journal article
Open Access
Feb 09, 2026
Monsoons, plumes, and blooms: intraseasonal variability of subsurface primary productivity in the Bay of Bengal
Abstract
Abstract. During the southwest monsoon, seasonal storms bring torrential rainfall to the South Asian subcontinent and the northern Indian Ocean. Dense cloud cover limits the amount of sunlight that reaches the ocean surface, and sediment-laden river runoff limits the depths to which light can penetrate. Changing light availability should affect phytoplankton primary productivity and its dependent biogeochemical processes, yet little is known about how subtropical weather is linked to ecosystem processes below the ocean’s surface. Here, using novel physical and bio-optical measurements from an array of free-drifting, autonomous systems in the Bay of Bengal, we show that the onset of cloudy conditions associated with “active” monsoon conditions led to >50 % reduction in gross chlorophyll productivity (GCP) near the subsurface chlorophyll maximum (SCM) relative to sunny “break” conditions. Optical backscatter measurements confirm chlorophyll fluorescence fluctuations correspond to biomass variability of a similar scale. Simultaneous bioacoustic measurements collected onboard the autonomous platforms suggest this intraseasonal variability in SCM chlorophyll and biomass generated a response in higher trophic levels. Long-term measurements from biogeochemical (BGC) Argo floats in the bay confirm the presence of intraseasonal oscillations in chlorophyll a concentration with days-to-weeks variability in magnitude similar to the regional annual cycle in the region. Our findings demonstrate that intraseasonal subtropical air-sea variability modulates important regional biogeochemical ocean processes in the Northern Indian Ocean with implications for the Indian Ocean carbon cycle.
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References
52
[1]
Antoine, D., André, J.-M., and Morel, A.: Oceanic primary production 2. Estimation at global scale from satelite (coastal zone color scanner) chlorophyll, Global Biogeochem. Cy., 10, 57–60, https://doi.org/10.1029/2003GL016889, 1996. a
10.1029/95gb02832
[2]
Argo: Argo float data and metadata from Global Data Assembly Centre (Argo GDAC), SEANOE [data set], https://doi.org/10.17882/42182, 2000. a, b
10.17882/42182
[3]
Barone, B., Nicholson, D., Ferrón, S., Firing, E., and Karl, D.: The estimation of gross oxygen production and community respiration from autonomous time-series measurements in the oligotrophic ocean, Limnol. Oceanogr.: Meth., 17, 650–664, https://doi.org/10.1002/lom3.10340, 2019. a, b, c, d
10.1002/lom3.10340
[4]
Britton, C. and Dodd, J.: Relationships of photosynthetically active radiation and shortwave irradiance, Agricult. Meteorol., 17, 1–7, https://doi.org/10.1016/0002-1571(76)90080-7, 1976. a
10.1016/0002-1571(76)90080-7
[5]
Cornec, M., Claustre, H., Mignot, A., Guidi, L., Lacour, L., Poteau, A., D'Ortenzio, F., Gentili, B., and Schmechtig, C.: Deep Chlorophyll Maxima in the Global Ocean: Occurrences, Drivers and Characteristics, Global Biogeochem. Cy., 35, 1–30, https://doi.org/10.1029/2020GB006759, 2021. a
10.1029/2020gb006759
[6]
Cullen, J. J.: The Deep Chlorophyll Maximum: Comparing Vertical Profiles of Chlorophyll a, Can. J. Fish. Aquat. Sci., 39, 791–803, https://doi.org/10.1139/f82-108, 1982. a
10.1139/f82-108
[7]
Cullen, J. J.: Subsurface chlorophyll maximum layers: Enduring enigma or mystery solved?, Annu. Rev. Mar. Sci., 7, 207–239, https://doi.org/10.1146/annurev-marine-010213-135111, 2015. a
10.1146/annurev-marine-010213-135111
[8]
Davis, R. E., Ohman, M. D., Rudnick, D. L., Sherman, J. T., and Hodges, B.: Glider surveillance of physics and biology in the southern California Current System, Limnol. Oceanogr., 53, 2151–2168, https://doi.org/10.4319/lo.2008.53.5_part_2.2151, 2008. a
10.4319/lo.2008.53.5_part_2.2151
[9]
EU Copernicus Marine Service Information: Global Ocean Physics Reanalysis, EU Copernicus Marine Service Information [data set], https://doi.org/10.48670/moi-00021, 2026. a
[10]
Frenzel, H., Sharp, J., Fassbender, A., and Buzby, N.: OneArgo-Mat: A MATLAB toolbox for accessing and visualizing Argo data, Zenodo [code], https://doi.org/10.5281/zenodo.6588042, 2020. a
[11]
Gadgil, S., Rajeevan, M., and Nanjundiah, R.: Monsoon prediction – Why yet another failure?, Curr. Sci., 88, 1389–1400, 2005. a, b, c
[12]
Gastauer, S., Nickels, C. F., and Ohman, M. D.: Body size- and season-dependent diel vertical migration of mesozooplankton resolved acoustically in the San Diego Trough, Limnol. Oceanogr., 67, 300–313, https://doi.org/10.1002/lno.11993, 2022. a, b, c, d
10.1002/lno.11993
[13]
Girishkumar, M. S., Ravichandran, M., McPhaden, M. J., and Rao, R. R.: Intraseasonal variability in barrier layer thickness in the south central Bay of Bengal, J. Geophys. Res.-Oceans, 116, https://doi.org/10.1029/2010JC006657, 2011. a
10.1029/2010jc006657
[14]
Goddard Space Flight Center and Ocean Ecology Laboratory: Moderate-resolution Imaging Spectroradiometer (MODIS) Aqua Downwelling Diffuse Attenuation Coefficient Data; 2018 Reprocessing, NASA OB.DAAC [data set], https://doi.org/10.5067/ORBVIEW-2/SEAWIFS/L2/OC/2018, 2018a. a, b
[15]
Gray, A. R., Johnson, K. S., Bushinsky, S. M., Riser, S. C., Russell, J. L., Talley, L. D., Wanninkhof, R., Williams, N. L., and Sarmiento, J. L.: Autonomous Biogeochemical Floats Detect Significant Carbon Dioxide Outgassing in the High-Latitude Southern Ocean, Geophys. Res. Lett., 45, 9049–9057, https://doi.org/10.1029/2018GL078013, 2018. a
10.1029/2018gl078013
[16]
Hansell, D. A.: Dissolved organic carbon in the carbon cycle of the Indian Ocean, Geophys. Monogr. Ser., 185, 217–230, https://doi.org/10.1029/2007GM000684, 2009. a
10.1029/2007gm000684
[17]
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Sabater, J. M., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2018. a, b
[18]
Johnson, K. S. and Bif, M. B.: Constraint on net primary productivity of the global ocean by Argo oxygen measurements, Nat. Geosci., 14, 769–774, https://doi.org/10.1038/s41561-021-00807-z, 2021. a, b, c, d, e
10.1038/s41561-021-00807-z
[19]
Johnson, K. S., Plant, J. N., Coletti, L. J., Jannasch, H. W., Sakamoto, C. M., Riser, S. C., Swift, D. D., Williams, N. L., Boss, E., Haëntjens, N., Talley, L. D., and Sarmiento, J. L.: Biogeochemical sensor performance in the SOCCOM profiling float array, J. Geophys. Res.-Oceans, 122, 6416–6436, https://doi.org/10.1002/2017JC012838, 2017. a
10.1002/2017jc012838
[20]
Kerhalkar, S., Tandon, A., Farrar, J., MacKinnon, J. A., Schlosser, T. L., Johnson, L., Lucas, A. J., Hormann, V., and Centurioni, L. R.: Modulation of Diurnal SST and Diurnal Warm Layer Variability by Salinity-Driven Stratification in the Bay of Bengal, J. Phys. Oceanogr., 56, 245–266, https://doi.org/10.1175/jpo-d-25-0134.1, 2025. a
10.1175/jpo-d-25-0134.1
[21]
Kumar, S. P., Narvekar, J., Nuncio, M., Kumar, A., Ramaiah, N., Sardesai, S., Gauns, M., Fernandes, V., and Paul, J.: Is the biological productivity in the Bay of Bengal light limited?, Curr. Sci., 98, 1331–1339, 2010a. a, b
[22]
Kumar, S. P., Nuncio, M., Narvekar, J., Ramaiah, N., Sardesai, S., Gauns, M., Fernandes, V., Paul, J. T., Jyothibabu, R., and Jayaraj, K. A.: Seasonal cycle of physical forcing and biological response in the Bay of Bengal, Ind. J. Mar. Sci., 39, 388–405, 2010b. a
[23]
Lavery, A. C., Wiebe, P. H., Stanton, T. K., Lawson, G. L., Benfield, M. C., and Copley, N.: Determining dominant scatterers of sound in mixed zooplankton populations, J. Acoust. Soc. Am., 122, 3304–3326, https://doi.org/10.1121/1.2793613, 2007. a, b, c, d
10.1121/1.2793613
[24]
Lucas, A., Nash, J., Pinkel, R., MacKinnon, J., Tandon, A., Mahadevan, A., Omand, M., Freilich, M., Sengupta, D., Ravichandran, M., and Boyer, A. L.: Adrift Upon a Salinity-Stratified Sea: A View of Upper-Ocean Processes in the Bay of Bengal During the Southwest Monsoon, Oceanography, 29, 134–145, https://doi.org/10.5670/oceanog.2016.46, 2016. a, b, c
10.5670/oceanog.2016.46
[25]
Malan, N., Archer, M., Roughan, M., Cetina-Heredia, P., Hemming, M., Rocha, C., Schaeffer, A., Suthers, I., and Queiroz, E.: Eddy-Driven Cross-Shelf Transport in the East Australian Current Separation Zone, J. Geophys. Res.-Oceans, 125, 1–15, https://doi.org/10.1029/2019JC015613, 2020. a
10.1029/2019jc015613
[26]
Mandke, S. K., Pillai, P. A., and Sahai, A. K.: Simulation of monsoon intra-seasonal oscillations in Geophysical Fluid Dynamics Laboratory models from Atmospheric Model Intercomparison Project integrations of Coupled Model Intercomparison Project phase 5, Int. J. Climatol., 40, 5574–5589, https://doi.org/10.1002/joc.6536, 2020. a, b, c
10.1002/joc.6536
[27]
Marra, J.: Analysis of diel variability in chlorophyll fluorescence, J. Mar. Res., 55, 767–784, https://doi.org/10.1357/0022240973224274, 1997. a, b, c, d
10.1357/0022240973224274
[28]
Mignot, A., Claustre, H., Uitz, J., Poteau, A., D'Ortenzio, F., and Xing, X.: Understanding the seasonal dynamics of phytoplankton biomass and the deep chlorophyll maximum in oligotrophic environments: A Bio-Argo float investigation, Global Biogeochem. Cy., 28, 856–876, https://doi.org/10.1002/2013GB004781, 2014. a, b, c
10.1002/2013gb004781
[29]
Mishra, D. R., Narumalani, S., Rundquist, D., and Lawson, M.: Characterizing the vertical diffuse attenuation coefficient for downwelling irradiance in coastal waters: Implications for water penetration by high resolution satellite data, ISPRS J. Photogram. Remote Sens., 60, 48–64, https://doi.org/10.1016/j.isprsjprs.2005.09.003, 2005. a
10.1016/j.isprsjprs.2005.09.003
[30]
Morel, A., Huot, Y., Gentili, B., Werdell, P. J., Hooker, S. B., and Franz, B. A.: Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach, Remote Sens. Environ., 111, 69–88, https://doi.org/10.1016/j.rse.2007.03.012, 2007. a, b
10.1016/j.rse.2007.03.012
[31]
Müller, P., Li, X. P., and Niyogi, K. K.: Non-photochemical quenching. A response to excess light energy, Plant Physiol., 125, 1558–1566, https://doi.org/10.1104/pp.125.4.1558, 2001. a, b
10.1104/pp.125.4.1558
[32]
NASA Goddard Space Flight Center and Ocean Ecology Laboratory: Moderate-resolution Imaging Spectroradiometer (MODIS) Aqua Photosynthetically Available Radiation Data; 2018 Reprocessing, NASA OB.DAAC [data set], https://doi.org/10.5067/AQUA/MODIS/L3M/PAR/2018, 2018. a, b
[33]
NASA Goddard Space Flight Center, Ocean Ecology Laboratory, and Ocean Biology Processing Group: MODIS-Aqua Ocean Color Data, NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group [data set], https://doi.org/10.5067/AQUA/MODIS/L3M/KD490/2018, 2014a. a
[34]
NASA Goddard Space Flight Center, Ocean Ecology Laboratory, and Ocean Biology Processing Group: MODIS-Aqua Ocean Color Data, NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group [data set], https://doi.org/10.5067/AQUA/MODIS/L3M/CHL/2018, 2014b. a
[35]
Nicholson, D. P., Wilson, S. T., Doney, S. C., and Karl, D. M.: Quantifying subtropical North Pacific gyre mixed layer primary productivity from Seaglider observations of diel oxygen cycles, Geophys. Res. Lett., 42, 4032–4039, https://doi.org/10.1002/2015GL063065, 2015. a, b, c, d, e
10.1002/2015gl063065
[36]
Ohman, M. D., Davis, R. E., Sherman, J. T., Grindley, K. R., Whitmore, B. M., Nickels, C. F., and Ellen, J. S.: Zooglider: An autonomous vehicle for optical and acoustic sensing of zooplankton, Limnol. Oceanogr.: Meth., 17, 69–86, https://doi.org/10.1002/lom3.10301, 2019. a, b, c, d
10.1002/lom3.10301
[37]
Pinkel, R., Goldin, M. A., Smith, J. A., Sun, O. M., Aja, A. A., Bui, M. N., and Hughen, T.: The Wirewalker: A vertically profiling instrument carrier powered by ocean waves, J. Atmos. Ocean. Tech., 28, 426–435, https://doi.org/10.1175/2010JTECHO805.1, 2011. a, b
10.1175/2010jtecho805.1
[38]
Prasanth, R., Vijith, V., and Vinayachandran, P. N.: Formation, maintenance and diurnal variability of subsurface chlorophyll maximum during the summer monsoon in the southern Bay of Bengal, Prog. Oceanogr., 212, 102974, https://doi.org/10.1016/j.pocean.2023.102974, 2023. a, b, c, d, e, f, g, h, i, j, k, l
10.1016/j.pocean.2023.102974
[39]
Sarma, V. V., Krishna, M. S., Rao, V. D., Viswanadham, R., Kumar, N. A., Kumari, T. R., Gawade, L., Ghatkar, S., and Tari, A.: Sources and sinks of CO2 in the west coast of Bay of Bengal, Tellus B, 64, 10961, https://doi.org/10.3402/tellusb.v64i0.10961, 2012. a
10.3402/tellusb.v64i0.10961
[40]
An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)
Shubha Sathyendranath, Robert Brewin, Carsten Brockmann et al.
Sensors
10.3390/s19194285
[41]
Sathyendranath, S., Jackson, T., Brockmann, C., Brotas, V., Calton, B., Chuprin, A., Clements, O., Cipollini, P., Danne, O., Dingle, J., Donlon, C., Donlon, C., Groom, S., Krasemann, H., Lavender, S., Mazeran, C., Mélin, F., Müller, D., Steinmetz, F., Valente, A., Zühlke, M., Feldman, G., Franz, B., Frouin, R., Werdell, J., and Platt, T.: ESA Ocean Colour Climate Change Initiative (Ocean-Colour-cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a geographic projection at 4km resolution, Version 6.0, https://catalogue.ceda.ac.uk/uuid/8ecae26f390b4938b67a97cbce3ecd8b/ (last access: 10 December 2025), 2023. a, b, c
[42]
Schlosser, T. L.: dielFit – adapted to accept PAR inputs, Zenodo [code], https://doi.org/10.5281/zenodo.18409716, 2026. a
[43]
Schlosser, T. L., Lucas, A. J., Jones, N. L., Nash, J. D., and Ivey, G. N.: Local winds and encroaching currents drive summertime subsurface blooms over a narrow shelf, Limnol. Oceanogr., 67, 888–902, https://doi.org/10.1002/lno.12043, 2022. a
10.1002/lno.12043
[44]
Schmechtig, C., Poteau, A., Claustre, H., D'Ortenzio, F., Dall'Olmo, G., and Boss, E.: Processing BGC-Argo particle backscattering at the DAC level. Version 1.4, 07 March 2018, Tech. rep., IFREMER for Argo Data Management, https://doi.org/10.13155/39459, 2018. a
[45]
Shroyer, E., Tandon, A., Sengupta, D., Fernando, H. J., Lucas, A. J., Farrar, J. T., Chattopadhyay, R., de Szoeke, S., Flatau, M., Rydbeck, A., Wijesekera, H., McPhaden, M., Seo, H., Subramanian, A., Venkatesan, R., Joseph, J., Ramsundaram, S., Gordon, A. L., Bohman, S. M., Pérez, J., Simoes-Sousa, I. T., Jayne, S. R., Todd, R. E., Bhat, G., Lankhorst, M., Schlosser, T., Adams, K., Jinadasa, S., Mathur, M., Mohapatra, M., Rao, E. P. R., Sahai, A. K., Sharma, R., Lee, C., Rainville, L., Cherian, D., Cullen, K., Centurioni, L. R., Hormann, V., MacKinnon, J., Send, U., Anutaliya, A., Waterhouse, A., Black, G. S., Dehart, J. A., Woods, K. M., Creegan, E., Levy, G., Kantha, L. H., and Subrahmanyam, B.: Bay of Bengal Intraseasonal Oscillations and the 2018 Monsoon Onset, B. Am. Meteorol. Soc., 102, E1936–E1951, https://doi.org/10.1175/bams-d-20-0113.1, 2021. a, b, c, d, e
10.1175/bams-d-20-0113.1
[46]
Thadathil, P., Muraleedharan, P. M., Rao, R. R., Somayajulu, Y. K., Reddy, G. V., and Revichandran, C.: Observed seasonal variability of barrier layer in the Bay of Bengal, J. Geophys. Res.-Oceans, 112, https://doi.org/10.1029/2006JC003651, 2007. a
10.1029/2006jc003651
[47]
Todd, R. E., Rudnick, D. L., and Davis, R. E.: Monitoring the greater San Pedro Bay region using autonomous underwater gliders during fall of 2006, J. Geophys. Res.-Oceans, 114, 1–13, https://doi.org/10.1029/2008JC005086, 2009. a
10.1029/2008jc005086
[48]
Uchida, T., Balwada, D., Abernathey, R., Prend, C. J., Boss, E., and Gille, S. T.: Southern Ocean Phytoplankton Blooms Observed by Biogeochemical Floats, J. Geophys. Res.-Oceans, 124, 7328–7343, https://doi.org/10.1029/2019JC015355, 2019. a, b, c
10.1029/2019jc015355
[49]
Weller, R., Farrar, J. T., Buckley, J., Matthew, S., Venkatesan, R., Lekha, J. S., Chaudhuri, D., Kumar, N. S., and Kuman, B. P.: Air-Sea Interaction in the Bay of Bengal, Oceanography, 29, 28–37, https://doi.org/10.5670/oceanog.2016.36, 2016. a
10.5670/oceanog.2016.36
[50]
White, A. E., Barone, B., Letelier, R. M., and Karl, D. M.: Productivity diagnosed from the diel cycle of particulate carbon in the North Pacific Subtropical Gyre, Geophys. Res. Lett., 44, 3752–3760, https://doi.org/10.1002/2016GL071607, 2017. a
10.1002/2016gl071607
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- Published
- Feb 09, 2026
- Vol/Issue
- 22(1)
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Funding
National Science Foundation
Award: NSF 2048491
Office of Naval Research
Award: N00014-17-1-2391
Cite This Article
Tamara L. Schlosser, Andrew J. Lucas, Melissa Omand, et al. (2026). Monsoons, plumes, and blooms: intraseasonal variability of subsurface primary productivity in the Bay of Bengal. Ocean Science, 22(1), 443-458. https://doi.org/10.5194/os-22-443-2026
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