Articles | Volume 18, issue 20
https://doi.org/10.5194/bg-18-5831-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-18-5831-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Oct 2021
Research article |
| 29 Oct 2021
| 29 Oct 2021
Fast local warming is the main driver of recent deoxygenation in the northern Arabian Sea
Zouhair Lachkar
CORRESPONDING AUTHOR
Center for Prototype Climate Modeling, New York University Abu Dhabi, Abu Dhabi, UAE
Michael Mehari
Center for Prototype Climate Modeling, New York University Abu Dhabi, Abu Dhabi, UAE
Muchamad Al Azhar
Center for Prototype Climate Modeling, New York University Abu Dhabi, Abu Dhabi, UAE
Plymouth Marine Laboratory, Plymouth, UK
Marina Lévy
Sorbonne Université (CNRS/IRD/MNHN), LOCEAN-IPSL, Paris, France
Shafer Smith
Center for Prototype Climate Modeling, New York University Abu Dhabi, Abu Dhabi, UAE
Courant Institute of Mathematical Sciences, New York University, New York, USA
Related authors
Said Ouala, Oussama Hidaoui, and Zouhair Lachkar
Earth Syst. Sci. Data, 18, 287–308, https://doi.org/10.5194/essd-18-287-2026, https://doi.org/10.5194/essd-18-287-2026, 2026
Short summary
Short summary
Ocean deoxygenation poses major challenges to marine life and can alter carbon cycling. Direct measurements of dissolved oxygen are sparse, and interpolation methods are needed to study the variability and changes in oxygen content. In this work, we used machine learning to improve estimates of oxygen levels across the global ocean. Our approach produces a new gridded product that captures detailed changes in oxygen over time and space.
Zouhair Lachkar, Olivier Pauluis, Francesco Paparella, Basit Khan, and John A. Burt
Ocean Sci., 21, 3241–3263, https://doi.org/10.5194/os-21-3241-2025, https://doi.org/10.5194/os-21-3241-2025, 2025
Short summary
Short summary
An analysis of model and reanalysis data reveals that extreme summer sea surface temperatures in the Arabian/Persian Gulf are driven by weakened local Shamal winds and intensified monsoon winds over the Arabian Sea. These conditions – typically associated with La Niña and a negative North Atlantic Oscillation phase – increase air moisture over the Gulf and enhance surface heat trapping. The findings offer promising prospects for forecasting summer marine heatwaves in the Gulf.
Said Ouala, Oussama Hidaoui, and Zouhair Lachkar
EGUsphere, https://doi.org/10.5194/egusphere-2025-1771, https://doi.org/10.5194/egusphere-2025-1771, 2025
Preprint withdrawn
Short summary
Short summary
In this study, we develop a novel gridded ocean oxygen concentration product by combining observed oxygen data with emulated measurements derived from temperature and salinity profiles. This approach increases the density of observations, particularly in data-sparse regions, allowing for more accurate oxygen concentration estimates than current state-of-the-art products.
Derara Hailegeorgis, Zouhair Lachkar, Christoph Rieper, and Nicolas Gruber
Biogeosciences, 18, 303–325, https://doi.org/10.5194/bg-18-303-2021, https://doi.org/10.5194/bg-18-303-2021, 2021
Short summary
Short summary
Using a Lagrangian modeling approach, this study provides a quantitative analysis of water and nitrogen offshore transport in the Canary Current System. We investigate the timescales, reach and structure of offshore transport and demonstrate that the Canary upwelling is a key source of nutrients to the open North Atlantic Ocean. Our findings stress the need for improving the representation of the Canary system and other eastern boundary upwelling systems in global coarse-resolution models.
Said Ouala, Oussama Hidaoui, and Zouhair Lachkar
Earth Syst. Sci. Data, 18, 287–308, https://doi.org/10.5194/essd-18-287-2026, https://doi.org/10.5194/essd-18-287-2026, 2026
Short summary
Short summary
Ocean deoxygenation poses major challenges to marine life and can alter carbon cycling. Direct measurements of dissolved oxygen are sparse, and interpolation methods are needed to study the variability and changes in oxygen content. In this work, we used machine learning to improve estimates of oxygen levels across the global ocean. Our approach produces a new gridded product that captures detailed changes in oxygen over time and space.
Zouhair Lachkar, Olivier Pauluis, Francesco Paparella, Basit Khan, and John A. Burt
Ocean Sci., 21, 3241–3263, https://doi.org/10.5194/os-21-3241-2025, https://doi.org/10.5194/os-21-3241-2025, 2025
Short summary
Short summary
An analysis of model and reanalysis data reveals that extreme summer sea surface temperatures in the Arabian/Persian Gulf are driven by weakened local Shamal winds and intensified monsoon winds over the Arabian Sea. These conditions – typically associated with La Niña and a negative North Atlantic Oscillation phase – increase air moisture over the Gulf and enhance surface heat trapping. The findings offer promising prospects for forecasting summer marine heatwaves in the Gulf.
Mathieu Delteil, Marina Lévy, and Laurent Bopp
EGUsphere, https://doi.org/10.5194/egusphere-2025-2805, https://doi.org/10.5194/egusphere-2025-2805, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
The ocean is losing oxygen due to climate change, threatening ecosystems, especially in naturally low-oxygen areas called Oxygen Minimum Zones (OMZs). Using the IPSL-CM6A-LR Large Ensemble, this study identifies when climate-driven changes in OMZ volumes and regional deoxygenation emerge from natural variability. We highlight hemispheric asymmetries due to ocean ventilation and provide model-based estimates for the timing of detectable OMZ evolution.
Marina Lévy, Karina von Schuckmann, Patrick Vincent, Bruno Blanke, Joachim Claudet, Patrice Guillotreau, Audrey Hasson, Claire Jolly, Yunne Shin, Olivier Thébaud, Adrien Vincent, and Pierre Bahurel
State Planet, 6-osr9, 1, https://doi.org/10.5194/sp-6-osr9-1-2025, https://doi.org/10.5194/sp-6-osr9-1-2025, 2025
Short summary
Short summary
The Ocean is vital to humanity, but humans are putting it at risk. The Starfish Barometer is a new yearly civic rendezvous that shows how people and the Ocean affect each other. Using science-based facts, it highlights major trends in ocean health, the pressures it faces, the harm to people, and current protection efforts and opportunities. The goal is to raise awareness to secure a better future for the Ocean and humanity.
Madhavan Girijakumari Keerthi, Olivier Aumont, Lester Kwiatkowski, and Marina Levy
Biogeosciences, 22, 2163–2180, https://doi.org/10.5194/bg-22-2163-2025, https://doi.org/10.5194/bg-22-2163-2025, 2025
Short summary
Short summary
We assessed how well climate models replicate sub-seasonal changes in ocean chlorophyll observed by satellites. Models struggle to capture these variations accurately. Some overestimate fluctuations and their impact on annual chlorophyll variability, while others underestimate them. The underestimation is likely due to limited model resolution, while the overestimation may come from internal model oscillations.
Said Ouala, Oussama Hidaoui, and Zouhair Lachkar
EGUsphere, https://doi.org/10.5194/egusphere-2025-1771, https://doi.org/10.5194/egusphere-2025-1771, 2025
Preprint withdrawn
Short summary
Short summary
In this study, we develop a novel gridded ocean oxygen concentration product by combining observed oxygen data with emulated measurements derived from temperature and salinity profiles. This approach increases the density of observations, particularly in data-sparse regions, allowing for more accurate oxygen concentration estimates than current state-of-the-art products.
Stéphane Doléac, Marina Lévy, Roy El Hourany, and Laurent Bopp
Biogeosciences, 22, 841–862, https://doi.org/10.5194/bg-22-841-2025, https://doi.org/10.5194/bg-22-841-2025, 2025
Short summary
Short summary
The marine biogeochemistry components of Coupled Model Intercomparison Project phase 6 (CMIP6) models vary widely in their process representations. Using an innovative bioregionalization of the North Atlantic, we reveal that this model diversity largely drives the divergence in net primary production projections under a high-emission scenario. The identification of the most mechanistically realistic models allows for a substantial reduction in projection uncertainty.
Roy El Hourany, Juan Pierella Karlusich, Lucie Zinger, Hubert Loisel, Marina Levy, and Chris Bowler
Ocean Sci., 20, 217–239, https://doi.org/10.5194/os-20-217-2024, https://doi.org/10.5194/os-20-217-2024, 2024
Short summary
Short summary
Satellite observations offer valuable information on phytoplankton abundance and community structure. Here, we employ satellite observations to infer seven phytoplankton groups at a global scale based on a new molecular method from Tara Oceans. The link has been established using machine learning approaches. The output of this work provides excellent tools to collect essential biodiversity variables and a foundation to monitor the evolution of marine biodiversity.
Inès Mangolte, Marina Lévy, Clément Haëck, and Mark D. Ohman
Biogeosciences, 20, 3273–3299, https://doi.org/10.5194/bg-20-3273-2023, https://doi.org/10.5194/bg-20-3273-2023, 2023
Short summary
Short summary
Ocean fronts are ecological hotspots, associated with higher diversity and biomass for many marine organisms, from bacteria to whales. Using in situ data from the California Current Ecosystem, we show that far from being limited to the production of diatom blooms, fronts are the scene of complex biophysical couplings between biotic interactions (growth, competition, and predation) and transport by currents that generate planktonic communities with an original taxonomic and spatial structure.
Saeed Hariri, Sabrina Speich, Bruno Blanke, and Marina Lévy
Ocean Sci., 19, 1183–1201, https://doi.org/10.5194/os-19-1183-2023, https://doi.org/10.5194/os-19-1183-2023, 2023
Short summary
Short summary
This work presents a series of studies conducted by the authors on the application of the Lagrangian approach for the connectivity analysis between different ocean locations in an idealized open-ocean model. We assess how the connectivity properties of typical oceanic flows are affected by the fine-scale circulation and discuss the challenges facing ocean connectivity estimates related to the spatial resolution. Our results are important to improve the understanding of marine ecosystems.
Clément Haëck, Marina Lévy, Inès Mangolte, and Laurent Bopp
Biogeosciences, 20, 1741–1758, https://doi.org/10.5194/bg-20-1741-2023, https://doi.org/10.5194/bg-20-1741-2023, 2023
Short summary
Short summary
Phytoplankton vary in abundance in the ocean over large regions and with the seasons but also because of small-scale heterogeneities in surface temperature, called fronts. Here, using satellite imagery, we found that fronts enhance phytoplankton much more where it is already growing well, but despite large local increases the enhancement for the region is modest (5 %). We also found that blooms start 1 to 2 weeks earlier over fronts. These effects may have implications for ecosystems.
Alain de Verneil, Zouhair Lachkar, Shafer Smith, and Marina Lévy
Biogeosciences, 19, 907–929, https://doi.org/10.5194/bg-19-907-2022, https://doi.org/10.5194/bg-19-907-2022, 2022
Short summary
Short summary
The Arabian Sea is a natural CO2 source to the atmosphere, but previous work highlights discrepancies between data and models in estimating air–sea CO2 flux. In this study, we use a regional ocean model, achieve a flux closer to available data, and break down the seasonal cycles that impact it, with one result being the great importance of monsoon winds. As demonstrated in a meta-analysis, differences from data still remain, highlighting the great need for further regional data collection.
Damien Couespel, Marina Lévy, and Laurent Bopp
Biogeosciences, 18, 4321–4349, https://doi.org/10.5194/bg-18-4321-2021, https://doi.org/10.5194/bg-18-4321-2021, 2021
Short summary
Short summary
An alarming consequence of climate change is the oceanic primary production decline projected by Earth system models. These coarse-resolution models parameterize oceanic eddies. Here, idealized simulations of global warming with increasing resolution show that the decline in primary production in the eddy-resolved simulations is half as large as in the eddy-parameterized simulations. This stems from the high sensitivity of the subsurface nutrient transport to model resolution.
Derara Hailegeorgis, Zouhair Lachkar, Christoph Rieper, and Nicolas Gruber
Biogeosciences, 18, 303–325, https://doi.org/10.5194/bg-18-303-2021, https://doi.org/10.5194/bg-18-303-2021, 2021
Short summary
Short summary
Using a Lagrangian modeling approach, this study provides a quantitative analysis of water and nitrogen offshore transport in the Canary Current System. We investigate the timescales, reach and structure of offshore transport and demonstrate that the Canary upwelling is a key source of nutrients to the open North Atlantic Ocean. Our findings stress the need for improving the representation of the Canary system and other eastern boundary upwelling systems in global coarse-resolution models.
Cited articles
Al-Ansari, E. M., Rowe, G., Abdel-Moati, M., Yigiterhan, O., Al-Maslamani, I.,
Al-Yafei, M., Al-Shaikh, I., and Upstill-Goddard, R.: Hypoxia in the central
Arabian Gulf Exclusive Economic Zone (EEZ) of Qatar during summer season,
Estuarine, Coast. Shelf Sci., 159, 60–68, 2015. a
Al-Rashidi, T. B., El-Gamily, H. I., Amos, C. L., and Rakha, K. A.: Sea surface
temperature trends in Kuwait bay, Arabian Gulf, Nat. Hazard., 50, 73–82,
2009. a
Al-Yamani, F. and Naqvi, S.: Chemical oceanography of the Arabian Gulf, Deep-Sea Res. Pt. II, 161, 72–80, 2019. a
Bange, H. W., Naqvi, S. W. A., and Codispoti, L.: The nitrogen cycle in the
Arabian Sea, Prog. Oceanogr., 65, 145–158, 2005. a
Banse, K., Naqvi, S. W. A., Narvekar, P. V., Postel, J. R., and Jayakumar, D. A.: Oxygen minimum zone of the open Arabian Sea: variability of oxygen and nitrite from daily to decadal timescales, Biogeosciences, 11, 2237–2261, https://doi.org/10.5194/bg-11-2237-2014, 2014. a
Barnier, B., Siefridt, L., and Marchesiello, P.: Thermal forcing for a global
ocean circulation model using a three-year climatology of ECMWF analyses,
J. Mar. Syst., 6, 363–380, 1995. a
Bianchi, D., Galbraith, E. D., Carozza, D. A., Mislan, K., and Stock, C. A.:
Intensification of open-ocean oxygen depletion by vertically migrating
animals, Nat. Geosci., 6, 545–548, 2013. a
Bindoff, N. L., Cheung, W. W. L., Kairo, J. G., Arístegui, J., Guinder, V. A., Hallberg, R., Hilmi, N., Jiao, N., Karim, M. S., Levin, L., O’Donoghue, S., Purca Cuicapusa, S. R., Rinkevich, B., Suga, T., Tagliabue, A., and Williamson, P., 2019: Changing Ocean, Marine Ecosystems, and Dependent Communities, in: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H.-O., Roberts, D.C., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N. M., 447–588, 2019. a, b, c, d, e
Bograd, S. J., Buil, M. P., Di Lorenzo, E., Castro, C. G., Schroeder, I. D.,
Goericke, R., Anderson, C. R., Benitez-Nelson, C., and Whitney, F. A.:
Changes in source waters to the Southern California Bight, Deep-Sea Res.
Pt. II, 112, 42–52, 2015. a
Bopp, L., Resplandy, L., Orr, J. C., Doney, S. C., Dunne, J. P., Gehlen, M., Halloran, P., Heinze, C., Ilyina, T., Séférian, R., Tjiputra, J., and Vichi, M.: Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models, Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, 2013. a, b
Boyer, T. P., Baranova, O. K., Coleman, C., Garcia, H. E., Grodsky, A., Locarnini, R. A., A., Mishonov, V., Paver, C. R., Reagan, J. R., Seidov, D., Smolyar, I. V., Weathers, K., and Zweng, M. M.: World Ocean Database 2018, A. V. Mishonov, Technical Editor, NOAA Atlas NESDIS 87, available at: https://www.ncei.noaa (last access: 1 August 2021), 2019. a
Breitburg, D., Levin, L. A., Oschlies, A., Grégoire, M., Chavez, F. P., Conley, D. J., Garçon, V., Gilbert, D., Gutiérrez, D., Isensee, K., Jacinto, G. S., Limburg, K. E., Montes, I., Naqvi, S. W. A., Pitcher, G. C., Rabalais, N. N., Roman, M. R., Rose, K. A., and Seibel, B. A.: Declining oxygen in the global ocean and coastal waters, Science,
359, 6371, https://doi.org/10.1126/science.aam7240, 2018. a
Burt, J. A., Paparella, F., Al-Mansoori, N., Al-Mansoori, A., and Al-Jailani,
H.: Causes and consequences of the 2017 coral bleaching event in the southern
Persian/Arabian Gulf, Coral Reefs, 38, 567–589, 2019. a
Carton, J. A. and Giese, B. S.: A reanalysis of ocean climate using Simple
Ocean Data Assimilation (SODA), Mon. Weather Rev., 136, 2999–3017,
2008. a
Chaidez, V., Dreano, D., Agusti, S., Duarte, C. M., and Hoteit, I.: Decadal
trends in Red Sea maximum surface temperature, Sci. Rep., 7, 1–8,
2017. a
Codispoti, L., Brandes, J. A., Christensen, J., Devol, A., Naqvi, S., Paerl,
H. W., and Yoshinari, T.: The oceanic fixed nitrogen and nitrous oxide
budgets: Moving targets as we enter the anthropocene?, Sci. Mar., 65,
85–105, 2001. a
Cummins, P. F. and Ross, T.: Secular trends in water properties at Station P in
the northeast Pacific: an updated analysis, Prog. Oceanogr., 186,
102329, https://doi.org/10.1016/j.pocean.2020.102329, 2020. a
Dai, A. and Trenberth, K. E.: Estimates of freshwater discharge from
continents: Latitudinal and seasonal variations, J. Hydrometeorol.,
3, 660–687, 2002. a
deCastro, M., Sousa, M., Santos, F., Dias, J., and Gómez-Gesteira, M.: How
will Somali coastal upwelling evolve under future warming scenarios?,
Sci. Rep., 6, 1–9, 2016. a
Deutsch, C., Berelson, W., Thunell, R., Weber, T., Tems, C., McManus, J., Crusius, J., Ito, T., Baumgartner, T., Ferreira, V., Mey, J., and van Geen, A.: Centennial
changes in North Pacific anoxia linked to tropical trade winds, Science, 345,
665–668, 2014. a
Deutsch, C., Ferrel, A., Seibel, B., Pörtner, H.-O., and Huey, R. B.:
Climate change tightens a metabolic constraint on marine habitats, Science,
348, 1132–1135, 2015. a
do Rosário Gomes, H., Goes, J. I., Matondkar, S. P., Buskey, E. J., Basu,
S., Parab, S., and Thoppil, P.: Massive outbreaks of Noctiluca scintillans
blooms in the Arabian Sea due to spread of hypoxia, Nat. Commun., 5,
1–8, 2014. a
Frölicher, T. L., Rodgers, K. B., Stock, C. A., and Cheung, W. W.: Sources
of uncertainties in 21st century projections of potential ocean ecosystem
stressors, Global Biogeochem. Cy., 30, 1224–1243, 2016. a
Fu, W., Primeau, F., Keith Moore, J., Lindsay, K., and Randerson, J. T.:
Reversal of increasing tropical ocean hypoxia trends with sustained climate
warming, Global Biogeochem. Cy., 32, 551–564, 2018. a
Garcia, H. E. and Gordon, L. I.: Oxygen solubility in seawater: Better fitting
equations, Limnol. Oceanogr., 37, 1307–1312, 1992. a
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Baranova, O. K., Zweng, M. M., Reagan, J. R., and Johnson, D. R.: World Ocean Atlas 2013, Vol. 3, Dissolved Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation, edited by: Levitus, S., A. Mishonov Technical Ed., NOAA Atlas NESDIS 75, 27 pp., 2014a. a
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Baranova, O.K., Zweng, M. M., Reagan, J. R., and Johnson, D. R.: World Ocean Atlas 2013, Vol. 4, Dissolved Inorganic Nutrients (phosphate, nitrate, silicate), edied by: Levitus, S., A. Mishonov Technical Ed., NOAA Atlas NESDIS 76, 25 pp., 2014b. a
Gobler, C. J. and Baumann, H.: Hypoxia and acidification in ocean ecosystems:
coupled dynamics and effects on marine life, Biol. Lett., 12, 20150976, https://doi.org/10.1098/rsbl.2015.0976,
2016. a
Gopika, S., Izumo, T., Vialard, J., Lengaigne, M., Suresh, I., and Kumar,
M. R.: Aliasing of the Indian Ocean externally-forced warming spatial pattern
by internal climate variability, Clim. Dynam., 54, 1093–1111, 2020. a
Griffies, S. M., Danabasoglu, G., Durack, P. J., Adcroft, A. J., Balaji, V., Böning, C. W., Chassignet, E. P., Curchitser, E., Deshayes, J., Drange, H., Fox-Kemper, B., Gleckler, P. J., Gregory, J. M., Haak, H., Hallberg, R. W., Heimbach, P., Hewitt, H. T., Holland, D. M., Ilyina, T., Jungclaus, J. H., Komuro, Y., Krasting, J. P., Large, W. G., Marsland, S. J., Masina, S., McDougall, T. J., Nurser, A. J. G., Orr, J. C., Pirani, A., Qiao, F., Stouffer, R. J., Taylor, K. E., Treguier, A. M., Tsujino, H., Uotila, P., Valdivieso, M., Wang, Q., Winton, M., and Yeager, S. G.: OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project, Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, 2016. a
Gruber, N., Frenzel, H., Doney, S. C., Marchesiello, P., McWilliams, J. C.,
Moisan, J. R., Oram, J. J., Plattner, G.-K., and Stolzenbach, K. D.:
Eddy-resolving simulation of plankton ecosystem dynamics in the California
Current System, Deep-Sea Res. Pt. I, 53,
1483–1516, 2006. a
Guieu, C., Al Azhar, M., Aumont, O., Mahowald, N., Lévy, M., Éthé,
C., and Lachkar, Z.: Major impact of dust deposition on the productivity of
the Arabian Sea, Geophys. Res. Lett., 46, 6736–6744, 2019. a
Hameau, A., Mignot, J., and Joos, F.: Assessment of time of emergence of anthropogenic deoxygenation and warming: insights from a CESM simulation from 850 to 2100 CE, Biogeosciences, 16, 1755–1780, https://doi.org/10.5194/bg-16-1755-2019, 2019. a
Huang, B., Liu, C., Banzon, V., Freeman, E., Graham, G., Hankins, B., Smith,
T., and Zhang, H.-M.: Improvements of the daily optimum interpolation sea
surface temperature (DOISST) version 2.1, J. Clim., 34, 2923–2939,
2021. a
Kendall, M. G.: Rank correlation methods, 4th Edn., Griffin, London, 160 pp., 1948. a
Koné, V., Aumont, O., Lévy, M., and Resplandy, L.: Physical and biogeochemical controls of the phytoplankton seasonal cycle in the Indian Ocean: a modeling study, in: Indian Ocean Biogeochemical Processes and Ecological Variability, edited by: Wiggert, J. D., Hood, R. R., Wajih, S., Naqvi, A., Brink, K. H., and Smith, S. L., Washington, DC, American Geophysical Union, Geophysical Monograph no. 185, 147–66, https://doi.org/10.1029/2008GM000700, 2009. a
Krishna, M., Prasad, M., Rao, D., Viswanadham, R., Sarma, V., and Reddy, N.:
Export of dissolved inorganic nutrients to the northern Indian Ocean from the
Indian monsoonal rivers during discharge period, Geochim. Cosmochim.
Ac., 172, 430–443, 2016. a
Kumar, S. P., Roshin, R. P., Narvekar, J., Kumar, P. D., and Vivekanandan, E.:
Response of the Arabian Sea to global warming and associated regional climate
shift, Mar. Environ. Res., 68, 217–222, 2009. a
Kwiatkowski, L., Torres, O., Bopp, L., Aumont, O., Chamberlain, M., Christian, J. R., Dunne, J. P., Gehlen, M., Ilyina, T., John, J. G., Lenton, A., Li, H., Lovenduski, N. S., Orr, J. C., Palmieri, J., Santana-Falcón, Y., Schwinger, J., Séférian, R., Stock, C. A., Tagliabue, A., Takano, Y., Tjiputra, J., Toyama, K., Tsujino, H., Watanabe, M., Yamamoto, A., Yool, A., and Ziehn, T.: Twenty-first century ocean warming, acidification, deoxygenation, and upper-ocean nutrient and primary production decline from CMIP6 model projections, Biogeosciences, 17, 3439–3470, https://doi.org/10.5194/bg-17-3439-2020, 2020. a, b
Lachkar, Z., Smith, S., Lévy, M., and Pauluis, O.: Eddies reduce
denitrification and compress habitats in the Arabian Sea, Geophys.
Res. Lett., 43, 9148–9156, 2016. a
Large, W. G. and Yeager, S. G.: Diurnal to decadal global forcing for ocean and
sea-ice models: The data sets and flux climatologies, University Corporation for Atmospheric Research, https://doi.org/10.5065/D6KK98Q6, 2004. a
Large, W. G., McWilliams, J. C., and Doney, S. C.: Oceanic vertical mixing: A
review and a model with a nonlocal boundary layer parameterization, Rev. Geophys., 32, 363–403, 1994. a
Levin, L. A.: Manifestation, drivers, and emergence of open ocean
deoxygenation, Annual review of marine science, 10, 229–260, 2018. a
Long, M. C., Deutsch, C., and Ito, T.: Finding forced trends in oceanic oxygen,
Global Biogeochem. Cy., 30, 381–397, 2016. a
Mann, H. B.: Nonparametric tests against trend, Econometrica, J.
Econom. Soc., 13, 245–259, https://doi.org/10.2307/1907187, 1945. a
Marchesiello, P., Debreu, L., and Couvelard, X.: Spurious diapycnal mixing in
terrain-following coordinate models: The problem and a solution, Ocean
Model., 26, 156–169, 2009. a
McCreary, J. P., Yu, Z., Hood, R. R., Vinaychandran, P., Furue, R., Ishida, A.,
and Richards, K. J.: Dynamics of the Indian-Ocean oxygen minimum zones,
Prog. Oceanogr., 112, 15–37, 2013. a
Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S., and Donion, C.:
Sea surface temperature datasets for climate applications from Phase 1 of the
European Space Agency Climate Change Initiative (SST CCI), Geosci. Data
J., 1, 179–191, 2014. a
Miller, S. H., Breitburg, D. L., Burrell, R. B., and Keppel, A. G.:
Acidification increases sensitivity to hypoxia in important forage fishes,
Mar. Ecol. Prog. Ser., 549, 1–8, 2016. a
Oschlies, A., Koeve, W., Landolfi, A., and Kähler, P.: Loss of fixed
nitrogen causes net oxygen gain in a warmer future ocean, Nat.
Commun., 10, 1–7, 2019. a
Piontkovski, S. and Al-Oufi, H.: The Omani shelf hypoxia and the warming
Arabian Sea, Int. J. Environ. Stud., 72, 256–264,
2015. a
Praveen, V., Ajayamohan, R., Valsala, V., and Sandeep, S.: Intensification of
upwelling along Oman coast in a warming scenario, Geophys. Res.
Lett., 43, 7581–7589, 2016. a
Queste, B. Y., Vic, C., Heywood, K. J., and Piontkovski, S. A.: Physical
controls on oxygen distribution and denitrification potential in the north
west Arabian Sea, Geophys. Res. Lett., 45, 4143–4152, 2018. a
Rabalais, N. N., Turner, R. E., and Wiseman Jr., W. J.: Gulf of Mexico hypoxia,
aka “The dead zone”, Ann. Rev. Ecol. Syst., 33,
235–263, 2002. a
Ramesh, R., Purvaja, G., and Subramanian, V.: Carbon and phosphorus transport
by the major Indian rivers, J. Biogeogr., 22, 409–415, 1995. a
Rayner, N., Parker, D. E., Horton, E., Folland, C. K., Alexander, L. V.,
Rowell, D., Kent, E. C., and Kaplan, A.: Global analyses of sea surface
temperature, sea ice, and night marine air temperature since the late
nineteenth century, J. Geophys. Res.-Atmos., 108, 4407, https://doi.org/10.1029/2002JD002670, 2003. a
Resplandy, L., Lévy, M., Bopp, L., Echevin, V., Pous, S., Sarma, V. V. S. S., and Kumar, D.: Controlling factors of the oxygen balance in the Arabian Sea's OMZ, Biogeosciences, 9, 5095–5109, https://doi.org/10.5194/bg-9-5095-2012, 2012. a
Robinson, C.: Microbial respiration, the engine of ocean deoxygenation,
Front. Mar. Sci., 5, 533, https://doi.org/10.3389/fmars.2018.00533, 2019. a
Schott, F. A., Xie, S.-P., and McCreary Jr., J. P.: Indian Ocean circulation and
climate variability, Rev. Geophys., 47, RG1002, https://doi.org/10.1029/2007RG000245, 2009. a
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling system
(ROMS): a split-explicit, free-surface, topography-following-coordinate
oceanic model, Ocean Model., 9, 347–404, 2005. a
Sooraj, K., Terray, P., and Mujumdar, M.: Global warming and the weakening of
the Asian summer monsoon circulation: assessments from the CMIP5 models,
Climate Dynamics, 45, 233–252, 2015. a
Stewart, K., Kim, W., Urakawa, S., Hogg, A. M., Yeager, S., Tsujino, H.,
Nakano, H., Kiss, A., and Danabasoglu, G.: JRA55-do-based repeat year forcing
datasets for driving ocean–sea-ice models, Ocean Model., 147, 101557, https://doi.org/10.1016/j.ocemod.2019.101557,
2020. a
Stramma, L., Johnson, G. C., Sprintall, J., and Mohrholz, V.: Expanding
oxygen-minimum zones in the tropical oceans, Science, 320, 655–658, 2008. a
Strong, A. E., Liu, G., Skirving, W., and Eakin, C. M.: NOAA's Coral Reef Watch
program from satellite observations, Ann. GIS, 17, 83–92, 2011. a
Swapna, P., Jyoti, J., Krishnan, R., Sandeep, N., and Griffies, S.:
Multidecadal weakening of Indian summer monsoon circulation induces an
increasing northern Indian Ocean sea level, Geophys. Res. Lett., 44,
10560–10572, https://doi.org/10.1002/2017GL074706, 2017. a, b
Vallivattathillam, P., Iyyappan, S., Lengaigne, M., Ethé, C., Vialard, J., Levy, M., Suresh, N., Aumont, O., Resplandy, L., Naik, H., and Naqvi, W.: Positive Indian Ocean Dipole events prevent anoxia off the west coast of India, Biogeosciences, 14, 1541–1559, https://doi.org/10.5194/bg-14-1541-2017, 2017. a
Vaquer-Sunyer, R. and Duarte, C. M.: Thresholds of hypoxia for marine
biodiversity, P. Natl. Acad. Sci. USA, 105,
15452–15457, 2008. a
Wang, B., Liu, J., Kim, H.-J., Webster, P. J., Yim, S.-Y., and Xiang, B.:
Northern Hemisphere summer monsoon intensified by mega-El Niño/southern
oscillation and Atlantic multidecadal oscillation, P.
Natl. Acad. Sci., 110, 5347–5352, 2013. a
Short summary
This study documents and quantifies a significant recent oxygen decline in the upper layers of the Arabian Sea and explores its drivers. Using a modeling approach we show that the fast local warming of sea surface is the main factor causing this oxygen drop. Concomitant summer monsoon intensification contributes to this trend, although to a lesser extent. These changes exacerbate oxygen depletion in the subsurface, threatening marine habitats and altering the local biogeochemistry.
This study documents and quantifies a significant recent oxygen decline in the upper layers of...
Altmetrics
Final-revised paper
Preprint