Articles | Volume 21, issue 1
https://doi.org/10.5194/hess-21-345-2017
https://doi.org/10.5194/hess-21-345-2017
Research article
 | 
20 Jan 2017
Research article |  | 20 Jan 2017

Formulating and testing a method for perturbing precipitation time series to reflect anticipated climatic changes

Hjalte Jomo Danielsen Sørup, Stylianos Georgiadis, Ida Bülow Gregersen, and Karsten Arnbjerg-Nielsen

Related authors

Data-driven distinction between convective, frontal and mixed extreme rainfall events in radar data
Emma Dybro Thomassen, Hjalte Jomo Danielsen Sørup, Marc Scheibel, Thomas Einfalt, and Karsten Arnbjerg-Nielsen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-397,https://doi.org/10.5194/hess-2020-397, 2020
Preprint withdrawn
Short summary
Explorative Analysis of Long Time Series of Very High Resolution Spatial Rainfall
Emma Dybro Thomassen, Hjalte Jomo Danielsen Sørup, Marc Scheibel, Thomas Einfalt, and Karsten Arnbjerg-Nielsen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-184,https://doi.org/10.5194/hess-2018-184, 2018
Revised manuscript not accepted
Short summary
Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator
Hjalte Jomo Danielsen Sørup, Ole Bøssing Christensen, Karsten Arnbjerg-Nielsen, and Peter Steen Mikkelsen
Hydrol. Earth Syst. Sci., 20, 1387–1403, https://doi.org/10.5194/hess-20-1387-2016,https://doi.org/10.5194/hess-20-1387-2016, 2016
Short summary
On the importance of observational data properties when assessing regional climate model performance of extreme precipitation
M. A. Sunyer, H. J. D. Sørup, O. B. Christensen, H. Madsen, D. Rosbjerg, P. S. Mikkelsen, and K. Arnbjerg-Nielsen
Hydrol. Earth Syst. Sci., 17, 4323–4337, https://doi.org/10.5194/hess-17-4323-2013,https://doi.org/10.5194/hess-17-4323-2013, 2013

Related subject area

Subject: Urban Hydrology | Techniques and Approaches: Modelling approaches
Combining statistical and hydrodynamic models to assess compound flood hazards from rainfall and storm surge: a case study of Shanghai
Hanqing Xu, Elisa Ragno, Sebastiaan N. Jonkman, Jun Wang, Jeremy D. Bricker, Zhan Tian, and Laixiang Sun
Hydrol. Earth Syst. Sci., 28, 3919–3930, https://doi.org/10.5194/hess-28-3919-2024,https://doi.org/10.5194/hess-28-3919-2024, 2024
Short summary
Simulation of spatially distributed sources, transport, and transformation of nitrogen from fertilization and septic system in an exurban watershed
Ruoyu Zhang, Lawrence E. Band, Peter M. Groffman, Amanda K. Suchy, Jonathan M. Duncan, and Arther J. Gold
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-256,https://doi.org/10.5194/hess-2023-256, 2023
Revised manuscript accepted for HESS
Short summary
An optimized long short-term memory (LSTM)-based approach applied to early warning and forecasting of ponding in the urban drainage system
Wen Zhu, Tao Tao, Hexiang Yan, Jieru Yan, Jiaying Wang, Shuping Li, and Kunlun Xin
Hydrol. Earth Syst. Sci., 27, 2035–2050, https://doi.org/10.5194/hess-27-2035-2023,https://doi.org/10.5194/hess-27-2035-2023, 2023
Short summary
A deep-learning-technique-based data-driven model for accurate and rapid flood predictions in temporal and spatial dimensions
Qianqian Zhou, Shuai Teng, Zuxiang Situ, Xiaoting Liao, Junman Feng, Gongfa Chen, Jianliang Zhang, and Zonglei Lu
Hydrol. Earth Syst. Sci., 27, 1791–1808, https://doi.org/10.5194/hess-27-1791-2023,https://doi.org/10.5194/hess-27-1791-2023, 2023
Short summary
Impact of urban geology on model simulations of shallow groundwater levels and flow paths
Ane LaBianca, Mette H. Mortensen, Peter Sandersen, Torben O. Sonnenborg, Karsten H. Jensen, and Jacob Kidmose
Hydrol. Earth Syst. Sci., 27, 1645–1666, https://doi.org/10.5194/hess-27-1645-2023,https://doi.org/10.5194/hess-27-1645-2023, 2023
Short summary

Cited articles

Ailliot, P., Thompson, C., and Thomson, P.: Space-time modelling of precipitation by using a hidden Markov model and censored Gaussian distributions, J. Roy. Stat. Soc. C-App., 58, 405–426, https://doi.org/10.1111/j.1467-9876.2008.00654.x, 2009.
Arnbjerg-Nielsen, K., Funder, S. G., and Madsen, H.: Identifying climate analogues for precipitation extremes for Denmark based on RCM simulations from the ENSEMBLES database, Water Sci. Technol., 71, 418–425, https://doi.org/10.2166/wst.2015.001, 2015a.
Arnbjerg-Nielsen, K., Leonardsen, L., and Madsen, H.: Evaluating adaptation options for urban flooding based on new high-end emission scenario regional climate model simulations, Clim. Res., 64, 73–84, https://doi.org/10.3354/cr01299, 2015b.
Barbu, V. and Limnios, N.: Semi-Markov Chains and Hidden Semi-Markov Models toward Applications: Their Use in Reliability and DNA Analysis, Springer, New York, NY, USA, https://doi.org/10.1007/978-0-387-73173-5, 2008.
Berndtsson, R. and Niemczynowicz, J.: Spatial and temporal scales in rainfall analysis: Some aspects and future perspectives, J. Hydrol., 100, 293–313, https://doi.org/10.1016/0022-1694(88)90189-8, 1988.
Download
Short summary
In this study we propose a methodology changing present-day precipitation time series to reflect future changed climate. Present-day time series have a much finer resolution than what is provided by climate models and thus have a much broader application range. The proposed methodology is able to replicate most expectations of climate change precipitation. These time series can be used to run fine-scale hydrological and hydraulic models and thereby assess the influence of climate change on them.