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North Pacific ocean–atmosphere responses to Holocene and future warming drive Southwest US drought

Nature Geoscience volume 18, pages 646–652 (2025)Cite this article

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Abstract

The Southwest United States is experiencing severe and persistent drought, although uncertainties regarding the causes limit our ability to predict changes in water availability. The severity of the current drought has been attributed to a combination of warming and natural changes in atmospheric circulation, suggesting that current rainfall deficits may improve as natural oscillations reverse sign. Here we use new leaf-wax stable isotope reconstructions and simulations for the mid-Holocene (6 thousand years ago) and demonstrate that moderate warming of the Northern Hemisphere can produce drought over the Southwest United States through an ocean–atmosphere response originating in the North Pacific. The patterns of ocean warming and rainfall change resemble the negative phase of the Pacific Decadal Oscillation, indicating that this mode can be excited by external forcings. A similar response to warming is evident in future projections, leading to sustained winter precipitation deficits through the mid-twenty-first century. However, the magnitudes of past and current precipitation deficits associated with this North Pacific response are systematically underestimated in models, possibly due to a weak coupling of ocean–atmosphere interactions. Projections may also underestimate the magnitude of this precipitation response to changes in the North Pacific, leading to greater drought risk in this already water-poor region.

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Fig. 1: Proxy palaeoclimate changes in the Southwest United States.
Fig. 2: Model and proxy estimates of mid-Holocene (6 ka) winter precipitation anomalies.
Fig. 3: Proxy and model data comparison for the mid-Holocene.
Fig. 4: Emergence of a PDO pattern and Southwest US drought in observations and simulations.

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Data availability

All data produced in our analyses are available in the main text, in the Supplementary Information and via figshare at https://doi.org/10.6084/m9.figshare.28947815 (ref. 52). CESM2 simulations are available for download from http://www.cesm.ucar.edu/experiments/. PMIP3 model output is publicly available from https://pmip3.lsce.ipsl.fr. The additional mid-Holocene simulations investigating vegetation changes using EC-Earth, GISS-E2-G and CCSM4-Toronto, and CESM are available from https://doi.org/10.5281/zenodo.7651155 (ref. 63) and https://zenodo.org/record/6112019#.YhfNZOjMKUm (ref. 64), respectively. All data processing and figures were produced in Python 3.9 using xarray65, Matplotlib66 and Cartopy67.

Code availability

The MixSIAR model is available from https://brianstock.github.io/MixSIAR/. Mixing model code produced during our analysis is available via figshare at https://doi.org/10.6084/m9.figshare.28947815 (ref. 52). Code for model data analysis and figures is available on request.

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Acknowledgements

We acknowledge the decades of work by many individual authors who produced the palaeoclimate records used here in the sea surface temperature and hydroclimate data syntheses. We also acknowledge the organizers and all the modellers who contributed mid-Holocene simulations to the Paleoclimate Modeling Intercomparison Project, Phase 3 (PMIP3). The CESM project is supported primarily by the National Science Foundation (NSF). This material is based on work supported by the National Center for Atmospheric Research (NCAR), a major facility sponsored by the NSF under Cooperative Agreement no. 1852977. The CAM6 Prescribed SST GOGA experiments were conducted by the Climate Variability and Change Working Group (CVCWG). Record generation, data synthesis, model comparisons and sensitivity simulations were funded by the US National Science Foundation P2C2 programme awards 1702271 to T.M.S. and 2002528 to T.M.S. and P.N.D. F.S.R.P. acknowledges financial support from the NSERC Discovery Grant (grant RGPIN-2018-04981) and the NOVA—FRQNT-NSERC (grants 2023-NOVA-324826 and ALLRP 577112-22).

Author information

Authors and Affiliations

  1. Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA

    Victoria L. Todd & Timothy M. Shanahan

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

    Pedro N. DiNezio & Jeremy M. Klavans

  3. The Department of Earth and Planetary Sciences, The University of New Mexico, Albuquerque, NM, USA

    Peter J. Fawcett

  4. School of Earth and Sustainability, Northern Arizona University, Flagstaff, AZ, USA

    R. Scott Anderson

  5. Departamento de Estratigrafía y Paleontología, Universidad de Granada, Granada, Spain

    Gonzalo Jiménez-Moreno

  6. Center for Climate Systems Research, Columbia University, New York, NY, USA

    Allegra N. LeGrande

  7. NASA Goddard Institute for Space Studies, New York, NY, USA

    Allegra N. LeGrande

  8. Centre ESCER and GEOTOP, Department of Earth and Atmospheric Sciences, University of Quebec in Montreal, Montreal, Quebec, Canada

    Francesco S. R. Pausata

  9. Cooperative Institute for Research In Environmental Sciences, The University of Colorado, Boulder, CO, USA

    Alexander J. Thompson

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

    Jiang Zhu

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  1. Victoria L. Todd
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  2. Timothy M. Shanahan
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  3. Pedro N. DiNezio
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Contributions

T.M.S. and P.N.D. conceived the study. The records were generated by T.M.S. and V.L.T. T.M.S., P.N.D. and V.L.T. developed the methodology. The investigation was conducted by T.M.S., P.N.D., V.L.T. and J.M.K. Samples were collected by R.S.A., P.J.F. and G.J.-M. Climate simulations were provided by F.S.R.P., A.N.L., A.J.T. and J.Z. V.L.T., T.M.S. and P.N.D. wrote the paper. All authors reviewed and edited the final version of the paper.

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Correspondence to Victoria L. Todd.

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Nature Geoscience thanks Dimitris Herrera and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: James Super, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Proxy and Model Precipitation Changes in the Mid-Holocene.

Locations of sites from this study (stars: 1- Hunters Lake, 2- Stewart Bog) and synthesized proxy hydroclimate data (symbols) compared against simulated winter (DJF) precipitation (shading) from the ensemble of mid-Holocene experiments with (a) preindustrial vegetation (from PMIP3) and with (b) prescribed 6 ka vegetation (this study). Symbols indicate the proxy type: δ18O (circles), pollen transfer functions (diamonds), lake level (triangles), lake sediment (squares), and others (thin diamonds). The isotope record from 3-Leviathan Cave is indicated with a yellow circle. Stippling indicates where the majority of models agree (a: 8/15; b: 5/8). The red box indicates the area used to calculate changes in precipitation in the Southwest US, which is the same as in ref. 8.

Extended Data Fig. 2 Seasonal δD Distribution and Modern Precipitation at Study Sites.

(a) Probability density plots of the seasonal distribution of modern precipitation δD for Stewart Bog, NM20 and Hunters Lake, CO23 from the Online Isotopes in Precipitation Calculator (OIPC)23 Winter (DJF) and summer (JAS) values are shown in blue and gold, respectively. The solid black line with grey shading indicates the annual average and 95% CI for each site. (b) Monthly averaged precipitation (cm/month) between 1980 and 2019 ref. 28 for Stewart Bog and Hunters Lake.

Extended Data Fig. 3 Simulated Seasonal δD Values Across Holocene Forcing Scenarios.

Probability density plots of simulated δD seasonal precipitation for winter (DJF, blue-grey) and summer (JAS, orange-yellow) over the region including our two study locations (−107°W, −105°W, 35°N, 38°N) from i-CESM1.2. PDFs are shown for simulations with boundary conditions and forcings for: preindustrial (PI), mid-Holocene with preindustrial vegetation (MHPIveg), mid-Holocene with prescribed “Green Sahara” (GS), mid-Holocene with prescribed “Green Sahara” and high latitude vegetation (MHGS+NHveg)25.

Extended Data Fig. 4 Impact of Vegetation on Albedo and Surface Radiation.

Surface albedo and net surface radiation (W/m2) anomalies (6 ka-preindustrial) for the CESM1 simulation forced by preindustrial vegetation and insolation only (left) and 6ka conditions with prescribed “Green Sahara” and Northern Hemisphere vegetation changes (right), from ref. 25. Compared with the simulation with insolation only (left), the prescribed vegetation simulation shows an increase in surface radiation localized over regions with expanded vegetation due to the associated reductions in surface albedo (right).

Extended Data Fig. 5 PDO Epoch Differences in North Pacific Hydroclimate.

Differences in winter precipitation over land (shading)28, sea surface temperature (shading)46, and sea level pressure (hPa 10 yr−1; contours)45 trends between epochs with negative (1900:1924, 1947:1995, and 2000:2021) and positive (1925:1946 and 1977:1995) values of the Pacific Decadal Oscillation (PDO) index (data from ref. 33).

Extended Data Fig. 6 Vegetation-Driven Changes in the Aleutian Low and Jet Stream.

The role of prescribed vegetation (6kaVegetation – 6kaControl) in driving the weakening of the Aleutian Low and the northward shift of the Pacific jet stream in sensitivity experiments with prescribed 6ka Control SSTs (Methods). Annual mean anomalies in a. surface temperature, b. sea level pressure, and c. zonal wind speed (m/s) at 200 hPa (shading), with control-run contours (black lines) overlaid. b. Shows the weakening of the Aleutian Low and c. the northward shift of the North Pacific jet stream resulting from vegetation-driven a. land surface warming.

Extended Data Fig. 7 Model Agreement Metrics for Mid-Holocene Precipitation Change.

a. Cohen’s κ and b. Gwet’s AC for the models as a function of wetter/drier thresholds. Greater agreement is evident in the majority of the models with dynamic or prescribed vegetation. The numbers refer to the following models: 1-GISS-E2-G, 2-CESM1.2, 3-Toronto-CCSM4, 4-EC-Earth, 5-HadGEM2-ES, 6-HadGEM2-CC, 7-CCSM4,8-MPI-ESM-P, 9-IPSL, 10-CSIRO-Mk3, 11-Fgoals-g2, 12-bcc-csm-1, 13-CGCM3, 14-CNRM-CM5, 15-MIROC-ESM, 16- GISS-E2-R, 17-Fgoals-s2.

Extended Data Fig. 8 Ocean Feedbacks Driving North Pacific SST Patterns.

The role of b. Ocean Dynamical Adjustments and c. Shortwave cloud forcing in driving the a. sea surface warming temperature pattern in the North Pacific in the fully coupled CESM1 mid-Holocene simulation with prescribed ‘Green Sahara’ and Siberian vegetation changes ref. 25. Results from Heat Budget Analysis following ref. 61.

Extended Data Fig. 9 Sensitivity to SST Boundary Conditions in Driving Mid-Holocene Climate.

Sensitivity experiments (Methods, Supplementary Table 3) illustrating winter (DJF) anomalies in a) surface temperature (ΔT, °C), (b) sea level pressure (Pa), and (c) large-scale precipitation (ΔP, %) relative to a 6 ka control run (6kaControl). Each row shows results with different prescribed SST boundary conditions taken from the coupled vegetation experiment25: Global SSTs and sea ice (6kaSSTVeg) (top row), Only Tropical Pacific SSTs (6kaTropPacSSTVeg) (middle row), and Only North Pacific SSTs (6kaNorthPacSSTVeg) (bottom row). These distinctions highlight the critical role of extratropical ocean forcing in shaping the mid‐Holocene winter climate, beyond the tropical influences alone. Red boxes indicate the area used to calculate Southwest US drought anomalies.

Extended Data Fig. 10 Observed-Model Comparison of Ocean Forcing on North American Climate.

Temperature trends (°C/decade) and precipitation changes (%) from 1983 to 2019 in the simulations from the a) Global Ocean Global Atmosphere (GOGA) and b) Tropical Ocean Global Atmosphere (TOGA) simulations as in ref. 8. c) The difference between the GOGA and TOGA experiments. The GOGA and TOGA simulations were completed by the NCAR Climate Variability and Change Working Group. This data is available from the NCAR Climate Data Gateway.

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Todd, V.L., Shanahan, T.M., DiNezio, P.N. et al. North Pacific ocean–atmosphere responses to Holocene and future warming drive Southwest US drought. Nat. Geosci. 18, 646–652 (2025). https://doi.org/10.1038/s41561-025-01726-z

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