Articles | Volume 28, issue 2
https://doi.org/10.5194/hess-28-375-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-375-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 Jan 2024
Research article |
| 31 Jan 2024
| 31 Jan 2024
Predicting extreme sub-hourly precipitation intensification based on temperature shifts
Department of Geosciences, University of Padova, Padua, Italy
Institute of Atmospheric Sciences and Climate, National Research Council, Bologna, Italy
Marika Koukoula
Institute of Earth Surface Dynamics, University of Lausanne, Lausanne, Switzerland
Antonio Canale
Department of Statistical Sciences, University of Padova, Padua, Italy
Institute of Earth Surface Dynamics, University of Lausanne, Lausanne, Switzerland
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Cited
14 citations as recorded by crossref.
- Utilizing non-stationary extreme value model to quantify extreme rainfall in two major cities in Bangladesh A. Dey & M. Patwary 10.1007/s00477-025-02969-3
- Estimation of future rainfall extreme values by temperature-dependent disaggregation of climate model data N. Ebers et al. 10.5194/nhess-24-2025-2024
- Estimation of design precipitation using weather radar in Germany: A comparison of statistical methods K. Lengfeld & F. Marra 10.1016/j.ejrh.2024.101952
- Urbanization Enhances Shorter‐Duration Precipitation Intensity in the Yangtze River Delta Region X. Xie et al. 10.1029/2024JD043300
- A 2°C warming can double the frequency of extreme summer downpours in the Alps N. Peleg et al. 10.1038/s41612-025-01081-1
- A simple and robust approach for adapting design storms to assess climate-induced changes in flash flood hazard N. Peleg et al. 10.1016/j.advwatres.2024.104823
- Enhancing generalizability of data-driven urban flood models by incorporating contextual information T. Cache et al. 10.5194/hess-28-5443-2024
- A non-stationary climate-informed weather generator for assessing future flood risks V. Nguyen et al. 10.5194/ascmo-10-195-2024
- Impacts of urban dynamics and thermodynamics on convective rainfall across different urban forms H. Torelló-Sentelles et al. 10.1016/j.uclim.2025.102499
- Predictive modeling of daily precipitation occurrence using weather data of prior days in various climates G. Mahtabi et al. 10.1007/s12145-024-01289-4
- Deriving Future Rainfall Depth-Duration-Frequency Curves from Hourly Regional Climate Projections and Simple Scaling in Sicily G. Buonacera et al. 10.1007/s11269-025-04219-1
- Climate change shifts risk of soil salinity and land degradation in water-scarce regions I. Kramer et al. 10.1016/j.agwat.2024.109223
- Future precipitation extremes and urban flood risk assessment using a non-stationary and convection-permitting climate-hydrodynamic modeling framework P. Laux et al. 10.1016/j.jhydrol.2025.133607
- Modelling non-stationarity in extreme rainfall using large-scale climate drivers L. Jayaweera et al. 10.1016/j.jhydrol.2024.131309
14 citations as recorded by crossref.
- Utilizing non-stationary extreme value model to quantify extreme rainfall in two major cities in Bangladesh A. Dey & M. Patwary 10.1007/s00477-025-02969-3
- Estimation of future rainfall extreme values by temperature-dependent disaggregation of climate model data N. Ebers et al. 10.5194/nhess-24-2025-2024
- Estimation of design precipitation using weather radar in Germany: A comparison of statistical methods K. Lengfeld & F. Marra 10.1016/j.ejrh.2024.101952
- Urbanization Enhances Shorter‐Duration Precipitation Intensity in the Yangtze River Delta Region X. Xie et al. 10.1029/2024JD043300
- A 2°C warming can double the frequency of extreme summer downpours in the Alps N. Peleg et al. 10.1038/s41612-025-01081-1
- A simple and robust approach for adapting design storms to assess climate-induced changes in flash flood hazard N. Peleg et al. 10.1016/j.advwatres.2024.104823
- Enhancing generalizability of data-driven urban flood models by incorporating contextual information T. Cache et al. 10.5194/hess-28-5443-2024
- A non-stationary climate-informed weather generator for assessing future flood risks V. Nguyen et al. 10.5194/ascmo-10-195-2024
- Impacts of urban dynamics and thermodynamics on convective rainfall across different urban forms H. Torelló-Sentelles et al. 10.1016/j.uclim.2025.102499
- Predictive modeling of daily precipitation occurrence using weather data of prior days in various climates G. Mahtabi et al. 10.1007/s12145-024-01289-4
- Deriving Future Rainfall Depth-Duration-Frequency Curves from Hourly Regional Climate Projections and Simple Scaling in Sicily G. Buonacera et al. 10.1007/s11269-025-04219-1
- Climate change shifts risk of soil salinity and land degradation in water-scarce regions I. Kramer et al. 10.1016/j.agwat.2024.109223
- Future precipitation extremes and urban flood risk assessment using a non-stationary and convection-permitting climate-hydrodynamic modeling framework P. Laux et al. 10.1016/j.jhydrol.2025.133607
- Modelling non-stationarity in extreme rainfall using large-scale climate drivers L. Jayaweera et al. 10.1016/j.jhydrol.2024.131309
Latest update: 07 Jul 2025
Short summary
We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
We present a new physical-based method for estimating extreme sub-hourly precipitation return...
