011). Modulation of SST, SSS over northern Bay of Bengal on ISO time scale. J. Geophys. Res. C: Oceans., 116(9): 1-11 (11 Pages).

Rao, S.A.; Behera, S.K., (2005). Subsurface influence on SST in the tropical Indian Ocean: Structure and interannual variability. Dyn. Atmos. Oceans., 39(1-2): (11 Pages).

Roy Chowdhury, R.; Prasanna Kumar, S.; Chakraborty, A., (2021). Simultaneous occurrence of tropical cyclones in the northern Indian ocean: differential response and triggering mechanisms. Front. Mar. Sci., 8: 1-25 (25 Pages).

Schott, F.A.; McCreary, J.P., (2001). The monsoon circulation of the Indian Ocean. Prog. Oceanogr., 1(1): 1-123 (123 Pages).

Schott, F.A.; Xie, S.P.; McCreary, J.P., (2009). Indian ocean circulation and climate variability. Rev. Geophys., 47(1): 1–46 (46 Pages).

Sil, S.; Chakraborty, A., (2012). The mechanism of the 20°C isotherm depth oscillations for the Bay of Bengal, Mar. Geod., 35(3): 233–245 (13 Pages).

Sprintall, J., (2003). Seasonal to interannual upper-ocean variability in the drake passage. J. Mar. Res., 61(1): 27–57 (31 Pages).

Sivareddy, S.; Ravichandran, M.; Girishkumar, M.S.; Prasad, K.V.S.R., (2015). Assessing the impact of various wind forcing on INCOIS-GODAS simulated ocean currents in the equatorial Indian Ocean. Ocean Dyn., 65(9–10): 1235–1247 (13 Pages).

Srivastava, A.; Dwivedi, S.; Mishra, A.K., (2016). Intercomparison of high-resolution Bay of Bengal circulation models forced with different winds. Mar. Geod., 39(3–4): 271–289 (19 Pages).

Srivastava, A.; Dwivedi, S.; Mishra, A.K., (2018). Investigating the role of air-sea forcing on the variability of hydrography, circulation, and mixed layer depth in the Arabian Sea and Bay of Bengal. Oceanologia., 60(2): 169–186 (18 Pages).

Thankaswamy, A.; Xian, T.; Ma, Y.F.; Wang, L.P., (2022). Sensitivity to different reanalysis data on WRF dynamic downscaling for South China sea wind resource estimations. Atmosphere., 13(5), 1–23 (23 Pages).

Ts, A.; Das, B.K.; Kuttippurath, J.; Chakraborty, A., (2020). A coupled model analyses on the interaction between oceanic eddies and tropical cyclones over the Bay of Bengal. Ocean Dyn., 70: 327-337 (11 Pages).

Vinayachandran, P.N.; Satish Shetye, D.S.; Gadgil, S., (1996). Forcing mechanisms of the Bay of Bengal. Current Science., 71(10): 753–763 (11 Pages).

Vinayachandran, P.N.; Julian, J.P.M.; Hood, R.R.; Kohler, K.E., (2014). Numerical investigation of the phytoplankton bloom in the Bay of Bengal during northeast monsoon. J. Geophys. Res., 110(C12): 1-14 (14 Pages).

Webster, P.J.; Magaña, V.O.; Palmer, T.N.; Shukla, J.; Tomas, R.A.; Yanai, M.; Yasunari, T., (1998). Monsoons: processes, predictability, and the prospects for prediction. J. Geophys. Res. C: Oceans. 103(C7): 14451–14510 (60 Pages).

Wu, Z.; Jiang, C.; Deng, B.; Chen, J.; Long, Y.; Qu, K.; Liu, X., (2019). Numerical investigation of typhoon Kai-tak (1213) using a mesoscale coupled WRF-ROMS model. Ocean Eng., 175: 1–15 (15 Pages).

Yadav, M., (2022). South Asian monsoon extremes and climate change, in: Saxena, P., Shukla, A., Gupta, A.K. (Eds.), Extremes in atmospheric processes and phenomenon: assessment, impacts and mitigation. Springer Nature Singapore, Singapore. 59–86 (28 Pages).

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Global Journal of Environmental Science and Management

Exploring the upper ocean characteristics of a bay using coastal and regional ocean community model

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Volume 10, Issue 1 - Serial Number 37
January 2024
Pages 97-116

Exploring the upper ocean characteristics of a bay using coastal and regional ocean community model

References

References

Letters to Editor

Send comment about this article

Volume 10, Issue 1 - Serial Number 37January 2024Pages 97-116

Volume 10, Issue 1 - Serial Number 37
January 2024
Pages 97-116