Toward robust fine-scale decadal precipitation forecasts through dynamically consistent subsampling

Couallier, Joanne; Swingedouw, Didier; Sakarovitch, Charlotte; Raymond, Théodore; Alkama, Ramdane

doi:10.5194/esd-17-1177-2026

Articles | Volume 17, issue 4

https://doi.org/10.5194/esd-17-1177-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esd-17-1177-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 4

Research article

|

26 Aug 2026

Research article |

| 26 Aug 2026

Toward robust fine-scale decadal precipitation forecasts through dynamically consistent subsampling

Joanne Couallier, Didier Swingedouw, Charlotte Sakarovitch, Théodore Raymond, and Ramdane Alkama

Supplement

https://doi.org/10.5194/esd-17-1177-2026-supplement

Data sets

ERA5 hourly data on single levels from 1940 to present Copernicus Climate Change Service, Climate Data Store https://doi.org/10.24381/cds.adbb2d47

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Short summary

Reliable decadal predictions of regional precipitation are essential, yet they remain a major challenge. We present a framework that integrates decadal predictions of relevant large-scale modes to enhance prediction skill of precipitation at a fine scale resolution over France. Using North Atlantic Oscillation improves winter skill, and combining summer North Atlantic Oscillation with Atlantic Multidecadal Variability improves summer forecasts, offering useful information for climate services.