Abstract
The global oceans absorb most of the surplus heat from anthropogenic warming, but it is unclear how this heat accumulation will affect the Earth’s climate under climate mitigation scenarios. Here we show that this stored heat will be released at a much slower rate than its accumulation, resulting in a robust pattern of surface ocean warming and consequent regional precipitation. The surface ocean warming is pronounced over subpolar to polar regions and the equatorial eastern Pacific where oceans are weakly stratified to allow vigorous heat release from the deep ocean to the surface layer. We also demonstrate that this ocean warming pattern largely explains changes in the precipitation pattern, including the southward shift of the Intertropical Convergence Zone and more moistening in high latitudes. This study suggests that deep ocean warming may hinder climate recovery in some regions, even if carbon neutrality or net negative emissions are successfully achieved.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
The data used in this study are available from https://doi.org/10.6084/m9.figshare.24873216.v1 (ref. 61), and the CMIP6 archives are freely available from https://esgf-node.llnl.gov/projects/cmip6.
Code availability
The codes used in this study are available from https://doi.org/10.6084/m9.figshare.24873216.v1 (ref. 61). All figures were generated using Python with the matplotlib and basemap modules (https://matplotlib.org/, https://matplotlib.org/basemap/).
References
Meyssignac, B. et al. Measuring global ocean heat content to estimate the earth energy imbalance. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00432 (2019).
von Schuckmann, K. et al. Heat stored in the Earth system: where does the energy go? Earth Syst. Sci. Data 12, 2013–2041 (2020).
Cheng, L. et al. Improved estimates of ocean heat content from 1960 to 2015. Sci. Adv. 3, e1601545 (2017).
Easterling, D. R. & Wehner, M. F. Is the climate warming or cooling? Geophys. Res. Lett. 36, L08706 (2009).
England, M. H. et al. Recent intensification of wind-driven circulation in the Pacific and the ongoing warming hiatus. Nat. Clim. Change 4, 222–227 (2014).
Meehl, G. A., Arblaster, J. M., Fasullo, J. T., Hu, A. & Trenberth, K. E. Model-based evidence of deep-ocean heat uptake during surface-temperature hiatus periods. Nat. Clim. Change 1, 360–364 (2011).
Cheng, L., Abraham, J., Hausfather, Z. & Trenberth, K. E. How fast are the oceans warming? Science 363, 128–129 (2019).
Cheng, L. et al. Past and future ocean warming. Nat. Rev. Earth Environ. https://doi.org/10.1038/s43017-022-00345-1 (2022).
Held, I. M. et al. Probing the fast and slow components of global warming by returning abruptly to preindustrial forcing. J. Clim. 23, 2418–2427 (2010).
Solomon, S., Plattner, G.-K., Knutti, R. & Friedlingstein, P. Irreversible climate change due to carbon dioxide emissions. Proc. Natl Acad. Sci. USA 106, 1704–1709 (2009).
Frölicher, T. L., Winton, M. & Sarmiento, J. L. Continued global warming after CO2 emissions stoppage. Nat. Clim. Change 4, 40–44 (2014).
Hoegh-Guldberg, O., Jacob, D. & Taylor, M. in IPCC Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) 175–181 (Cambridge Univ. Press, 2018).
Luderer, G. et al. Residual fossil CO2 emissions in 1.5–2 °C pathways. Nat. Clim. Change 8, 626–633 (2018).
Tong, D. et al. Committed emissions from existing energy infrastructure jeopardize 1.5 °C climate target. Nature 572, 373–377 (2019).
Welsby, D., Price, J., Pye, S. & Ekins, P. Unextractable fossil fuels in a 1.5 °C world. Nature 597, 230–234 (2021).
Boucher, O. et al. Reversibility in an Earth System model in response to CO2 concentration changes. Environ. Res. Lett. 7, 024013 (2012).
Garbe, J., Albrecht, T., Levermann, A., Donges, J. F. & Winkelmann, R. The hysteresis of the Antarctic ice sheet. Nature 585, 538–544 (2020).
Jackson, L. C., Schaller, N., Smith, R. S., Palmer, M. D. & Vellinga, M. Response of the Atlantic meridional overturning circulation to a reversal of greenhouse gas increases. Clim. Dyn. 42, 3323–3336 (2014).
Sgubin, G., Swingedouw, D., Drijfhout, S., Hagemann, S. & Robertson, E. Multimodel analysis on the response of the AMOC under an increase of radiative forcing and its symmetrical reversal. Clim. Dyn. 45, 1429–1450 (2015).
Chadwick, R., Wu, P., Good, P. & Andrews, T. Asymmetries in tropical rainfall and circulation patterns in idealised CO2 removal experiments. Clim. Dyn. 40, 295–316 (2013).
Wu, P., Ridley, J., Pardaens, A., Levine, R. & Lowe, J. The reversibility of CO2-induced climate change. Clim. Dyn. 45, 745–754 (2015).
Bouttes, N., Gregory, J. M. & Lowe, J. A. The reversibility of sea level rise. J. Clim. 26, 2502–2513 (2013).
Ehlert, D. & Zickfeld, K. Irreversible ocean thermal expansion under carbon dioxide removal. Earth Syst. Dyn. 9, 197–210 (2018).
Oh, J., An, S., Shin, J. & Kug, J. Centennial memory of the Arctic Ocean for future Arctic climate recovery in response to a carbon dioxide removal. Earths Future 10, e2022EF002804 (2022).
An, S. et al. Global cooling hiatus driven by an AMOC overshoot in a carbon dioxide removal scenario. Earths Future 9, e2021EF002165 (2021).
Song, S.-Y. et al. Asymmetrical response of summer rainfall in East Asia to CO2 forcing. Sci. Bull. 67, 213–222 (2022).
Kug, J.-S. et al. Hysteresis of the intertropical convergence zone to CO2 forcing. Nat. Clim. Change 12, 47–53 (2022).
Kim, S.-K. et al. Widespread irreversible changes in surface temperature and precipitation in response to CO2 forcing. Nat. Clim. Change 12, 834–840 (2022).
Pathirana, G. et al. Increase in convective extreme El Niño events in a CO2 removal scenario. Sci. Adv. 9, eadh2412 (2023).
Schwinger, J., Asaadi, A., Steinert, N. J. & Lee, H. Emit now, mitigate later? Earth system reversibility under overshoots of different magnitudes and durations. Earth Syst. Dyn. 13, 1641–1665 (2022).
Li, X., Zickfeld, K., Mathesius, S., Kohfeld, K. & Matthews, J. B. R. Irreversibility of marine climate change impacts under carbon dioxide removal. Geophys. Res. Lett. 47, e2020GL088507 (2020).
Mathesius, S., Hofmann, M., Caldeira, K. & Schellnhuber, H. J. Long-term response of oceans to CO2 removal from the atmosphere. Nat. Clim. Change 5, 1107–1113 (2015).
Wu, P., Wood, R., Ridley, J. & Lowe, J. Temporary acceleration of the hydrological cycle in response to a CO2 rampdown. Geophys. Res. Lett. 37, L12705 (2010).
Long, S.-M., Xie, S.-P., Zheng, X.-T. & Liu, Q. Fast and slow responses to global warming: sea surface temperature and precipitation patterns. J. Clim. 27, 285–299 (2014).
Long, S. M. et al. Effects of ocean slow response under low warming targets. J. Clim. 33, 477–496 (2020).
Xie, S.-P. et al. Global warming pattern formation: sea surface temperature and rainfall. J. Clim. 23, 966–986 (2010).
Zhou, S., Huang, P., Xie, S.-P., Huang, G. & Wang, L. Varying contributions of fast and slow responses cause asymmetric tropical rainfall change between CO2 ramp-up and ramp-down. Sci. Bull. 67, 1702–1711 (2022).
Li, G. et al. Increasing ocean stratification over the past half-century. Nat. Clim. Change 10, 1116–1123 (2020).
Morrison, A. K., Waugh, D. W., Hogg, A. M., Jones, D. C. & Abernathey, R. P. Ventilation of the Southern Ocean pycnocline. Annu. Rev. Mar. Sci. 14, 405–430 (2022).
Shi, J.-R., Xie, S.-P. & Talley, L. D. Evolving relative importance of the Southern Ocean and North Atlantic in anthropogenic ocean heat uptake. J. Clim. 31, 7459–7479 (2018).
Liu, W., Lu, J., Xie, S.-P. & Fedorov, A. Southern Ocean heat uptake, redistribution, and storage in a warming climate: the role of meridional overturning circulation. J. Clim. 31, 4727–4743 (2018).
Huguenin, M. F., Holmes, R. M. & England, M. H. Drivers and distribution of global ocean heat uptake over the last half century. Nat. Commun. 13, 4921 (2022).
An, S.-I. et al. General circulation and global heat transport in a quadrupling CO2 pulse experiment. Sci. Rep. 12, 11569 (2022).
Gregory, J. & Webb, M. Tropospheric adjustment induces a cloud component in CO2 forcing. J. Clim. 21, 58–71 (2008).
Bourgeois, T., Goris, N., Schwinger, J. & Tjiputra, J. F. Stratification constrains future heat and carbon uptake in the Southern Ocean between 30° S and 55° S. Nat. Commun. 13, 340 (2022).
Bronselaer, B. & Zanna, L. Heat and carbon coupling reveals ocean warming due to circulation changes. Nature 584, 227–233 (2020).
Gent, P. R. & Mcwilliams, J. C. Isopycnal mixing in ocean circulation models. J. Phys. Oceanogr. 20, 150–155 (1990).
Wu, P., Jackson, L., Pardaens, A. & Schaller, N. Extended warming of the northern high latitudes due to an overshoot of the Atlantic meridional overturning circulation. Geophys. Res. Lett. 38, L24704 (2011).
Redi, M. H. Oceanic isopycnal mixing by coordinate rotation. J. Phys. Oceanogr. 12, 1154–1158 (1982).
Stuecker, M. F. et al. Polar amplification dominated by local forcing and feedbacks. Nat. Clim. Change 8, 1076–1081 (2018).
Mechoso, C. R. et al. Can reducing the incoming energy flux over the Southern Ocean in a CGCM improve its simulation of tropical climate? Geophys. Res. Lett. 43, 11,057–11,063 (2016).
Kim, H., Kang, S. M., Kay, J. E., Xie, S.-P. & Hartmann, D. Subtropical clouds key to Southern Ocean teleconnections to the tropical Pacific. Proc. Natl Acad. Sci. USA 119, e2200514119 (2022).
Schneider, T., Bischoff, T. & Haug, G. H. Migrations and dynamics of the intertropical convergence zone. Nature 513, 45–53 (2014).
Bischoff, T. & Schneider, T. Energetic constraints on the position of the intertropical convergence zone. J. Clim. 27, 4937–4951 (2014).
White, R. H. et al. Tropical precipitation and cross-equatorial heat transport in response to localized heating: basin and hemisphere dependence. Geophys. Res. Lett. 45, 11,949–11,958 (2018).
Byrne, M. P., Pendergrass, A. G., Rapp, A. D. & Wodzicki, K. R. Response of the intertropical convergence zone to climate change: location, width, and strength. Curr. Clim. Change Rep. 4, 355–370 (2018).
Cai, W. et al. Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Clim. Change 4, 111–116 (2014).
Hoskins, B. J. & Karoly, D. J. The steady linear response of a spherical atmosphere to thermal and orographic forcing. J. Atmos. Sci. 38, 1179–1196 (1981).
Goosse, H. et al. Quantifying climate feedbacks in polar regions. Nat. Commun. 9, 1919 (2018).
Keller, D. P. et al. The carbon dioxide removal model intercomparison project (CDRMIP): rationale and experimental protocol for CMIP6. Geosci. Model Dev. 11, 1133–1160 (2018).
Oh, J.-H. Emergent climate change patterns originating from deep ocean warming in climate mitigation scenarios. figshare https://doi.org/10.6084/m9.figshare.24873216.v1 (2023).
Acknowledgements
The CESM simulation and data transfer were supported by the National Supercomputing Center with supercomputing resources (KSC-2023-CHA-0001), and the National Center for Meteorological Supercomputer of the Korea Meteorological Administration (KMA) and the Korea Research Environment Open NETwork (KREONET), respectively. J.-S.K. was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (NRF-2022R1A3B1077622). S.-I.A. was supported by the National Research Foundation of Korea (NRF-2018R1A5A1024958). This is PMEL contribution no. 5451.
Author information
Authors and Affiliations
Contributions
J.-H.O. compiled the data, conducted analyses and simulations, prepared the figures and wrote the paper. J.-S.K. designed the research and wrote the paper. All authors discussed the results and revised the paper.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Climate Change thanks George Nurser, Kirsten Zickfeld and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Background barotropic steam function and Eulerian vertical velocity.
a, Background annual mean barotropic steam function. The black line indicates the barotropic steam function of 0 Sv. b, c, d, e, Background annual mean Eulerian vertical velocity (\({W}_{{eulerian}}\)) at 200 m, 700 m, 1000 m, and 2000 m, respectively.
Extended Data Fig. 3 Background maximum mixed layer depth (MMLD) and isopycnal diffusivity.
a, b, Maximum mixed layer depth (monthly maximum among 12 months climatology in each grid) and isopycnal diffusivity at 700 m for the CESM1 (present-day control simulation, see Methods), respectively. The contour in panels a and b indicates the MMLD of 150 m.
Extended Data Fig. 4 Temporal evolution of the changes in AMOC strength.
Temporal evolution of the AMOC strength defined as the maximum of the ocean stream function below 500 m at 26°N. The line and shading are as in Fig. 1a.
Extended Data Fig. 5 Positive feedbacks amplifying the irreversible SST warming.
a, c, d, As in Fig. 2a, but for the low cloud fraction, sea ice concentration, and surface air temperature, respectively. b, Shortwave cloud feedback strength (SWCFS) in the present-day control simulation, which is calculated as shortwave radiation at the top of the atmosphere regressed onto the underlying SST at each grid. The positive feedback between the SST and low clouds (that is shortwave cloud feedback) can amplify the irreversible SST warming: As the amount of low clouds decreases, the amount of solar radiation reaching the surface increases, resulting in a warming effect on the local SST. This SST warming, in turn, decreases atmospheric stability, which subsequently contributes to a decrease in the amount of low clouds. The black contour in panel a and b indicates the SWCFS of 0 Wm−2K−1. It is clear that the significant reduction in low cloud fraction occurs in regions with strong cloud feedback in the present climate. This low cloud reduction pattern well explains the distribution of the surface air temperature anomaly with significant sea-ice reduction in polar oceans, indicating the positive local feedbacks.
Extended Data Fig. 6 Spatial patterns of the irreversible OHC and SST changes in CMIP6 models.
a, b, Multi-model mean in the total OHC and SST anomalies averaged over the restoring period of each CMIP6 model ACCESS-ESM1-5, CESM2, CNRM-ESM2-1, CanESM5, GFDL-ESM4, MIROC-ES2L, NorESM2-LM, UKESM1-0-LL). c, Same as in b, but the AMOC effect is linearly removed using simple linear regression between AMOC strength and SST field. Note that the length of restoring period in each CMIP6 model is different (see Methods). Hatchings indicate insignificant responses at the 95% confidence level.
Extended Data Fig. 7 Patterns of the AMOC changes in CMIP6 models.
a, b, c, d, e, f, g, h, AMOC anomalies averaged over the restoring period of each CMIP6 model ACCESS-ESM1-5, CESM2, CNRM-ESM2-1, CanESM5, GFDL-ESM4, MIROC-ES2L, NorESM2-LM, UKESM1-0-LL).
Extended Data Fig. 8 Inter-ensemble relationship between global OHC and irreversible SST pattern.
a, Magnitude of irreversible SST pattern (see Methods) against global total OHC anomaly at its peak for each of 28 ensemble members. The gray dot indicates the ensemble mean. b, As in panel a, but for global 700-2000 m integrated OHC anomaly. c, As in panel a, cl 700-2000 m integrated OHC from its peak. The p value based on two-sided student’s t test in each panel is 7.2 × 10−5, 3.3 × 10−6, and 9.3 × 10−7, respectively.
Extended Data Fig. 9 Spatial patterns of the irreversible surface climate changes in initial warming experiments.
a, b, As in Fig. 3c, d, but for the IW_be100. c, d, As in Fig. 4c, d, but for the IW_be700. e, f, As in Fig. 3c, d, but for the IW_up100. Only significant values at the 95% confidence level are shown in all panels. The numbers labeled at the upper top corner in panels are the pattern correlations between each panel’s pattern and the reference irreversible SST and PRCP patterns (Figs. 2a and 2d).
Extended Data Fig. 10 Spatial patterns of the irreversible land temperature changes.
a, As in Fig. 2a, but for the land surface air temperature (SAT). b, c, d, e, As in Fig. 3c, but for the land SAT in IW_total, IW_be100, IW_be700, and IW_up100, respectively. The blue lines in each panel show the climatological annual mean snow cover edge of 50% in the present-day simulation. Only significant values at the 95% confidence level are shown in all panels. The numbers labeled at the upper top corner in panels (b-e) are the pattern correlations between each panel’s pattern and the pattern in panel a.
Supplementary information
Supplementary Information
Supplementary Figs. 1–3 and discussions (two topics).
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Oh, JH., Kug, JS., An, SI. et al. Emergent climate change patterns originating from deep ocean warming in climate mitigation scenarios. Nat. Clim. Chang. 14, 260–266 (2024). https://doi.org/10.1038/s41558-024-01928-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41558-024-01928-0
This article is cited by
-
Potential Impact of Climate Change-Induced Alterations on Pyroptotic Cell Death in Animal Cells: A Review
Molecular Biotechnology (2024)