Abstract
The ocean’s surface layer has a crucial role in Earth’s climate, absorbing excess atmospheric heat, thereby regulating global temperatures. Here, using global daily sea surface temperature (SST) data, we document a notable increase in the persistence of SST anomalies across the global ocean since 1982. This trend is also evident in frequency space, showing a decreased variance in SSTs on timescales shorter than a month, but a slight increase on longer timescales. A simple stochastic model attributes this prolonged memory to three key factors––a deepening of the surface mixed layer, a weakening of oceanic forcing and reduced damping rates. The first two factors decrease the variance on shorter timescales, while the third increases it on longer timescales. Our findings have great relevance to the observed increase in the duration of marine heatwaves and the associated heightened thermal threats to marine organisms. Our study also suggests that the ocean’s ability to sequester heat is weakening.
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Data availability
Details regarding the source database utilized in this study can be found at the following URLs: https://doi.org/10.5067/GHAAO-4BC21 (ref. 52) and https://doi.org/10.24381/cds.bd0915c6 (ref. 38). The global maps illustrating the trend and climatology MLD fields discussed in this paper are available via Zenodo at https://doi.org/10.5281/zenodo.4073174 (ref. 53).
Code availability
The analytical code employed for the results and Supplementary Information in this paper can be accessed at https://github.com/ChaehyeongLee/ThermalMemory.git (ref. 54).
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Acknowledgements
H.S. was supported by a National Research Foundation of Korea grant funded by the Korean government (2018R1A5A1024958 and 2022R1A2C1009792). J.M. was supported by the Physical Oceanography program of the National Aeronautics and Space Administration (6945064) and the Massachusetts Institute of Technology–Goddard Institute for Space Studies cooperative agreement.
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H.S. designed the study. C.L. and H.S. performed the analysis. C.L. created the figures. Y.C., A.C. and J.M. helped in the investigation. C.L. wrote the original draft and C.L., H.S., Y.C. and J.M. reviewed and edited the paper.
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Extended data
Extended Data Fig. 1 The mean memory timescales obtained by fitting an arctangent function.
a-e. The mean memory timescales (\(\overline{\tau }\)) of SST anomalies over a 42-year period (1982-2023). Optimal coefficients for the arctangent function are determined using 2, 5, 10, 20, and 30 consecutive autocorrelation coefficients of SST anomalies, spanning from 0-lag to the lag (n − 1).
Extended Data Fig. 2 The trend in the mean memory timescales obtained by fitting an arctangent function.
a-e. The linear trend of the memory timescale is calculated using the same arctangent model used to produce the means shown in Extended Data Fig. 1a–e. from 1982 to 2023, respectively.
Extended Data Fig. 3 Mean damping coefficients.
a-b. Mean atmospheric (λa) and mean oceanic (λo) damping coefficient over the last 42 years. The atmospheric damping coefficient is decomposed into three contributions: c. long-wave radiation (λrad), d. sensible heat flux (λsh), and e. latent heat flux (λlh). The units are in W m−2 K−1.
Extended Data Fig. 4 Power spectra of atmospheric forcing.
a-e. Power spectra of annual atmospheric forcing (\({\hat{F}}_{\omega ,a}^{2}\)) for the five regions, denoted by black boxes in Fig. 1b, are presented in every 10-year interval from 1982 to 2023.
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Supplementary Figs. 1–3 and Table 1.
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Lee, C., Song, H., Choi, Y. et al. Observed multi-decadal increase in the surface ocean’s thermal inertia. Nat. Clim. Chang. 15, 308–314 (2025). https://doi.org/10.1038/s41558-025-02245-w
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DOI: https://doi.org/10.1038/s41558-025-02245-w
