Published papers acknowledging the XAIDA project

Bevacqua, E., Zappa, G., Lehner, F., Zscheischler, J. (2022). “Precipitation trends determine future occurrences of compound hot–dry events“. Nature Climate Change.


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., Zscheischler, J. (2021).Guidelines for Studying Diverse Types of Compound Weather and Climate Events“. Earth’s Future. Volume 9, Issue 11. 25 October 2021.


Buriticá, G, Naveau P (2022), “Stable sums to infer high return levels of multivariate rainfall time series”.

Cadiou C., Malhomme N., Noyelle R., Faranda D. (2022). “Challenges in attributing the 2022 Australian rain bombs to climate change”. ⟨hal-03722233⟩
In Press.
Egli, M., Sippel, S., Pendergrass, A. G., de Vries, I., & Knutti, R. (2022). “Reconstruction of zonal precipitation from sparse historical observations using climate model information and statistical learning. Geophysical Research Letters, 49, e2022GL099826.


Faranda, D., Bourdin, S., Ginesta, M., Krouma, M., Messori, G., Noyelle, R., Pons, F., and Yiou, P. (2022) “A climate-change attribution retrospective of some impactful weather extremes of 2021“, Weather Clim. Dynam. Discuss, 3, 1311–1340,


Faranda D., Messori G., Yiou P., Thao S., Pons F., et al. (2022). Dynamical footprints of Hurricanes in the Tropical Dynamics“. Chaos: An Interdisciplinary Journal of Nonlinear Science, In press. <hal-03219409v3>


Gardoll, S., Boucher, O. (2022). “Classification of tropical cyclone containing images using a convolutional neural network: performance and sensitivity to the learning dataset“. EGU sphere.


Li, D., Chen, Y., Messmer, M., Zhu, Y., Qi, J., Feng, J., Yin, B., and Bevacqua, E. (2022). “Compound wind and precipitation extremes across the Indo-Pacific: climatology, variability and drivers“. Geophysical Research Letters, 49, e2022GL098594.


Li, J., Bevacqua, E., Chen, C., Wang, Z., Chen, X., Myneni, R. B., Wu, X., Xu, C., Zhang, Z., and Zscheischler, J. (2022). “Regional asymmetry in the response of global vegetation growth to springtime compound climate events”. Communications Earth & Environment 3,  123.


Naveau, P., Thao, S. (2022). “Multimodel Errors and Emergence of Times in Climate Attribution Studies“. Journal of Climate. Volume 35, Issue 14.


Rivoire, P., Le Gall, P., Favre, A.-C., Naveau, P., Martius, O. (2022) “High return level estimates of daily ERA-5 precipitation in Europe estimated using regionalized extreme value distributions“, Weather and Climate Extremes, Volume 38.


Schumacher D. L., Hauser M., Seneviratne S. (2022), “Drivers and mechanisms of the 2021 Pacific North West Heatwave“. Earth’s Future.


Sippel, S., Meinshausen, N., Székely, E., Fischer, E., Pendergrass, A. G., Lehner, F., and Knutti, R. (2021). “Robust detection of forced warming in the presence of potentially large climate variability“. Science Advances. 7, eabh4429.

Robert Vautard, Geert Jan van Oldenborgh, Rémy Bonnet, Sihan Li, Yoann Robin, Sarah Kew, Sjoukje Philip, Jean-Michel Soubeyroux, Brigitte Dubuisson, Nicolas Viovy, Markus Reichstein, Friederike Otto, and Iñaki Garcia de Cortazar-Atauri (2022). “Human influence on growing-period frosts like the early April 2021 in Central France”, Nat. Hazards Earth Syst. Sci. Discuss.
In press.
Worms J, Naveau P (2022), “Record events attribution in climate studies“. Environmetrics, e2777. 

Zscheischler & Lehner (2021). “Attributing compound events to anthropogenic climate change. BAMS.

Pre-prints and work documents

Bevacqua, E., Jezequel, A., Suarez-Gutierrez, L., Lehner, F., Vrac, M., Yiou, P., and Zscheischler, J. (2022). “Advancing our understanding of compound weather and climate events via large ensemble model simulations”, In review,

Davide Faranda, Gabriele Messori, Stella Bourdin, Mathieu Vrac, Soulivanh Thao, Jacopo Riboldi, Sebastien Fromang, Pascal Yiou. (2022). Correcting biases in tropical cyclone intensities in low-resolution datasets using dynamical systems metrics. ⟨hal-03631098⟩ 

Jiang, S., Bevacqua, E., and Zscheischler, J. (2022). “River flooding mechanisms and their changes in Europe revealed by explainable machine learning”, Hydrol. Earth Syst. Sci. Discuss. [preprint],, in review.

Richards J., Huser R., Bevacqua E., Zscheischler J. (2022). Insights into the drivers and spatio-temporal trends of extreme Mediterranean wildfires with statistical deep-learning. In Review.