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Counterbalancing influences of aerosols and greenhouse gases on atmospheric rivers

Abstract

Atmospheric rivers (ARs) are filamentary conduits of intense water vapour transport in the extratropics, accounting for the majority of poleward moisture transport in the mid-latitudes and acting as a key precipitation source for coastal regions. How ARs have responded to climate change nevertheless remains uncertain. Here we use a series of coupled model experiments to show that there was little to no change in mean AR characteristics in 1920–2005 due to opposite but equal influences from industrial aerosols, which weaken ARs, and greenhouse gases (GHGs), which strengthen them. Despite little historical change, the simulations project steep intensification of ARs in the coming decades, including mean AR-driven precipitation increases of up to ~20 mm per month, as the influence of GHGs greatly outpaces that of industrial aerosols. We also investigate the extent to which future AR changes are dynamically and thermodynamically driven, highlighting the need to conceptualize AR change beyond the scaling of humidity with warming.

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Fig. 1: Historical and future influences.
Fig. 2: Single forcing influences.
Fig. 3: Multi-model comparison of aerosol and GHG influences.
Fig. 4: Future influences of aerosols and GHGs.
Fig. 5: Thermodynamic and dynamical influences of aerosols.
Fig. 6: Thermodynamic and dynamical influences of GHGs.

Data availability

All NCAR CESM1 Large Ensemble model data are publicly available through the Casper cluster at /glade/campaign/cesm/collections/cesmLE/CESM-CAM5-BGC-LE/. The three-hourly IVT and IWV variables calculated from MERRA-2 can be found through the NCAR Climate Data Gateway at https://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.merra.artmip.011980-062017.atm.proc.3hourly_inst.html. The Lora_v2 catalogue to identify ARs within MERRA-2 can also be found through the Climate Data Gateway at https://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.artmip.tier1.html. The DAMIP experiments are part of Coupled Model Intercomparison Project Phase 6 and are available at https://esgf-node.llnl.gov/search/cmip6.

Code availability

All code necessary for performing the reported analyses is available upon reasonable request from the corresponding author.

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Acknowledgements

This work was supported by the Department of Earth and Planetary Sciences at Yale University. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

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Authors

Contributions

S.H.B. conceived the study. S.H.B. and J.M.L. designed the study. S.H.B. performed the analyses, with contributions from J.M.L. in interpreting the results. S.H.B. wrote the paper, with contributions from J.M.L.

Corresponding author

Correspondence to Seung H. Baek.

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The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Breanna Zavadoff and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Comparison of model and reanalysis ARs.

(top) AR IVT identified on MERRAv2 and (middle) CESM1 ALL ensemble, both over 1980-2005. (bottom) Differences in AR IVT between MERRAv2 and CESM1 over 1980-2005.

Extended Data Fig. 2 Climatological ARs.

(left) Climatological AR-driven precipitation and IVT and (right) percent of total precipitation accounted by AR-driven precipitation (top) due to internal variability exclusive of historical forcings, (middle) over 1920-2005 with historical forcings, and (bottom) over 2006-2080 under the RCP8.5 scenario.

Extended Data Fig. 3 Temperature influences of AER and GHG.

Influences of greenhouse gases (orange) and industrial aerosols (blue), respectively, on mean surface air temperature over the mid-latitude (20°-70°) oceans from 1920–2005.

Extended Data Fig. 4 Humidity and wind influence of AER.

Changes in (left) specific humidity and (right) zonal winds induced by industrial aerosols for 1920–2005 for (top) the 500 hPa and (bottom) 850 hPa levels. IVT changes for each level are shown as contours. Note that different contour intervals are used for the 500 hPa and 850 hPa panels.

Extended Data Fig. 5 Humidity and wind influence of GHG.

Same as Extended Data Fig. 4, but for greenhouse gases.

Extended Data Fig. 6 Vertical wind influence of AER.

The influence of industrial aerosols (AER) on vertical winds at 527.4 hPa over 2006-2080. Contours show AER-induced change in specific humidity (g/kg) at 850 hPa.

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Baek, S.H., Lora, J.M. Counterbalancing influences of aerosols and greenhouse gases on atmospheric rivers. Nat. Clim. Chang. (2021). https://doi.org/10.1038/s41558-021-01166-8

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