Abstract
Reliable projections of the South American Summer Monsoon (SASM) are critical for managing regional hydroclimatic risks, yet remain highly uncertain due to internal climate variability. Here, we reconstruct a robust historical SASM index ensemble from 1850 CE onward by integrating high-resolution paleoclimate proxies (tree rings and ice cores), historical documents, and instrumental observations. We further analyze future changes using large ensembles from the CESM2 and CanESM5 climate models. Our results demonstrate that multidecadal variability in the SASM is primarily driven by the Interdecadal Pacific Oscillation (IPO) and the associated changes in the Pacific Walker Circulation (PWC), whereas the influence of the tropical Atlantic sea surface temperature (SST) gradient is comparatively minor. By constraining these key Pacific modes, we reduce the uncertainty in projected SASM intensity by approximately 30%, highlighting their dominant role in shaping near-term monsoon trajectories. This study underscores the importance of improved simulation and representation of Pacific variability for advancing hydroclimate projections and informing climate adaptation strategies in tropical South America.
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Data availability
All data used in this study were obtained from publicly available repositories. Long-term precipitation station data from tropical South America were obtained from the Climatic Research Unit (CRU) at the University of East Anglia (https://crudata.uea.ac.uk/cru/data/hrg/). Tree-ring width data were downloaded from the Center for Climate and Resilience Research (https://www.cr2.cl/datos-dendro-sada/). Tree-ring and ice core δ18O records used in the reconstruction are available from the Iso2k database (https://lipdverse.org/iso2k/current_version/) and NOAA Paleo Data website: https://www.ncei.noaa.gov/access/paleo-search/. The historical documentary dataset is accessible at https://www.ncei.noaa.gov/pub/data/paleo/historical/southamerica/neukom2009.txt. Long-term daily water level data for the Negro River at Manaus Harbor were obtained from the Brazilian Water Agency (http://www.snirh.gov.br/hidroweb/publico/medicoes_historicas_abas.jsf). ERA5 reanalysis data were obtained from the Copernicus Climate Change Service (C3S) Climate Data Store. Sea surface temperature data from ERSSTv5 (https://downloads.psl.noaa.gov/Datasets/noaa.ersst.v5/) and Twentieth Century Reanalysis data (20CRv3) (https://psl.noaa.gov/data/gridded/data.20thC_ReanV3.html) were accessed via the NOAA PSL database. CESM2 Large Ensemble data were obtained from the NCAR Climate Data Gateway (https://www.cesm.ucar.edu/community-projects/lens2), and CanESM5 Large Ensemble data were accessed through the CMIP6 archive hosted by the ESGF node at DKRZ (https://esgf-data.dkrz.de/search/cmip6-dkrz/). The South American Summer Monsoon reconstruction ensemble generated in this study is available on Zenodo at 10.5281/zenodo.15683617.
Code availability
The code implementing the Bayesian Optimal Information Extraction approach for the reconstruction of the South American Summer Monsoon index was developed in MATLAB and is available at https://github.com/iggcasPDA/SASM_code. The repository includes scripts for data preprocessing, calibration, and ensemble generation. Additional information or support is available from the corresponding author upon reasonable request.
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Acknowledgements
This work was supported by the U.S. National Science Foundation under awards AGS-2402113 (to Z.L. and M.V.), EAR-2103041 (to M.V.), and AGS-2015780 (to A.D.). M.S.M. acknowledges support from the Agencia Nacional de Promoción Científica y Tecnológica, Argentina (PICT 2013-1880), and the Consejo Nacional de Investigaciones Científicas y Técnicas (PIP 11220130100584 and PIP 11220210100910), as well as funding from CONCYTEC–World Bank, Peru (FONDECYT-BM-INC.INV 039-2019). D.A.C. was supported by FONDECYT project 1241699 and ANID/FONDAP/1523A0002. M.E.F. acknowledges support from PIP 11220200102929CO.
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Z.L. designed the study. Z.L., F.S., and Y.Y. performed the reconstructions and analyzed the climate model simulations. They also wrote the first draft of the manuscript, with A.D. and M.V. contributing to the final version. K.T. assisted with climate model data processing and ensemble management. D.A.C., M.M., and E.F. provided tree-ring data and contributed to the interpretation of regional proxy records. All authors discussed the results and contributed to the final manuscript.
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Lyu, Z., Shi, F., Yang, Y. et al. Pacific and Atlantic teleconnections reduce uncertainty in multidecadal projections of the South American Summer Monsoon. npj Clim Atmos Sci (2026). https://doi.org/10.1038/s41612-026-01373-0
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DOI: https://doi.org/10.1038/s41612-026-01373-0
