Articles | Volume 22, issue 1
https://doi.org/10.5194/hess-22-727-2018
© Author(s) 2018. 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-22-727-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Censored rainfall modelling for estimation of fine-scale extremes
David Cross
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK
Christian Onof
Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK
Hugo Winter
EDF Energy R&D UK Centre, Interchange, 81–85 Station Road, Croydon, CR0 2RD, UK
Pietro Bernardara
CEREA, EDF R&D – ENPC, 6 quai Watier, 78400 Chatou, France
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Cited
13 citations as recorded by crossref.
- Coupling of satellite-derived precipitation products with Bartlett-Lewis model to estimate intensity-frequency-duration curves for remote areas M. Islam et al. 10.1016/j.jhydrol.2022.127743
- Flood-related extreme precipitation in southwestern Germany: development of a two-dimensional stochastic precipitation model F. Ehmele & M. Kunz 10.5194/hess-23-1083-2019
- Modelling rainfall with a Bartlett–Lewis process: pyBL (v1.0.0), a Python software package and an application with short records C. Wei et al. 10.5194/gmd-18-1357-2025
- A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales J. Park et al. 10.5194/hess-23-989-2019
- Does the complexity in temporal precipitation disaggregation matter for a lumped hydrological model? H. Müller-Thomy & A. Sikorska-Senoner 10.1080/02626667.2019.1638926
- STORAGE (STOchastic RAinfall GEnerator): A User-Friendly Software for Generating Long and High-Resolution Rainfall Time Series D. De Luca & A. Petroselli 10.3390/hydrology8020076
- Investigation of rainfall disaggregation with flexible timescales based on point process models X. Qin & C. Dai 10.1016/j.jhydrol.2024.131101
- Bartlett–Lewis Model Calibrated with Satellite-Derived Precipitation Data to Estimate Daily Peak 15 Min Rainfall Intensity M. Islam et al. 10.3390/atmos14060985
- Context-Specific Selection of Poisson cluster rainfall models for accurate urban hydrological simulations T. Lian et al. 10.1016/j.jhydrol.2024.132637
- Calibration of NSRP Models from Extreme Value Distributions D. De Luca & L. Galasso 10.3390/hydrology6040089
- A simple scheme to adjust Poisson cluster rectangular pulse rainfall models for improved performance at sub-hourly timescales J. Park et al. 10.1016/j.jhydrol.2021.126296
- Ensemble estimation of future rainfall extremes with temperature dependent censored simulation D. Cross et al. 10.1016/j.advwatres.2019.103479
- Stochastic Models of Rainfall P. Northrop 10.1146/annurev-statistics-040622-023838
13 citations as recorded by crossref.
- Coupling of satellite-derived precipitation products with Bartlett-Lewis model to estimate intensity-frequency-duration curves for remote areas M. Islam et al. 10.1016/j.jhydrol.2022.127743
- Flood-related extreme precipitation in southwestern Germany: development of a two-dimensional stochastic precipitation model F. Ehmele & M. Kunz 10.5194/hess-23-1083-2019
- Modelling rainfall with a Bartlett–Lewis process: pyBL (v1.0.0), a Python software package and an application with short records C. Wei et al. 10.5194/gmd-18-1357-2025
- A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales J. Park et al. 10.5194/hess-23-989-2019
- Does the complexity in temporal precipitation disaggregation matter for a lumped hydrological model? H. Müller-Thomy & A. Sikorska-Senoner 10.1080/02626667.2019.1638926
- STORAGE (STOchastic RAinfall GEnerator): A User-Friendly Software for Generating Long and High-Resolution Rainfall Time Series D. De Luca & A. Petroselli 10.3390/hydrology8020076
- Investigation of rainfall disaggregation with flexible timescales based on point process models X. Qin & C. Dai 10.1016/j.jhydrol.2024.131101
- Bartlett–Lewis Model Calibrated with Satellite-Derived Precipitation Data to Estimate Daily Peak 15 Min Rainfall Intensity M. Islam et al. 10.3390/atmos14060985
- Context-Specific Selection of Poisson cluster rainfall models for accurate urban hydrological simulations T. Lian et al. 10.1016/j.jhydrol.2024.132637
- Calibration of NSRP Models from Extreme Value Distributions D. De Luca & L. Galasso 10.3390/hydrology6040089
- A simple scheme to adjust Poisson cluster rectangular pulse rainfall models for improved performance at sub-hourly timescales J. Park et al. 10.1016/j.jhydrol.2021.126296
- Ensemble estimation of future rainfall extremes with temperature dependent censored simulation D. Cross et al. 10.1016/j.advwatres.2019.103479
- Stochastic Models of Rainfall P. Northrop 10.1146/annurev-statistics-040622-023838
Latest update: 05 Apr 2025
Short summary
Extreme rainfall is one of the most significant natural hazards. However, estimating very large events is highly uncertain. We present a new approach to construct intense rainfall using the structure of rainfall generation in clouds. The method is particularly effective at estimating short-duration extremes, which can be the most damaging. This is expected to have immediate impact for the estimation of very rare downpours, with the potential to improve climate resilience and hazard preparedness.
Extreme rainfall is one of the most significant natural hazards. However, estimating very large...
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