Preprints
https://doi.org/10.5194/hess-2021-381
https://doi.org/10.5194/hess-2021-381

  17 Aug 2021

17 Aug 2021

Review status: a revised version of this preprint is currently under review for the journal HESS.

Temporal downscaling of precipitation time-series projections to forecast green roofs future detention performance

Vincent Pons1,2, Rasmus Benestad3, Edvard Sivertsen4, Tone Merete Muthanna1, and Jean-Luc Bertrand-Krajewski2 Vincent Pons et al.
  • 1Department of Civil and Environmental Engineering, The Norwegian University of Science and Technology, Trondheim, 7031, Norway
  • 2Univ Lyon, INSA Lyon, DEEP, EA7429, 11 rue de la Physique, F-69621, Villeurbanne cedex, France
  • 3Norwegian Meteorological Institute, Oslo, Norway
  • 4SINTEF AS, S.P. Andersens veg 3, N-7465 Trondheim, Norway

Abstract. A strategy to simulate rainfall by the means of different Multiplicative random Cascades (MRC) was developed to evaluate their applicability to produce inputs for green roof infrastructures models taking into account climate change. The MRC reproduce a (multi)fractal distribution of precipitation through an iterative and multiplicative random process. The initial model was improved with a temperature dependency and an additional function to improve its capability to reproduce the temporal structure of rainfall. The structure of the models with depth and temperature dependency was found to be applicable in eight locations studied across Norway (N) and France (F). The resulting time-series from both reference period and projection based on RCP 8.5 were applied to two green roofs (GR) with different properties. The different models lead to a slight change in the performance of GR, but this was not significant compared to the range of outcomes due to ensemble uncertainty in climate modelling and the stochastic uncertainty due to nature of the process. The moderating effect of the green infrastructure was found to decrease in most of the Norwegian cities, especially Bergen (N), while increasing in Lyon (F).

Vincent Pons et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-381', Anonymous Referee #1, 13 Sep 2021
    • AC1: 'Reply on RC1', Vincent Pons, 13 Nov 2021
  • RC2: 'Comment on hess-2021-381', Anonymous Referee #2, 17 Sep 2021
    • AC2: 'Reply on RC2', Vincent Pons, 13 Nov 2021

Vincent Pons et al.

Vincent Pons et al.

Viewed

Total article views: 531 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
420 101 10 531 1 3
  • HTML: 420
  • PDF: 101
  • XML: 10
  • Total: 531
  • BibTeX: 1
  • EndNote: 3
Views and downloads (calculated since 17 Aug 2021)
Cumulative views and downloads (calculated since 17 Aug 2021)

Viewed (geographical distribution)

Total article views: 504 (including HTML, PDF, and XML) Thereof 504 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 02 Dec 2021
Download
Short summary
Different models to increase the temporal resolution of precipitation time-series to minute were developed. Their applicability under climate change and their suitability to produce input time-series for green infrastructure (e.g. green roofs) modelling were evaluated. The robustness of the model was validated against a range of European climates in 8 locations in France and Norway. The future hydrological performances of green roofs were finally evaluated in order to improve design practices.