Climate driven generative time-varying model for improved decadal storm power predictions in the Mediterranean

Decadal climate predictions are crucial for communities engaged in scenario planning under Sustainable Development Goals. However, uncertainties in future precipitation extremes hinder climate mitigation and adaptation efforts. Here we present a hybrid statistical climate-driven time-varying model to predict the Areal MEan Storm Erosivity Index, a key indicator of hydrological events, for the Mediterranean region. By integrating historical data (1884-2022) with large-scale (El Niño–Southern Oscillation) and small-scale (precipitation variability) climate forcings, our model captures past storm behavior and projects future dynamics. The Hurst exponent (0.63) suggests a long-term positive memory in Areal MEan Storm Erosivity Index, enhancing prediction accuracy. Projections show an Index increase until 2040, then a decline until 2050, and a resurgence. While consistent with other regional models at the interdecadal scale, finer variations are less pronounced at the interannual scale. This approach offers valuable insights into hydroclimate variability, aiding climate resilience planning in the Mediterranean and beyond. Decadal climate predictions reveal a notable increase in the Areal Mean Strom Erosivity Index until 2040 in the Mediterranean, followed by a decline until 2050 and a resurgence, according to a climate-driven generative time-varying model, historical data from 1884 to 2022, as well as climate forcings.

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Publication Details

Journal
Communications Earth & Environment
Published
2025-03-18
DOI
https://doi.org/10.1038/s43247-025-02196-2
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11
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article

Climate driven generative time-varying model for improved decadal storm power predictions in the Mediterranean

Cristina Di Salvo, Gianni Bellocchi, Nazzareno Diodato
1 citations
Communications Earth & Environment
Climate variability and models
1.11
article

Climate driven generative time-varying model for improved decadal storm power predictions in the Mediterranean

Cristina Di Salvo, Gianni Bellocchi, Nazzareno Diodato
article en
1 citations

Abstract

Decadal climate predictions are crucial for communities engaged in scenario planning under Sustainable Development Goals. However, uncertainties in future precipitation extremes hinder climate mitigation and adaptation efforts. Here we present a hybrid statistical climate-driven time-varying model to predict the Areal MEan Storm Erosivity Index, a key indicator of hydrological events, for the Mediterranean region. By integrating historical data (1884-2022) with large-scale (El Niño–Southern Oscillation) and small-scale (precipitation variability) climate forcings, our model captures past storm behavior and projects future dynamics. The Hurst exponent (0.63) suggests a long-term positive memory in Areal MEan Storm Erosivity Index, enhancing prediction accuracy. Projections show an Index increase until 2040, then a decline until 2050, and a resurgence. While consistent with other regional models at the interdecadal scale, finer variations are less pronounced at the interannual scale. This approach offers valuable insights into hydroclimate variability, aiding climate resilience planning in the Mediterranean and beyond. Decadal climate predictions reveal a notable increase in the Areal Mean Strom Erosivity Index until 2040 in the Mediterranean, followed by a decline until 2050 and a resurgence, according to a climate-driven generative time-varying model, historical data from 1884 to 2022, as well as climate forcings.

Communications Earth & EnvironmentVol. 6(1)
Université Clermont Auvergne (FR), University Corporation for Atmospheric Research (US), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Institute of Environmental Geology and Geoengineering (IT), VetAgro Sup (FR)
Climate action
Openalex Percentile: Top 26%
Climate variability and models
1.11
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Climate driven generative time-varying model for improved decadal storm power predictions in the Mediterranean — Cristina Di Salvo, Gianni Bellocchi, et al. · Communications Earth & Environment (2025) | TGRS Research Map | TGRS