Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.153
IF5.153
IF 5-year value: 5.460
IF 5-year
5.460
CiteScore value: 7.8
CiteScore
7.8
SNIP value: 1.623
SNIP1.623
IPP value: 4.91
IPP4.91
SJR value: 2.092
SJR2.092
Scimago H <br class='widget-line-break'>index value: 123
Scimago H
index
123
h5-index value: 65
h5-index65
HESS | Articles | Volume 22, issue 11
Hydrol. Earth Syst. Sci., 22, 5919–5933, 2018
https://doi.org/10.5194/hess-22-5919-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 22, 5919–5933, 2018
https://doi.org/10.5194/hess-22-5919-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 19 Nov 2018

Research article | 19 Nov 2018

Dealing with non-stationarity in sub-daily stochastic rainfall models

Lionel Benoit et al.

Related authors

On the value of high density rain gauge observations for small Alpine headwater catchment hydrology
Anthony Michelon, Lionel Benoit, Harsh Beria, Natalie Ceperley, and Bettina Schaefli
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-371,https://doi.org/10.5194/hess-2020-371, 2020
Preprint under review for HESS
Short summary
Nonstationary stochastic rain type generation: accounting for climate drivers
Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 24, 2841–2854, https://doi.org/10.5194/hess-24-2841-2020,https://doi.org/10.5194/hess-24-2841-2020, 2020
Short summary
On the value of high density rain gauge observations for small Alpine headwater catchments
Anthony Michelon, Lionel Benoit, Harsh Beria, Natalie Ceperley, and Bettina Schaefli
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-683,https://doi.org/10.5194/hess-2019-683, 2020
Manuscript not accepted for further review
Short summary
A high-resolution image time series of the Gorner Glacier – Swiss Alps – derived from repeated unmanned aerial vehicle surveys
Lionel Benoit, Aurelie Gourdon, Raphaël Vallat, Inigo Irarrazaval, Mathieu Gravey, Benjamin Lehmann, Günther Prasicek, Dominik Gräff, Frederic Herman, and Gregoire Mariethoz
Earth Syst. Sci. Data, 11, 579–588, https://doi.org/10.5194/essd-11-579-2019,https://doi.org/10.5194/essd-11-579-2019, 2019
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Stochastic approaches
Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues
Damien Raynaud, Benoit Hingray, Guillaume Evin, Anne-Catherine Favre, and Jérémy Chardon
Hydrol. Earth Syst. Sci., 24, 4339–4352, https://doi.org/10.5194/hess-24-4339-2020,https://doi.org/10.5194/hess-24-4339-2020, 2020
Short summary
A new discrete multiplicative random cascade model for downscaling intermittent rainfall fields
Marc Schleiss
Hydrol. Earth Syst. Sci., 24, 3699–3723, https://doi.org/10.5194/hess-24-3699-2020,https://doi.org/10.5194/hess-24-3699-2020, 2020
Short summary
Modelling rainfall with a Bartlett–Lewis process: new developments
Christian Onof and Li-Pen Wang
Hydrol. Earth Syst. Sci., 24, 2791–2815, https://doi.org/10.5194/hess-24-2791-2020,https://doi.org/10.5194/hess-24-2791-2020, 2020
Short summary
Nonstationary stochastic rain type generation: accounting for climate drivers
Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 24, 2841–2854, https://doi.org/10.5194/hess-24-2841-2020,https://doi.org/10.5194/hess-24-2841-2020, 2020
Short summary
Conditional simulation of surface rainfall fields using modified phase annealing
Jieru Yan, András Bárdossy, Sebastian Hörning, and Tao Tao
Hydrol. Earth Syst. Sci., 24, 2287–2301, https://doi.org/10.5194/hess-24-2287-2020,https://doi.org/10.5194/hess-24-2287-2020, 2020
Short summary

Cited articles

Aghakouchak, A., Nasrollahi, N., Li, J., Imam, J., and Sorooshian, S.: Geometrical Characterization of Precipitation Patterns, J. Hydrometeorol., 12, 274–285, https://doi.org/10.1175/2010JHM1298.1, 2011. a, b
Allcroft, D. J. and Glasbey, C. A.: A latent Gaussian Markov random-field model for spatiotemporal rainfall disaggregation, Appl. Statist., 52, 487–498, https://doi.org/10.1111/1467-9876.00419, 2003. a
Bárdossy, A. and Plate, E. J.: space-time Model for Daily Rainfall Using Atmospheric Circulation Patterns, Water Resour. Res., 28, 1247–1259, https://doi.org/10.1029/91WR02589, 1992. a
Bárdossy, A. and Pegram, G. G. S.: Space-time conditional disaggregation of precipitation at high resolution via simulation, Water Resour. Res., 52, 920–937, https://doi.org/10.1002/2015WR018037, 2016. a, b, c
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical weather prediction, Nature, 525, 47–55, https://doi.org/10.1038/nature14956, 2015. a
Publications Copernicus
Download
Short summary
We propose a method for unsupervised classification of the space–time–intensity structure of weather radar images. The resulting classes are interpreted as rain types, i.e. pools of rain fields with homogeneous statistical properties. Rain types can in turn be used to define stationary periods for further stochastic rainfall modelling. The application of rain typing to real data indicates that non-stationarity can be significant within meteorological seasons, and even within a single storm.
We propose a method for unsupervised classification of the space–time–intensity structure of...
Citation