Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator

Abstract. Spatio-temporal precipitation is modelled for urban application at 1 h temporal resolution on a 2 km grid using a spatio-temporal Neyman–Scott rectangular pulses weather generator (WG). Precipitation time series used as input to the WG are obtained from a network of 60 tipping-bucket rain gauges irregularly placed in a 40 km  ×  60 km model domain. The WG simulates precipitation time series that are comparable to the observations with respect to extreme precipitation statistics. The WG is used for downscaling climate change signals from regional climate models (RCMs) with spatial resolutions of 25 and 8 km, respectively. Six different RCM simulation pairs are used to perturb the WG with climate change signals resulting in six very different perturbation schemes. All perturbed WGs result in more extreme precipitation at the sub-daily to multi-daily level and these extremes exhibit a much more realistic spatial pattern than what is observed in RCM precipitation output. The WG seems to correlate increased extreme intensities with an increased spatial extent of the extremes meaning that the climate-change-perturbed extremes have a larger spatial extent than those of the present climate. Overall, the WG produces robust results and is seen as a reliable procedure for downscaling RCM precipitation output for use in urban hydrology.

[1]  Valerie Isham,et al.  Some models for rainfall based on stochastic point processes , 1987, Proceedings of the Royal Society of London. A. Mathematical and Physical Sciences.

[2]  Variability in the scale properties of high‐resolution precipitation data in the Alpine climate of Switzerland , 2008 .

[3]  Hayley J. Fowler,et al.  Downscaling transient climate change using a Neyman- Scott Rectangular Pulses stochastic rainfall model , 2010 .

[4]  J. Olsson,et al.  Applying climate model precipitation scenarios for urban hydrological assessment: a case study in Kalmar City, Sweden. , 2009 .

[5]  Peter Steen Mikkelsen,et al.  On the importance of observational data properties when assessing regional climate model performance of extreme precipitation , 2013 .

[6]  J. Christensen,et al.  A summary of the PRUDENCE model projections of changes in European climate by the end of this century , 2007 .

[7]  K Arnbjerg-Nielsen,et al.  Impacts of climate change on rainfall extremes and urban drainage systems: a review. , 2013, Water science and technology : a journal of the International Association on Water Pollution Research.

[8]  D. Wilks,et al.  The weather generation game: a review of stochastic weather models , 1999 .

[9]  Paul S. P. Cowpertwait,et al.  Regionalised spatiotemporal rainfall and temperature models for flood studies in the Basque Country, Spain , 2013 .

[10]  H. Fowler,et al.  A stochastic model for the spatial‐temporal simulation of nonhomogeneous rainfall occurrence and amounts , 2010 .

[11]  Peter Steen Mikkelsen,et al.  Quality control of rain data used for urban runoff systems , 1997 .

[12]  A. Thomson,et al.  The representative concentration pathways: an overview , 2011 .

[13]  V. Gupta,et al.  The mathematical structure of rainfall representations: 1. A review of the stochastic rainfall models , 1981 .

[14]  Klaus Wyser,et al.  EC-Earth V2.2: description and validation of a new seamless earth system prediction model , 2012, Climate Dynamics.

[15]  S. Sobolowski,et al.  Background information on the RiskChange simulations by BCCR and DMI , 2014 .

[16]  H. Madsen,et al.  Assessing future climatic changes of rainfall extremes at small spatio-temporal scales , 2013, Climatic Change.

[17]  Wolfgang Schilling,et al.  Rainfall data for urban hydrology: what do we need? , 1991 .

[18]  Jonas Olsson,et al.  Reproduction of temporal scaling by a rectangular pulses rainfall model , 2002 .

[19]  Paul S. P. Cowpertwait,et al.  A Poisson-cluster model of rainfall: some high-order moments and extreme values , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[20]  W. Briggs.  Statistical Methods in the Atmospheric Sciences , 2007 .

[21]  G. Powers,et al.  A Description of the Advanced Research WRF Version 3 , 2008 .

[22]  K. Hennessy,et al.  Potential impacts of global warming on the frequency and magnitude of heavy precipitation , 1995 .

[23]  P. S. Mikkelsen,et al.  Potential future increase in extreme one-hour precipitation events over Europe due to climate change. , 2009, Water science and technology : a journal of the International Association on Water Pollution Research.

[24]  J. Olsson,et al.  Climate change impact assessment on urban rainfall extremes and urban drainage: Methods and shortcomings , 2012 .

[25]  P. Linden,et al.  ENSEMBLES: Climate Change and its Impacts - Summary of research and results from the ENSEMBLES project , 2009 .

[26]  H. Madsen,et al.  Properties of extreme point rainfall III: Identification of spatial inter-site correlation structure , 1996 .

[27]  H. Madsen,et al.  Regional estimation of rainfall intensity‐duration‐frequency curves using generalized least squares regression of partial duration series statistics , 2002 .

[28]  D. Maraun,et al.  Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user , 2010 .

[29]  Ronny Berndtsson,et al.  Spatial and temporal scales in rainfall analysis ― some aspects and future perspectives , 1988 .

[30]  H. Fowler,et al.  Heavier summer downpours with climate change revealed by weather forecast resolution model , 2014 .

[31]  D. Lettenmaier,et al.  Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs , 2004 .

[32]  Robert Leconte,et al.  A daily stochastic weather generator for preserving low-frequency of climate variability , 2010 .

[33]  A. Kirkevåg,et al.  The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate , 2013 .

[34]  Hayley J. Fowler,et al.  Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling , 2007 .

[35]  Henrik Madsen,et al.  Comparison of different statistical downscaling methods to estimate changes in hourly extreme precipitation using RCM projections from ENSEMBLES , 2015 .

[36]  K. Arnbjerg-Nielsen,et al.  Quantification of anticipated future changes in high resolution design rainfall for urban areas. , 2009 .

[37]  Hayley J. Fowler,et al.  RainSim: A spatial-temporal stochastic rainfall modelling system , 2008, Environ. Model. Softw..

[38]  B. Stevens,et al.  The atmospheric general circulation model ECHAM6 - Model description , 2013 .

[39]  F. Ashkar,et al.  Regional frequency analysis of extreme rainfalls. , 2002, Water science and technology : a journal of the International Association on Water Pollution Research.

[40]  Katharine Hayhoe,et al.  Statistical downscaling of precipitation through nonhomogeneous stochastic weather typing , 2007 .

[41]  Niko E. C. Verhoest,et al.  Are stochastic point rainfall models able to preserve extreme flood statistics? , 2010 .

[42]  Henrik Madsen,et al.  A Bayesian Approach for Uncertainty Quantification of Extreme Precipitation Projections Including Climate Model Interdependency and Nonstationary Bias , 2014 .

[43]  Andreas Schumann,et al.  Modeling of daily precipitation at multiple locations using a mixture of distributions to characterize the extremes , 2009 .

[44]  P. H. Ang,et al.  A comparison of different regional climate models and statistical downscaling methods for extreme rainfall estimation under climate change , 2012 .

[45]  H. Madsen,et al.  A rationale for using local and regional point rainfall data for design and analysis of urban storm drainage systems , 1998 .

[46]  Juan B. Valdés,et al.  Rectangular pulses point process models for rainfall: Analysis of empirical data , 1987 .

[47]  Paul S. P. Cowpertwait,et al.  A spatial–temporal point process model of rainfall for the Thames catchment, UK , 2006 .

[48]  H. Madsen,et al.  Update of regional intensity-duration-frequency curves in Denmark: tendency towards increased storm intensities. , 2009 .

[49]  Richard W. Katz,et al.  Improving the simulation of extreme precipitation events by stochastic weather generators , 2008 .

[50]  E. van Meijgaard,et al.  The KNMI regional atmospheric climate model RACMO version 2.1 , 2008 .

[51]  Reto Knutti,et al.  The use of the multi-model ensemble in probabilistic climate projections , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[52]  S. Sobolowski,et al.  Identifying added value in high-resolution climate simulations over Scandinavia , 2015 .

[53]  P. E. O'connell,et al.  A Regionalised Neyman-Scott Model of Rainfall with Convective and Stratiform Cells , 1997 .