Articles | Volume 16, issue 6
https://doi.org/10.5194/esd-16-2225-2025
https://doi.org/10.5194/esd-16-2225-2025
Research article
 | 
17 Dec 2025
Research article |  | 17 Dec 2025

Multi-annual predictions of hot, dry and hot-dry compound extremes

Alvise Aranyossy, Paolo De Luca, Carlos Delgado-Torres, Balakrishnan Solaraju-Murali, Margarida Samso Cabre, and Markus G. Donat

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Cited articles

Aranyossy, A.: Multi-annual predictions of hot, dry and hot-dry compound extremes, Zenodo [code], https://doi.org/10.5281/zenodo.17867448, 2025. a
Beguería, S., Vicente-Serrano, S. M., Reig, F., and Latorre, B.: Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring, International Journal of Climatology, 34, 3001–3023, 2014. a
Bethke, I., Wang, Y., Counillon, F., Keenlyside, N., Kimmritz, M., Fransner, F., Samuelsen, A., Langehaug, H., Svendsen, L., Chiu, P.-G., Passos, L., Bentsen, M., Guo, C., Gupta, A., Tjiputra, J., Kirkevåg, A., Olivié, D., Seland, Ø., Solsvik Vågane, J., Fan, Y., and Eldevik, T.: NorCPM1 and its contribution to CMIP6 DCPP, Geosci. Model Dev., 14, 7073–7116, https://doi.org/10.5194/gmd-14-7073-2021, 2021. a, b
Bevacqua, E., De Michele, C., Manning, C., Couasnon, A., Ribeiro, A. F. S., Ramos, A. M., Vignotto, E., Bastos, A., Blesić, S., Durante, F., Hillier, J., Oliveira, S. C., Pinto, J. G., Ragno, E., Rivoire, P., Saunders, K., Van Der Wiel, K., Wu, W., Zhang, T., and Zscheischler, J.: Guidelines for studying diverse types of compound weather and climate events, Earth's Future, 9, e2021EF002340, https://doi.org/10.1029/2021EF002340, 2021. a
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We investigate multi-year predictability of hot, dry and hot-dry compound events, using the Coupled Model Intercomparison Project Phase 6 decadal hindcast experiments, focusing on the forecast years 2–5. We find that hot-dry compound and hot extremes are skillfully predicted in many regions, but lower skill is found for dry extremes. The skill is largely due to long-term trends in response to external forcing, while added skill from initialisation is limited to a few regions.
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