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Tropical response to ocean circulation slowdown raises future drought risk

Nature volume 644, pages 676–683 (2025)Cite this article

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Abstract

Projections of tropical rainfall under global warming remain highly uncertain1,2, largely because of an unclear climate response to a potential weakening of the Atlantic meridional overturning circulation (AMOC)3. Although an AMOC slowdown can substantially alter tropical rainfall patterns4,5,6,7,8, the physical mechanisms linking high-latitude changes to tropical hydroclimate are poorly understood11. Here we demonstrate that an AMOC slowdown drives widespread shifts in tropical rainfall through the propagation of high-latitude cooling into the tropical North Atlantic. We identify and validate this mechanism using climate model simulations and palaeoclimate records from Heinrich Stadial 1 (HS1)—a past period marked by pronounced AMOC weakening9,10. In models, prevailing easterly and westerly winds communicate the climate signal to the Pacific Ocean and Indian Ocean through the transport of cold air generated over the tropical and subtropical North Atlantic. Air–sea interactions transmit the response across the Pacific Ocean and Indian Ocean, altering rainfall patterns as far as Indonesia, the tropical Andes and northern Australia. A similar teleconnection emerges under global warming scenarios, producing a consistent multi-model pattern of tropical hydroclimatic change. These palaeo-validated projections show widespread drying across Mesoamerica, the Amazon and West Africa, highlighting an elevated risk of severe drought for vulnerable human and ecological systems.

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Fig. 1: Proxy-inferred changes in hydroclimate during HS1 compared with simulated changes in response to reductions in the strength of the AMOC.
Fig. 2: Rainfall responses associated with patterns of tropical Atlantic cooling.
Fig. 3: Simulated climate responses driving hydroclimate changes during HS1.
Fig. 4: Simulated climate responses in the eastern tropical Pacific and the Indian Ocean.
Fig. 5: Surface temperature and rainfall changes in response to greenhouse warming associated with cooling patterns over the North Atlantic.
Fig. 6: Impact of model validation on rainfall projections.

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Data availability

Our synthesis of hydroclimate changes during HS1 (ref. 62), including metadata, methods and references, is available at Zenodo62 (https://doi.org/10.5281/zenodo.13881535). The original published records are available in published repositories as detailed by the individual publications listed in the document accompanying the synthesis.

Code availability

The MATLAB code used to perform the quantitative model-proxy evaluation and create the figures is available at Zenodo79 (https://doi.org/10.5281/zenodo.13886977).

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Acknowledgements

We acknowledge the decades of work by many individual authors who produced the palaeoclimate records used here. We thank K. Thirumalai for comments on this work. We acknowledge A. Abe-Ouchi, G. Lohmann and J. Singarayer for providing model output and N. Piatrunia and K. Gomez for participating in an initial collation of palaeoclimate records. The CESM project is supported primarily by the National Science Foundation (NSF). This work was supported by the NCAR, which is a main facility sponsored by the NSF under cooperative agreement no. 1852977. Computing and data storage resources, including the Cheyenne supercomputer (https://doi.org/10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory at NCAR. We thank all the scientists, software engineers and administrators who contributed to the development of CESM1. Funding for this work was provided by the NSF (grants AGS-2002528 and AGS–2103007 for P.N.D., grants AGS-2002528 and OCE–1903482 for T.S.). M.K. was funded by the CNRS (Centre National de la Recherche Scientifique). The IPSL model was run on the Très Grande Infrastructure de Calcul at Commissariat à l’Energie Atomique (gen2212 project). M.P. and U.M. acknowledge the support from the PalMod project (www.palmod.de; FKZ 01LP1915B and 01LP1916C) funded by the German Federal Ministry of Education and Research. X.Z. acknowledges the technical support of the National Large Scientific and Technological Infrastructure Earth System Numerical Simulation Facility (https://cstr.cn/31134.02.EL), and the support from National Key Research and Development Projects of China (2023YFF0805201).

Author information

Authors and Affiliations

  1. Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO, USA

    Pedro N. DiNezio

  2. Department of Earth and Planetary Sciences, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA

    Timothy M. Shanahan

  3. Environmental Defense Fund, Austin, TX, USA

    Tianyi Sun

  4. Earth and Planetary Sciences Department, University of California, Davis, Davis, CA, USA

    Chijun Sun

  5. The Department of Sustainable Earth Systems Sciences, The University of Texas at Dallas, Richardson, TX, USA

    Xian Wu

  6. Environmental Studies and Science Program, Colorado College, Colorado, Springs CO, USA

    Allison Lawman

  7. Department of Earth Science, University of California, Santa Barbara, CA, USA

    David Lea

  8. Laboratoire des Sciences du Climat, l’Environnement/Institut Pierre-Simon-Laplace, Gif-sur-Yvette, France

    Masa Kageyama

  9. MARUM—Center for Marine Environmental Sciences, University of Bremen, Bremen, Germany

    Ute Merkel & Matthias Prange

  10. Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO, USA

    Bette Otto-Bliesner

  11. British Antarctic Survey, Cambridge, UK

    Xu Zhang

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  1. Pedro N. DiNezio
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Contributions

P.N.D. and T.M.S. conceived the study and wrote the paper. T.M.S., P.N.D., A.L. and C.S. compiled and analysed the palaeodata. P.N.D., T.M.S. and D.L. formulated the hypotheses. P.N.D., T.S. and X.W. analysed the model output. P.N.D., M.K., U.M., M.P., B.O.-B. and X.Z. performed the simulations.

Corresponding author

Correspondence to Pedro N. DiNezio.

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The authors declare no competing interests.

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Nature thanks Yassine Ait Brahim, Matthew Osman and Frerk Pöppelmeier for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Simulated changes in surface air temperature in response to freshwater forcing.

Change in annual-mean surface air temperature simulated by climate models under varied magnitudes and locations of freshwater forcing in the North Atlantic. The maps are labeled according to the name of the simulation as specified in Extended Data Table 1. All experiments were run relative to glacial background states. The climate response to freshwater forcing was computed as difference relative to the corresponding glacial simulation as described in the Methods.

Extended Data Fig. 2 Simulated changes in rainfall in response to freshwater forcing.

Change in annual-mean rainfall simulated by climate models under varied magnitudes and locations of freshwater forcing in the North Atlantic. The maps are labeled according to the name of the simulation as specified in Extended Data Table 1. All experiments were run relative to glacial background states. The climate response to freshwater forcing was computed as difference relative to the corresponding glacial simulation as described in the Methods.

Extended Data Fig. 3 Reconstructed hydroclimate changes during Heinrich Stadial 1.

Proxy-inferred hydroclimate changes during Heinrich Stadial 1 (symbols) from published palaeoclimate records capturing drier (red downward triangle), unchanged (white squares), wetter (green upward triangle), or unclear (black circles) conditions during Heinrich Stadial 1. Bigger triangles indicate sites resulting from merging multiple records within a 100 km radius.

Extended Data Fig. 4 Sensitivity of global and regional proxy-model agreement to different proxy types.

Global (a) and regional (b–f) agreement between hydroclimate changes reconstructed using different combinations of two proxy types and the simulated responses associated with cooling patterns in the North Atlantic. Dotted, solid, and dashed lines correspond to ensemble-mean responses from simulations with stronger, moderate, and muted cooling over the tropical North Atlantic respectively. Model-proxy agreement is quantified using the Cohen’s κ metric.

Extended Data Fig. 5 Correlation between simulated responses associated with AMOC reductions and global proxy-model agreement for hydroclimate changes.

a. Correlation between proxy-model agreement and simulated tropical North Atlantic temperature change. b. Correlation between proxy-model agreement and simulated high latitude North Atlantic temperature change. Each symbol represents a simulation in our ensemble. Symbol colors indicate the magnitude of the AMOC reduction as % of the strength in the glacial baseline.

Extended Data Fig. 6 Simulated and reconstructed patterns of cooling over the tropical North Atlantic.

Changes in surface air temperature from simulations classified as moderate tropical North Atlantic cooling (shading) and inferred for HS1 using existing temperature records (symbols). Triangles correspond to \({U}_{37}^{{k}^{{\prime} }}\) records and circles to Mg/Ca records. White symbols indicate a muted temperature response during HS1. Symbols are colored based on the categories listed in Extended Data Table 2 following the same color scheme as for the simulated changes.

Extended Data Fig. 7 Climate responses in the Indian Ocean for different patterns of cooling in the North Atlantic.

Changes in annual-mean rainfall (a–d) and surface air temperature (e–h) averaged across simulations with different combinations of strong and muted cooling in the high latitude and tropical North Atlantic. The simulations in each group are listed below each panels title. The values of strong and weak high latitude cooling range from −20 to −8 K and from −7 to −1 K respectively. The values of strong/moderate and weak tropical cooling range from −5.5 to −1 K and from −1 to 0 K respectively.

Extended Data Fig. 8 Correlation between changes in rainfall over India and Arabian Sea cooling.

Relationship between rainfall changes over India (70–85°E 7– 30°N) (y-axix) vs. the magnitude of the surface air temperature responses over the Arabian Sea (50–70°E 5–25°N).

Extended Data Fig. 9 Seasonal climate responses in the Indian Ocean.

Changes in rainfall (a–c) and surface air temperature (d–f) simulated by the Community Earth System Model Version 1 (CESM1) in response to 0.15 Sv of freshwater forcing. Annual mean (a,d), boreal summer (b,e) and austral summer (c,f) changes are displayed to illustrate the responses of the Indian and Australian summer monsoons respectively. Vectors indicate changes in surface wind stress.

Extended Data Fig. 10 AMOC-related sea-surface temperature changes in CMIP greenhouse warming simulations.

Normalized sea-surface temperature change over the high latitude (x-axis) vs. tropical (y-axis) North Atlantic simulated from 1921 to 2100 under high-emissions scenarios by models participating in the Climate Model Intercomparison Project (CMIP). Each symbol corresponds to values simulated by a distinct model participating in phases 3, 5, and 6 of CMIP indicated by the colors. Models are grouped based on the magnitude of the normalized sea-surface temperature change in each region defined by the dotted lines and by the symbols as indicated by the legend. The averaged sea-surface temperature change over the North Atlantic (50°W–0°50°N–65°N) is normalized by the surface temperature change averaged over the Northern Hemisphere (0–90°N). The averaged sea-surface temperature change over the tropical North Atlantic (80°W–40°W 12°N–22°N) is normalized by the surface temperature averaged change over the tropics (20°S-20°N).

Extended Data Table 1 Freshwater hosing simulations and model configuration
Full size table
Extended Data Table 2 Temperature records used to infer the pattern and magnitude of tropical Atlantic cooling during Heinrich Stadial 1
Full size table

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DiNezio, P.N., Shanahan, T.M., Sun, T. et al. Tropical response to ocean circulation slowdown raises future drought risk. Nature 644, 676–683 (2025). https://doi.org/10.1038/s41586-025-09319-x

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