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Global trends in ocean fronts and impacts on the air–sea CO2 flux and chlorophyll concentrations

Nature Climate Change (2026)Cite this article

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Abstract

Ocean fronts are critical features that influence marine ecosystems and can affect climate at both regional and global scales. In many regions, fronts enhance vertical mixing and advection, increasing nutrient supply, which can stimulate primary production and modulate air–sea CO2 fluxes. However, a global perspective on the impacts of changing ocean fronts on primary production and air–sea CO2 exchange is still lacking. Here using satellite observations (2003–2024) and supplementary reanalysis data at higher latitudes (2003–2024), we identify areas with the richest frontal activity and the fastest-changing frontal properties. We find that 72% of global ocean CO2 uptake occurs in key frontal areas. Trends in sea surface chlorophyll concentration and ocean CO2 uptake closely track changes in local frontal activity. Our results indicate that ocean fronts play a central role in regulating the global carbon cycle by influencing the biological component of air–sea CO2 fluxes.

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Fig. 1: Annual frontal frequency at each MODIS pixel location for 2024.
Fig. 2: Global frontal areas and their mean values and trends (2003–2024).
Fig. 3: MODIS-based frontal activity distribution: density, frequency and strength.
Fig. 4: MODIS-based linear trends of global frontal activity: density, frequency and strength.
Fig. 5: Chlorophyll a concentrations by area for the 2003–2024 period.
Fig. 6: Air–sea CO2 fluxes by area.

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Data availability

NASA MODIS-Aqua daily SST data (MODIS_AQUA_L3_SST_MID-IR_DAILY_4KM_NIGHTTIME_V2019.0) are distributed by NASA Physical Oceanography Distributed Active Archive Center (https://podaac.jpl.nasa.gov/, https://doi.org/10.5067/MODAM-1D4N9)75. MODIS-Aqua monthly chlorophyll a concentration data (Aqua/MODIS level 3 mapped chlorophyll data version 2022) are available from NASA Ocean Color (https://oceancolor.gsfc.nasa.gov/, https://doi.org/10.5067/AQUA/MODIS/L3M/CHL/2022.0)76. C3S daily reprocessed SST data (C3S-GLO-SST-L4-REP-OBS-SST) are available from the EU Copernicus Marine Service (https://marine.copernicus.eu/, https://doi.org/10.48670/moi-00169)77. Model-based CO2 flux data are available via Zenodo at https://doi.org/10.5281/zenodo.10222483 (ref. 78) and monthly pCO2 data can also be downloaded from the EU Copernicus Marine Service (https://marine.copernicus.eu/, https://doi.org/10.48670/moi-00047)79. Source data are provided with this paper.

Code availability

The Cayula–Cornillon algorithm (frontal detection method) was applied using the module ‘Oceanographic Analysis’ embedded in the Marine Geospatial Ecology Tools (MGET), v.0.8a75, released on 8 April 2021, which integrates with ArcGIS. The MGET toolbox67 is available at Duke Marine Geospatial Ecology Lab (https://mgel.env.duke.edu). Trend and significance analyses were performed using code published by Martínez-Moreno et al.80, available via Zenodo at https://doi.org/10.5281/zenodo.4458783 and https://doi.org/10.5281/zenodo.4458776 (refs. 81,82). All Jupyter Notebook scripts used to produce figures are available and regularly updated via Zenodo at https://doi.org/10.5281/zenodo.13943854) (ref. 83).

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Acknowledgements

K.Y. acknowledges financial support from the University of Tasmania and the China Scholarship Council (CSC) of the Ministry of Education of the People’s Republic of China (grant no. 202006330006). K.Y., A.M. and P.G.S. were supported by the Australian Research Council (ARC) Centre of Excellence for Climate Extremes (CLEX; ARC grant no. CE170100023) and Centre of Excellence for 21st Century Weather (ARC grant no. CE230100012). A.M. was also supported by the Australian Research Council Discovery Early Career Researcher Award project DE200100414. We are grateful for the freely available MODIS SST and chlorophyll a concentration data products from NASA OBPG and the reprocessed SST product from the EU Copernicus Marine Service. We acknowledge the Global Carbon Project, which produced the Global Carbon Budget with the CO2 flux estimates used in this study and we thank the ocean modelling and fCO2-mapping groups for making their model and fCO2-product outputs available. We also thank J. Hauck from the Alfred Wegener Institute (AWI) for providing suggestions about the Global Carbon Budget data product. K.Y. also acknowledges the State Key Laboratory of Marine Environmental Science (MEL) and the College of Ocean and Earth Sciences at Xiamen University (XMU), China, for providing support, including short-term funding and access to facilities, during the later stages of this study.

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Authors and Affiliations

  1. Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Tasmania, Australia

    Kai Yang, Amelie Meyer, Phuc T. D. Le, Peter G. Strutton & Andrew M. Fischer

  2. Australian Research Council Centre of Excellence for Climate Extremes, University of Tasmania, Hobart, Tasmania, Australia

    Kai Yang, Amelie Meyer & Peter G. Strutton

  3. State Key Laboratory of Marine Environmental Science & College of Ocean and Earth Sciences, Xiamen University, Xiamen, China

    Kai Yang

  4. AMC Search, Australian Maritime College, University of Tasmania, Newnham, Tasmania, Australia

    Andrew M. Fischer

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Contributions

K.Y. designed, performed the experiment, wrote the code, analysed the data and wrote the paper. A.M. designed the experiment and contributed to writing the paper. P.T.D.L. analysed data and contributed to writing the paper. P.G.S. and A.M.F. contributed to writing the paper. All authors discussed the results and implications and commented on the paper at all stages.

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Correspondence to Kai Yang.

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Nature Climate Change thanks Prasanjit Dash, Yackar Mauzole and Peter Miller for their contributions to the peer review of this work.

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Extended data

Extended Data Table 1 Spearman’s rank correlation coefficients (ρ) between frontal metrics (frequency, density, and strength), chlorophyll-a (Chl-a) concentration, and air-sea CO2 flux (FCO2) across areas
Full size table

Extended Data Fig. 1 Temporal coverage of Aqua-MODIS daily sea surface temperature (SST) data from 2003 to 2024.

Hatched areas indicate areas with more than 80% data availability. Only grid cells within 60°N–60°S were included in the main analysis.

Extended Data Fig. 2 Spatial distribution of surface partial pressure of CO2 (pCO2) in seawater.

Panel a: estimated non-thermal pCO2 for 2024, with key frontal areas (black contours), intensifying frontal areas (red contours), and declining frontal areas (blue contours). Panel b: area-averaged non-thermal pCO2 for 2024. Non-thermal pCO2 is the temperature-corrected component of seawater pCO2, isolating the influence of biological activity, vertical mixing, and other non-thermal processes. Lower values indicate enhanced biological CO2 uptake or weakened upwelling of CO2-rich waters, whereas higher values reflect stronger non-thermal CO2 sources.

Extended Data Fig. 3 Temporal changes in key, intensifying, and declining frontal areas.

Panel a: annual area (million km2) of the key frontal areas with the corresponding linear trend (dashed line; Theil-Sen). Panel b: annual area (million km2) of intensifying (red) and declining (blue) frontal areas, computed using a 5-year rolling window, with their linear trends (dashed lines; Theil-Sen). Trend slopes, reported as % per year, quantify the average relative change in area per year, referenced to the first year (panel a) or the first 5-year rolling window (panel b). None of the estimated trends are statistically significant.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2, Table 1 and discussion.

Source data

Source Data Fig. 2

Statistical source data; slope data.

Source Data Fig. 3

Zonal mean data.

Source Data Fig. 4

Zonal mean data.

Source Data Fig. 5

Zonal mean data; statistical source data; slope data.

Source Data Fig. 6

Area data; statistical source data; slope data.

Source Data Extended Data Fig. 3

Time series data.

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Yang, K., Meyer, A., Le, P.T.D. et al. Global trends in ocean fronts and impacts on the air–sea CO2 flux and chlorophyll concentrations. Nat. Clim. Chang. (2026). https://doi.org/10.1038/s41558-025-02538-0

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