Technical note: Temperature dependence of precipitation tail heaviness in the TENAX model

Thomas, Ella; Vohnicky, Petr; Borga, Marco; Peleg, Nadav; Marra, Francesco

doi:10.5194/hess-30-4957-2026

Articles | Volume 30, issue 15

https://doi.org/10.5194/hess-30-4957-2026

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

https://doi.org/10.5194/hess-30-4957-2026

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

Articles | Volume 30, issue 15

Technical note

|

06 Aug 2026

Technical note |

| 06 Aug 2026

Technical note: Temperature dependence of precipitation tail heaviness in the TENAX model

Ella Thomas, Petr Vohnicky, Marco Borga, Nadav Peleg, and Francesco Marra

Supplement

https://doi.org/10.5194/hess-30-4957-2026-supplement

Data sets

Subset of Global Sub-Daily Rainfall (GSDR) dataset E. Lewis et al. https://doi.org/10.5281/zenodo.8369987

ERA5-Land hourly data from 1950 to present Copernicus Climate Change Service (C3S) https://doi.org/10.24381/cds.e2161bac

Model code and software

Code for "Technical note: Temperature dependence of precipitation tail heaviness in the TENAX model" Ella Thomas et al. https://doi.org/10.5281/zenodo.20208783

TEmperature-dependent Non-Asymptotic statistical model for eXtreme return levels (TENAX) (1.5) F. Marra and N. Peleg https://doi.org/10.5281/zenodo.15291014

Short summary

Extreme rainfall is expected to grow in magnitude with increasing temperature. We assess whether very rare extremes increase with temperature faster than moderate extremes, and we test methods to include this effect into a model to predict future extremes called TENAX. We find that this dependence on temperature is typically observed but including it in the model without prior information on its magnitude may lead to disproportionately large uncertainty.