Abstract
The Madden–Julian Oscillation (MJO) is a dominant source of subseasonal atmospheric variability in the tropics and significantly impacts global weather and climate predictability. Changes in its activity and predictability due to human-induced global climate change have profound implications for future global weather prediction. Here we investigate changes in MJO predictability in reanalysis and climate model data and find that MJO predictability has increased over the past century. This increase can be attributed to anthropogenic warming and continues during the twenty-first century in projections. The increased predictability is accompanied by stronger MJO amplitude, more regular oscillation patterns and organized eastward propagation under global warming. Our results suggest that greenhouse warming will increase the predictability of the MJO, with far-reaching consequences for global weather prediction.
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Data availability
CERA-20C reanalysis is provided by ECMWF on a data portal (https://apps.ecmwf.int/datasets/data/cera20c/). CESM2 and CESM2–WACCM control run, historical simulations and future projections are accessible through the Coupled Model Intercomparison Project (Phase 6) search interface (https://esgf-node.llnl.gov/search/cmip6/). CSF-20C hindcast ensemble data62 are available via https://catalogue.ceda.ac.uk/uuid/6e1c3df49f644a0f812818080bed5e45 under the Open Government License v.3.0. The MJO RMMI time series we computed in this study has been posted for public access63. Source data are provided with this paper.
Code availability
The Python code used for the WPE computation is available on Zenodo at https://zenodo.org/records/10031057 (ref. 64).
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Acknowledgements
D.D., W.H. and A.C.S. disclose support from NASA (21-OSST21-0026). D.D. and A.C.S. disclose support from the ONR MISOBOB research initiative (N00014-17-S-B001) and NOAA (NA18OAR4310405). E.B. discloses support from NSF (AGS 2001670). W.H. also acknowledges the travel support of the Johannes Geiss Fellowship from the International Space Science Institute, Bern Switzerland. We also acknowledge high-performance computing support and CESM2 data access from Cheyenne provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. All analyses were done with the Casper data analysis and visualization cluster.
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D.D. conducted most of the analyses and drafted the manuscript. All other authors contributed to the discussions on shaping this work, as well as the writing and editing of the manuscript. A.C.S., W.H. and J.B.W. offered suggestions on conceiving and designing the analyses. W.E.C. computed the RMMI in ECMWF seasonal forecasts and in CERA-20C. E.B. suggested using the WPE method and provided mathematical consultants.
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Extended data
Extended Data Fig. 1 An example MJO diagram.
It shows the MJO trajectory for 1997 January (blue), February (red) and March (black) in CERA-20C (ensemble member m0).
Extended Data Fig. 2 Time series of the MJO predictability in the model outputs represented by WPE.
CESM2 control run (pre-1850; black), CESM2/CESM2-WACCM historical simulation (1850-2015; blue for ensemble mean), and CESM2/CESM2-WACCM ssp585 future projection (2015-2100; red for ensemble mean) are shown. The WPE time series of different ensemble members are shown as the thin colored lines. Note that only the WPE values for the last 100 years in the CESM2 control run are plotted. Though these values are plotted as pre-1850 on the time axis, they are actually the results of a free model run initialized from conditions of Year 1850, and do not correspond to any calendar years.
Extended Data Fig. 3 The budget analysis of WPE.
It visualizes how individual permutations contribute to the WPE changing rate of RMM1, RMM2, the MJO amplitude and the MJO propagation in ssp585 runs. The unit of the y-axis values is year−1.
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Supplementary Sections 1–4 with Figs. 1–19.
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Du, D., Subramanian, A.C., Han, W. et al. Increase in MJO predictability under global warming. Nat. Clim. Chang. 14, 68–74 (2024). https://doi.org/10.1038/s41558-023-01885-0
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DOI: https://doi.org/10.1038/s41558-023-01885-0
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