Articles | Volume 20, issue 4
Hydrol. Earth Syst. Sci., 20, 1387–1403, 2016
https://doi.org/10.5194/hess-20-1387-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 20, 1387–1403, 2016
https://doi.org/10.5194/hess-20-1387-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
08 Apr 2016
Research article
| 08 Apr 2016
Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator
Hjalte Jomo Danielsen Sørup et al.
Related authors
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Preprint withdrawn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
Short summary
This study examines characteristics of extreme events of a 13 year long record of 1 × 1 km spatial resolution and durations ranging from 15-minute to daily durations by means of simple data driven methods. We found that these analyses enabled us to distinguish and characterise types of extreme events useful for urban hydrology applications. The result is useful e.g. for selecting events of particular interest when assessing performance of e.g. urban drainage systems.
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
Short summary
This article takes the first steps in describing rainfall with spatio-temporal variations. A detailed description of rainfall will provide an improved planning tool for protecting cities against pluvial flooding. The article uses high resolution radar data from the catchment of the river Wupper, North Rhine-Westphalia, Germany. The spatio-temporal properties of extreme rain events was described with 16 variables. Three statistical methods were applied and four rainfall types were identified.
Hjalte Jomo Danielsen Sørup, Stylianos Georgiadis, Ida Bülow Gregersen, and Karsten Arnbjerg-Nielsen
Hydrol. Earth Syst. Sci., 21, 345–355, https://doi.org/10.5194/hess-21-345-2017, https://doi.org/10.5194/hess-21-345-2017, 2017
Short summary
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.
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
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
Short summary
Short summary
Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
Erika Médus, Emma D. Thomassen, Danijel Belušić, Petter Lind, Peter Berg, Jens H. Christensen, Ole B. Christensen, Andreas Dobler, Erik Kjellström, Jonas Olsson, and Wei Yang
Nat. Hazards Earth Syst. Sci., 22, 693–711, https://doi.org/10.5194/nhess-22-693-2022, https://doi.org/10.5194/nhess-22-693-2022, 2022
Short summary
Short summary
We evaluate the skill of a regional climate model, HARMONIE-Climate, to capture the present-day characteristics of heavy precipitation in the Nordic region and investigate the added value provided by a convection-permitting model version. The higher model resolution improves the representation of hourly heavy- and extreme-precipitation events and their diurnal cycle. The results indicate the benefits of convection-permitting models for constructing climate change projections over the region.
H. E. Markus Meier, Christian Dieterich, Matthias Gröger, Cyril Dutheil, Florian Börgel, Kseniia Safonova, Ole B. Christensen, and Erik Kjellström
Earth Syst. Dynam., 13, 159–199, https://doi.org/10.5194/esd-13-159-2022, https://doi.org/10.5194/esd-13-159-2022, 2022
Short summary
Short summary
In addition to environmental pressures such as eutrophication, overfishing and contaminants, climate change is believed to have an important impact on the marine environment in the future, and marine management should consider the related risks. Hence, we have compared and assessed available scenario simulations for the Baltic Sea and found considerable uncertainties of the projections caused by the underlying assumptions and model biases, in particular for the water and biogeochemical cycles.
Ole Bøssing Christensen, Erik Kjellström, Christian Dieterich, Matthias Gröger, and Hans Eberhard Markus Meier
Earth Syst. Dynam., 13, 133–157, https://doi.org/10.5194/esd-13-133-2022, https://doi.org/10.5194/esd-13-133-2022, 2022
Short summary
Short summary
The Baltic Sea Region is very sensitive to climate change, whose impacts could easily exacerbate biodiversity stress from society and eutrophication of the Baltic Sea. Therefore, there has been a focus on estimations of future climate change and its impacts in recent research. Models show a strong warming, in particular in the north in winter. Precipitation is projected to increase in the whole region apart from the south during summer. New results improve estimates of future climate change.
Torben Schmith, Peter Thejll, Peter Berg, Fredrik Boberg, Ole Bøssing Christensen, Bo Christiansen, Jens Hesselbjerg Christensen, Marianne Sloth Madsen, and Christian Steger
Hydrol. Earth Syst. Sci., 25, 273–290, https://doi.org/10.5194/hess-25-273-2021, https://doi.org/10.5194/hess-25-273-2021, 2021
Short summary
Short summary
European extreme precipitation is expected to change in the future; this is based on climate model projections. But, since climate models have errors, projections are uncertain. We study this uncertainty in the projections by comparing results from an ensemble of 19 climate models. Results can be used to give improved estimates of future extreme precipitation for Europe.
Marie-Estelle Demory, Ségolène Berthou, Jesús Fernández, Silje L. Sørland, Roman Brogli, Malcolm J. Roberts, Urs Beyerle, Jon Seddon, Rein Haarsma, Christoph Schär, Erasmo Buonomo, Ole B. Christensen, James M. Ciarlo ̀, Rowan Fealy, Grigory Nikulin, Daniele Peano, Dian Putrasahan, Christopher D. Roberts, Retish Senan, Christian Steger, Claas Teichmann, and Robert Vautard
Geosci. Model Dev., 13, 5485–5506, https://doi.org/10.5194/gmd-13-5485-2020, https://doi.org/10.5194/gmd-13-5485-2020, 2020
Short summary
Short summary
Now that global climate models (GCMs) can run at similar resolutions to regional climate models (RCMs), one may wonder whether GCMs and RCMs provide similar regional climate information. We perform an evaluation for daily precipitation distribution in PRIMAVERA GCMs (25–50 km resolution) and CORDEX RCMs (12–50 km resolution) over Europe. We show that PRIMAVERA and CORDEX simulate similar distributions. Considering both datasets at such a resolution results in large benefits for impact studies.
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
Short summary
This study examines characteristics of extreme events of a 13 year long record of 1 × 1 km spatial resolution and durations ranging from 15-minute to daily durations by means of simple data driven methods. We found that these analyses enabled us to distinguish and characterise types of extreme events useful for urban hydrology applications. The result is useful e.g. for selecting events of particular interest when assessing performance of e.g. urban drainage systems.
Roland Löwe and Karsten Arnbjerg-Nielsen
Nat. Hazards Earth Syst. Sci., 20, 981–997, https://doi.org/10.5194/nhess-20-981-2020, https://doi.org/10.5194/nhess-20-981-2020, 2020
Short summary
Short summary
To consider potential future urban developments in pluvial flood risk assessment, we develop empirical relationships for imperviousness and flood damage based on an analysis of existing urban characteristics. Results suggest that (1) data resolutions must be carefully selected, (2) there are lower limits for the spatial scale at which predictions can be generated, and (3) depth-dependent damage estimates are challenging to reproduce empirically and can be vulnerable to simulation artifacts.
Peter Berg, Ole B. Christensen, Katharina Klehmet, Geert Lenderink, Jonas Olsson, Claas Teichmann, and Wei Yang
Nat. Hazards Earth Syst. Sci., 19, 957–971, https://doi.org/10.5194/nhess-19-957-2019, https://doi.org/10.5194/nhess-19-957-2019, 2019
Short summary
Short summary
A state-of-the-art regional climate model ensemble for Europe is investigated for extreme precipitation intensities. The models poorly reproduce short duration events of less than a few hours. Further, there is poor connection to some known hotspots for extreme cases. The model performance is much improved at 12 h durations. Projected future increases scale with seasonal mean temperature change, within a range from a few percent to over 10 percent per degree Celsius.
Giuliano Di Baldassarre, Heidi Kreibich, Sergiy Vorogushyn, Jeroen Aerts, Karsten Arnbjerg-Nielsen, Marlies Barendrecht, Paul Bates, Marco Borga, Wouter Botzen, Philip Bubeck, Bruna De Marchi, Carmen Llasat, Maurizio Mazzoleni, Daniela Molinari, Elena Mondino, Johanna Mård, Olga Petrucci, Anna Scolobig, Alberto Viglione, and Philip J. Ward
Hydrol. Earth Syst. Sci., 22, 5629–5637, https://doi.org/10.5194/hess-22-5629-2018, https://doi.org/10.5194/hess-22-5629-2018, 2018
Short summary
Short summary
One common approach to cope with floods is the implementation of structural flood protection measures, such as levees. Numerous scholars have problematized this approach and shown that increasing levels of flood protection can generate a false sense of security and attract more people to the risky areas. We briefly review the literature on this topic and then propose a research agenda to explore the unintended consequences of structural flood protection.
Erik Kjellström, Grigory Nikulin, Gustav Strandberg, Ole Bøssing Christensen, Daniela Jacob, Klaus Keuler, Geert Lenderink, Erik van Meijgaard, Christoph Schär, Samuel Somot, Silje Lund Sørland, Claas Teichmann, and Robert Vautard
Earth Syst. Dynam., 9, 459–478, https://doi.org/10.5194/esd-9-459-2018, https://doi.org/10.5194/esd-9-459-2018, 2018
Short summary
Short summary
Based on high-resolution regional climate models we investigate European climate change at 1.5 and 2 °C of global warming compared to pre-industrial levels. Considerable near-surface warming exceeding that of the global mean is found for most of Europe, already at the lower 1.5 °C of warming level. Changes in precipitation and near-surface wind speed are identified. The 1.5 °C of warming level shows significantly less change compared to the 2 °C level, indicating the importance of mitigation.
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
Short summary
This article takes the first steps in describing rainfall with spatio-temporal variations. A detailed description of rainfall will provide an improved planning tool for protecting cities against pluvial flooding. The article uses high resolution radar data from the catchment of the river Wupper, North Rhine-Westphalia, Germany. The spatio-temporal properties of extreme rain events was described with 16 variables. Three statistical methods were applied and four rainfall types were identified.
Per Skougaard Kaspersen, Nanna Høegh Ravn, Karsten Arnbjerg-Nielsen, Henrik Madsen, and Martin Drews
Hydrol. Earth Syst. Sci., 21, 4131–4147, https://doi.org/10.5194/hess-21-4131-2017, https://doi.org/10.5194/hess-21-4131-2017, 2017
Søren Thorndahl, Thomas Einfalt, Patrick Willems, Jesper Ellerbæk Nielsen, Marie-Claire ten Veldhuis, Karsten Arnbjerg-Nielsen, Michael R. Rasmussen, and Peter Molnar
Hydrol. Earth Syst. Sci., 21, 1359–1380, https://doi.org/10.5194/hess-21-1359-2017, https://doi.org/10.5194/hess-21-1359-2017, 2017
Short summary
Short summary
This paper reviews how weather radar data can be used in urban hydrological applications. It focuses on three areas of research: (1) temporal and spatial resolution of rainfall data, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Moreover, the paper provides examples of urban hydrological applications which can benefit from radar rainfall data in comparison to tradition rain gauge measurements of rainfall.
Hjalte Jomo Danielsen Sørup, Stylianos Georgiadis, Ida Bülow Gregersen, and Karsten Arnbjerg-Nielsen
Hydrol. Earth Syst. Sci., 21, 345–355, https://doi.org/10.5194/hess-21-345-2017, https://doi.org/10.5194/hess-21-345-2017, 2017
Short summary
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.
P. Skougaard Kaspersen, N. Høegh Ravn, K. Arnbjerg-Nielsen, H. Madsen, and M. Drews
Proc. IAHS, 370, 21–27, https://doi.org/10.5194/piahs-370-21-2015, https://doi.org/10.5194/piahs-370-21-2015, 2015
Short summary
Short summary
A combined remote sensing and hydrological modelling approach is developed to examine the influence of urban land cover changes and climate change for the exposure of cities towards flooding. Results show that the past 30 years of urban development has increased the exposure to pluvial flooding by 6-26%. Corresponding estimates for a medium and high climate change scenario (2071-2100) are 40% and 100%, indicating that urban land cover changes are central for the exposure of cities to flooding.
M. A. D. Larsen, J. C. Refsgaard, M. Drews, M. B. Butts, K. H. Jensen, J. H. Christensen, and O. B. Christensen
Hydrol. Earth Syst. Sci., 18, 4733–4749, https://doi.org/10.5194/hess-18-4733-2014, https://doi.org/10.5194/hess-18-4733-2014, 2014
Short summary
Short summary
The paper presents results from a novel dynamical coupling between a hydrology model and a regional climate model developed to include a wider range of processes, land-surface/atmosphere interaction and finer spatio-temporal scales. The coupled performance was largely dependent on the data exchange frequency between the two model components, and longer-term precipitation was somewhat improved by the coupled system whereas the short-term dynamics for a range of variables was less accurate.
B. Merz, J. Aerts, K. Arnbjerg-Nielsen, M. Baldi, A. Becker, A. Bichet, G. Blöschl, L. M. Bouwer, A. Brauer, F. Cioffi, J. M. Delgado, M. Gocht, F. Guzzetti, S. Harrigan, K. Hirschboeck, C. Kilsby, W. Kron, H.-H. Kwon, U. Lall, R. Merz, K. Nissen, P. Salvatti, T. Swierczynski, U. Ulbrich, A. Viglione, P. J. Ward, M. Weiler, B. Wilhelm, and M. Nied
Nat. Hazards Earth Syst. Sci., 14, 1921–1942, https://doi.org/10.5194/nhess-14-1921-2014, https://doi.org/10.5194/nhess-14-1921-2014, 2014
S. Kotlarski, K. Keuler, O. B. Christensen, A. Colette, M. Déqué, A. Gobiet, K. Goergen, D. Jacob, D. Lüthi, E. van Meijgaard, G. Nikulin, C. Schär, C. Teichmann, R. Vautard, K. Warrach-Sagi, and V. Wulfmeyer
Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, https://doi.org/10.5194/gmd-7-1297-2014, 2014
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: Stochastic approaches
Improving radar-based rainfall nowcasting by a nearest-neighbour approach – Part 1: Storm characteristics
The role of storm scale, position and movement in controlling urban flood response
Event-based stochastic point rainfall resampling for statistical replication and climate projection of historical rainfall series
Statistical analysis of hydrological response in urbanising catchments based on adaptive sampling using inter-amount times
Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling
Local impact analysis of climate change on precipitation extremes: are high-resolution climate models needed for realistic simulations?
Stochastic rainfall analysis for storm tank performance evaluation
Bora Shehu and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 26, 1631–1658, https://doi.org/10.5194/hess-26-1631-2022, https://doi.org/10.5194/hess-26-1631-2022, 2022
Short summary
Short summary
In this paper we investigate whether similar storms behave similarly and whether the information obtained from past similar storms can improve storm nowcast based on radar data. Here a nearest-neighbour approach is employed to first identify similar storms and later to issue either a single or an ensemble nowcast based on k most similar past storms. The results indicate that the information obtained from similar storms can reduce the errors considerably, especially for convective storm nowcast.
Marie-Claire ten Veldhuis, Zhengzheng Zhou, Long Yang, Shuguang Liu, and James Smith
Hydrol. Earth Syst. Sci., 22, 417–436, https://doi.org/10.5194/hess-22-417-2018, https://doi.org/10.5194/hess-22-417-2018, 2018
Short summary
Short summary
The effect of storm scale and movement on runoff flows in urban catchments remains poorly understood due to the complexity of urban land use and man-made infrastructure. In this study, interactions among rainfall, urbanisation and peak flows were analyzed based on 15 years of radar rainfall and flow observations. We found that flow-path networks strongly smoothed rainfall peaks. Unexpectedly, the storm position relative to impervious cover within the basins had little effect on flow peaks.
Søren Thorndahl, Aske Korup Andersen, and Anders Badsberg Larsen
Hydrol. Earth Syst. Sci., 21, 4433–4448, https://doi.org/10.5194/hess-21-4433-2017, https://doi.org/10.5194/hess-21-4433-2017, 2017
Short summary
Short summary
Time series of rainfall are developed in order to represent future climate conditions. These series can be used in design of, for example, drainage systems where future rainfall loads are important to account for. The climate projections are evaluated on a number of key statistical parameters of rainfall such as yearly and seasonal precipitation amounts, number of extreme events and rainfall intensities, specific duration, and return periods.
Marie-Claire ten Veldhuis and Marc Schleiss
Hydrol. Earth Syst. Sci., 21, 1991–2013, https://doi.org/10.5194/hess-21-1991-2017, https://doi.org/10.5194/hess-21-1991-2017, 2017
Short summary
Short summary
In this paper we analysed flow measurements from 17 watersheds in a (semi-)urban region, to characterise flow patterns according to basin features. Instead of sampling flows at fixed time intervals, we looked at how fast given amounts of flow were accumulated. By doing so, we could identify patterns of flow regulation in urban streams and quantify flashiness of hydrological response. We were able to show that in this region, higher urbanisation was clearly associated with lower basin flashiness.
Nadav Peleg, Frank Blumensaat, Peter Molnar, Simone Fatichi, and Paolo Burlando
Hydrol. Earth Syst. Sci., 21, 1559–1572, https://doi.org/10.5194/hess-21-1559-2017, https://doi.org/10.5194/hess-21-1559-2017, 2017
Short summary
Short summary
We investigated the relative contribution of the spatial versus climatic rainfall variability for flow peaks by applying an advanced stochastic rainfall generator to simulate rainfall for a small urban catchment and simulate flow dynamics in the sewer system. We found that the main contribution to the total flow variability originates from the natural climate variability. The contribution of spatial rainfall variability to the total flow variability was found to increase with return periods.
Hossein Tabari, Rozemien De Troch, Olivier Giot, Rafiq Hamdi, Piet Termonia, Sajjad Saeed, Erwan Brisson, Nicole Van Lipzig, and Patrick Willems
Hydrol. Earth Syst. Sci., 20, 3843–3857, https://doi.org/10.5194/hess-20-3843-2016, https://doi.org/10.5194/hess-20-3843-2016, 2016
I. Andrés-Doménech, A. Montanari, and J. B. Marco
Hydrol. Earth Syst. Sci., 14, 1221–1232, https://doi.org/10.5194/hess-14-1221-2010, https://doi.org/10.5194/hess-14-1221-2010, 2010
Cited articles
Arnbjerg-Nielsen, K. and Onof, C.: Quantification of anticipated future changes in high resolution design rainfall for urban areas, Atmos. Res., 2, 350–363, https://doi.org/10.1016/j.atmosres.2009.01.014, 2009.
Arnbjerg-Nielsen, K., Willems, P., Olsson, J., Beecham, S., Pathirana, A., Gregersen, I. B., Madsen, H., Nguyen, V.-T.-V.: Impacts of climate change on rainfall extremes and urban drainage systems: a review, Water Sci. Technol., 68, 16–28, https://doi.org/10.2166/wst.2013.251, 2013.
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., and Kristjánsson, J. E.: The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687–720, https://doi.org/10.5194/gmd-6-687-2013, 2013.
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.
Burton, A., Kilsby, C. G., Fowler, H. J., Cowpertwait, P. S. P., and O'Connel, P. E.: RainSim: a spatial temporal stochastic rainfall modelling system, Environ. Model. Softw., 23, 1356–1369, https://doi.org/10.1016/j.envsoft.2008.04.003, 2008.
Burton, A., Fowler, H. J., Kilsby, C. G., and O'Connell, P. E.: A stochastic model for the spatial-temporal simulation of nonhomogeneous rainfall occurrence and amounts, Water Resour. Res., 46, W11501, https://doi.org/10.1029/2009WR008884, 2010a.
Burton, A., Fowler, H. J., Blenkinsop, S., and Kilsby, C. G.: Downscaling transient climate change using a Neyman–Scott Rectangular Pulses stochastic rainfall model, J. Hydrol., 381, 18–32, https://doi.org/10.1016/j.jhydrol.2009.10.031, 2010b.
Chen, J., Brissette, F. P., and Leconte, R.: A daily stochastic weather generator for preserving low-frequency of climate variability, J. Hydrol., 388, 480–490, https://doi.org/10.1016/j.jhydrol.2010.05.032, 2010.
Christensen, O. B. and Christensen, J. H.: A summary of the PRUDENCE model projections of changes in European climate by the end of the century, Climatic Change, 81, 7–30, https://doi.org/10.1007/s10584-006-9210-7, 2007.
Christensen, O. B., Drews, M., Christensen, J. H., Dethloff, K., Ketelsen, K., Hebestadt, I., and Rinke, A.: The HIRHAM Regional Climate Model, version 5(β), Danish Meteorological Institute Technical report 06-17, Danish Meteorological Institute, Copenhagen, Denmark, 22 pp., 2006.
Cowpertwait, P. S. P.: A Poisson-cluster model of rainfall: high-order moments and extreme values, P. Roy. Soc. A, 454, 885–898, https://doi.org/10.1098/rspa.1998.0191, 1998.
Cowpertwait, P. S. P.: A spatial-temporal point process model of rainfall for the Thames catchment, UK, J. Hydrol., 330, 586–595, https://doi.org/10.1016/j.jhydrol.2006.04.043, 2006.
Cowpertwait, P. S. P. and O'Connell, P. E.: A Regionalised Neyman–Scott Model of Rainfall with Convective and Stratiform Cells, Hydrol. Earth Syst. Sci., 1, 71–80, https://doi.org/10.5194/hess-1-71-1997, 1997.
Cowpertwait, P. S. P., Ocio, D., Collazos, G., de Cos, O., and Stocker, C.: Regionalised spatiotemporal rainfall and temperature models for flood studies in the Basque Country, Spain, Hydrol. Earth Syst. Sci., 17, 479–494, https://doi.org/10.5194/hess-17-479-2013, 2013.
Fowler, A. M. and Hennessy, K. J.: Potential impacts of global warming on the frequency and magnitude of heavy precipitation, Nat. Hazards, 11, 283–303, https://doi.org/10.1007/BF00613411, 1995.
Fowler, H. J., Blenkinsop, S., and Tebaldi, C.: Review linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling, Int. J. Climatol., 27, 1547–1578, https://doi.org/10.1002/joc.1556, 2007.
Fox Maule, C., Mayer, S., Sobolowski, S. and Christensen, O. B.: Background information on the RiskChange simulations by BCCR and DMI, Danish Climate Centre Report 14-05, The Danish Meteorological Institute, Copenhagen, Denmark, 15 pp., 2014.
Furrer, E. M. and Katz R. W.: Improving the simulation of extreme precipitation events by stochastic weather generators, Water Resour. Res., 44, W12439, https://doi.org/10.1029/2008WR007316, 2008.
Gregersen, I. B., Sørup, H. J. D., Madsen, H., Rosbjerg, D., Mikkelsen, P. S., and Arnbjerg-Nielsen, K.: Assessing future climatic changes of rainfall extremes at small spatio-temporal scales, Climatic Change, 118, 783–797, https://doi.org/10.1007/s10584-012-0669-0, 2013.
Hazeleger, W., Wang, X., Severijns, C., Ştefănescu, S., Bintanja, R., Sterl, A., Wyser, K., Semmler, T., Yang, S., van den Hurk, B., van Noije, T., van der Linden, E., and van der Wiel, K.: EC-Earth V2.2: description and validation of a new seamless earth system prediction model, Clim. Dynam., 39, 2611–2629, https://doi.org/10.1007/s00382-011-1228-5, 2012.
Hundecha, Y., Pahlow, M., and Schumann, A.: Modeling of daily precipitation at multiple locations using a mixture of distributions to characterize the extremes, Water Resour. Res., 45, W12412, https://doi.org/10.1029/2008WR007453, 2009.
Jørgensen, H. K., Rosenørn, S., Madsen, H., and Mikkelsen, P. S.: Quality control of rain data used for urban runoff systems, Water Sci. Technol., 37, 113–120, https://doi.org/10.1016/S0273-1223(98)00323-0, 1998.
Kendon, E. J., Roberts, N. M., Fowler, H. J., Roberts, M. J., Chan, S. C., and Senior, C. A.: Heavier summer downpours with climate change revealed by weather forecast resolution model, Nat. Clim. Change, 4, 570–576, 2014.
Larsen, A. N., Gregersen, I. B., Christensen, O. B., Linde, J. J., and Mikkelsen, P. S.: Potential future increase in extreme precipitation events over Europe due to climate change, Water Sci. Technol., 60, 2205–2216, https://doi.org/10.2166/wst.2009.650, 2009.
Madsen, H., Mikkelsen, P. S., Rosbjerg, D., and Harremoes, P.: Regional estimation of rainfall intensity-duration-frequency curves using generalized least squares regression of partial duration series statistics, Water Resour. Res., 38, 21-1–21-11, https://doi.org/10.1029/2001WR001125, 2002.
Madsen, H., Arnbjerg-Nielsen, K., and Mikkelsen, P. S.: Update of regional intensity-duration-frequency curves in Denmark: Tendency towards increased storm intensities, Atmos. Res., 92, 343–349, https://doi.org/10.1016/j.atmosres.2009.01.013, 2009.
Maraun, D., Wetterhall, F., Ireson, A. M., Chandler, R. E., Kendon, E. J., Widmann, M., Brienen, S., Rust, H. W., Sauter, T., ThemeßI, M., Venema, V. K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., and Thiele-Eich, I.:. Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user, Rev. Geophys., 48, RG3003, https://doi.org/10.1029/2009RG000314, 2010.
Mayer, S., Maule, C., Sobolowski, S., Christensen, O., Sørup, H., Sunyer, M., Arnbjerg-Nielsen, K., and Barstad, I.: Identifying added value in high-resolution climate simulations over Scandinavia, Tellus A, 67, 24941, https://doi.org/10.3402/tellusa.v67.24941, 2015.
Meijgaard, E. V., Ulft, L. H. V., v. d. Berg, W. J., Bosveld, F. C., v. d. Hurk, B. J. J. M., Lenderink, G., and Siebesma, A. P.: The KNMI regional atmospheric climate model RACMO, version 2.1, Report no. 302, KNMI Technical Report, KNMI, De Bilt, the Netherlands, 50 pp., 2008.
Mikkelsen, P. S., Madsen, H., Rosbjerg, D., and Harremoes, P.: Properties of extreme point rainfall. 3. Identification of spatial inter-site correlation structure, Atmos. Res., 40, 77–98, https://doi.org/10.1016/0169-8095(95)00026-7, 1996.
Mikkelsen, P. S., Madsen, H., Arnbjerg-Nielsen, K., Jørgensen, H. K., Rosbjerg, D., and Harremoës, P.: A rationale for using local and regional point rainfall data for design and analysis of urban storm drainage systems, Water Sci. Technol., 37, 7–14, 1998.
Molnar, P., and Burlando, P.: Variability in the scale properties of high-resolution precipitation data in the Alpine climate of Switzerland, Water Resour. Res., 44, W10404, https://doi.org/10.1029/2007wr006142, 2008.
Nguyen, V.-T.-V., Nguyen, T.-D., and Ashkar, F.: Regional frequency analysis of extreme rainfalls, Water Sci. Technol., 45, 75–81, 2002.
Olsson, J. and Burlando, P.: Reproduction of temporal scaling by a rectangular pulses rainfall model, Hydrol. Process., 16, 611–630, https://doi.org/10.1002/hyp.307, 2002.
Olsson, J., Berggren, K., Olofsson, M., and Viklander, M.: Applying climate model precipitation scenarios for urban hydrological assessment: a case study in Kalmar City, Sweden, Atmos. Res., 92, 364–375, https://doi.org/10.1016/j.atmosres.2009.01.015, 2009.
Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U., and Tompkins, A.: The atmospheric general circulation model ECHAM5: Model description, Max Planck Institute for Meteorology Rep. 349, Max Planck Institute for Meteorology, Hamburg, Germany, 140 pp. 2003.
Rodriguez-Iturbe, I., Cox, D. R., and Isham, V.: Some models for rainfall based on stochastic point processes, P. Roy. Soc. Lond. A, 410, 269–288, https://doi.org/10.1098/rspa.1987.0039, 1987a.
Rodriguez-Iturbe, I., Febres de Power, B., and Valdes, J. B.: Rectangular pulses point process models for rainfall: analysis of empirical data, J. Geophys. Res., 92, 9645–9656, https://doi.org/10.1029/JD092iD08p09645, 1987b.
Scharling, M.: klimagrid Danmark nedbør 10 ∗ 10 km (ver. 2) – metodebeskrivelse, Danish Meteorological Institute Technical report no. 99-15, Danish Meteorological Institute, Copenhagen, Denmark, 18 pp., 1999.
Scharling, M.: Climate Grid Denmark, Danish Meteorological Institute Technical report no. 12-10, Danish Meteorological Institute, Copenhagen, Denmark, 12 pp., 2012.
Schilling, W.: Rainfall data for urban hydrology: what do we need?, Atmos. Res., 27, 5–22, https://doi.org/10.1016/0169-8095(91)90003-F, 1991.
Skamarock, W., Klemp, J., Dudhia, J., Gill, D., and Barker, D.: A description of the Advanced Research WRF version 3, NCAR Tech. Note NCAR/TN-475+STR, NCAR, Boulder, Colorado, USA, 125 pp., 2005.
Sunyer, M. A., Madsen, H., and Ang, P. H.: A comparison of different regional climate models and statistical downscaling methods for extreme rainfall estimation under climate change, Atmos. Res., 103, 129–128, https://doi.org/10.1016/j.atmosres.2011.06.011, 2012.
Sunyer, M. A., Sørup, H. J. D., Madsen, H., Rosbjerg, D., Christensen, O. B., Mikkelsen, P. S., and Arnbjerg-Nielsen K.: On the importance of observational data properties when assessing regional climate model performance of extreme precipitation, Hydrol. Earth Syst. Sci., 17, 4323–4337, https://doi.org/10.5194/hess-17-4323-2013, 2013.
Sunyer, M. A., Gregersen, I. B., Rosbjerg, D., Madsen, H., Luchner, J., and Arnbjerg-Nielsen, K.: Comparison of different statistical downscaling methods to estimate changes in hourly extreme precipitation using RCM projections from ENSEMBLES, Int. J. Climatol., 35, 2528–2539, https://doi.org/10.1002/joc.4138, 2014a.
Sunyer, M. A., Madsen, H., Rosbjerg, D., and Arnbjerg-Nielsen, K.: A Bayesian Approach for Uncertainty Quantification of Extreme Precipitation Projections Including Climate Model Interdependency and Non-Stationary Bias, J. Climate, 27, 7113–7132, https://doi.org/10.1175/JCLI-D-13-00589.1, 2014b.
Tebaldi, C., and Knutti, R.: The use of the multi-model ensemble in probabilistic climate projections, Philos. T. Ser. A, 365, 2053–2075, https://doi.org/10.1098/rsta.2007.2076, 2007.
van der Linden, P. and Mitchell, J. F. B. (Eds.): ENSEMBLES: Climate Change and its Impacts: Summary of research and results from the ENSEMBLES project, Met Office Hadley Center, Exeter, 164 pp., 2009.
van Vuuren, D. P., Edmonton, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T., Meinshausen, M., Nakocenovic, N., Smith, S. J., and Rose, S. K.: The representative concentration pathways: an overview, Climatic Change, 109, 5–31, https://doi.org/10.1007/s10584-011-0148-z, 2011.
Verhoest, N. E. C., Vandenberghe, S., Cabus, P., Onof, C., Meca-Figueras, T., and Jameleddine, S.: Are Stochastic point rainfall models able to preserve extreme flood statistics?, Hydrol. Process., 24, 3439–3445, https://doi.org/10.1002/hyp.7867, 2010.
Vrac, M., Stein, M., and Hayhoe, K.: Statistical downscaling of precipitation through nonhomogeneous stochastic weather typing, Clim. Res., 34, 169–184, https://doi.org/10.3354/cr00696, 2007.
Waymire, E. and Gupta, V. K.: The mathematical structure of rainfall representations. I. A review of the stochastic rainfall models, Water Resour. Res., 17, 1261–1272, https://doi.org/10.1029/WR017i005p01261, 1981.
Wilks, D. S.: Statistical methods in the atmospheric sciences, 3rd Edn., Academic Press, San Diego, CA, 704 pp., 2011.
Wilks, D. S. and Wilby, R. L.: The Weather generator game: a review of stochastic weather models, Prog. Phys. Geogr., 23, 329–357, https://doi.org/10.1177/030913339902300302, 1999.
Willems, P., Arnbjerg-Nielsen, K., Olsson, J., and Nguyen, V.-T.-V.: Climate change impact assessment on urban rainfall extremes and urban drainage: methods and shortcomings, Atmos. Res., 103, 106–118, https://doi.org/10.1016/j.atmosres.2011.04.003, 2012.
Wood, A. W., Leung, L. R., Sridhar, V., and Lettenmaier, D. P.: Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs, Climatic Change, 62, 189–216, https://doi.org/10.1023/B:CLIM.0000013685.99609.9e, 2004.
Short summary
Fine-resolution spatio-temporal precipitation data are important as input to urban hydrological models to assess performance issues under all possible conditions. In the present study synthetic data at very fine spatial and temporal resolution are generated using a stochastic model. Data are generated for both present and future climate conditions. The results show that it is possible to generate spatially distributed data at resolutions relevant for urban hydrology.
Fine-resolution spatio-temporal precipitation data are important as input to urban hydrological...
