Wilby, R. L. and Dawson, C. W. and Yu, D. and Herring, Z. and Baruch, A. and Ascott, M. J. and Finney, D. L. and Macdonald, D. M. J. and Marsham, J. H. and Matthews, T. and Murphy, C. (2023) Spatial and temporal scaling of sub-daily extreme rainfall for data sparse places. Climate Dynamics, 60 (11-12). pp. 3577-3596. ISSN 0930-7575

Preview

Download (4MB) | Preview

Abstract

Global efforts to upgrade water, drainage, and sanitation services are hampered by hydrometeorological data-scarcity plus uncertainty about climate change. Intensity–duration–frequency (IDF) tables are used routinely to design water infrastructure so offer an entry point for adapting engineering standards. This paper begins with a novel procedure for guiding downscaling predictor variable selection for heavy rainfall simulation using media reports of pluvial flooding. We then present a three step workflow to: (1) spatially downscale daily rainfall from grid-to-point resolutions; (2) temporally scale from daily series to sub-daily extreme rainfalls and; (3) test methods of temporal scaling of extreme rainfalls within Regional Climate Model (RCM) simulations under changed climate conditions. Critically, we compare the methods of moments and of parameters for temporal scaling annual maximum series of daily rainfall into sub-daily extreme rainfalls, whilst accounting for rainfall intermittency. The methods are applied to Kampala, Uganda and Kisumu, Kenya using the Statistical Downscaling Model (SDSM), two RCM simulations covering East Africa (CP4 and P25), and in hybrid form (RCM-SDSM). We demonstrate that Gumbel parameters (and IDF tables) can be reliably scaled to durations of 3 h within observations and RCMs. Our hybrid RCM-SDSM scaling reduces errors in IDF estimates for the present climate when compared with direct RCM output. Credible parameter scaling relationships are also found within RCM simulations under changed climate conditions. We then discuss the practical aspects of applying such workflows to other city-regions

Item Type:	Article
Additional Information:	This research was funded by the UK Department for International Development (DFID) / Natural Environment Research Council (NERC) Future Climate for Africa (FCFA) HyCRISTAL project (NE/ M020371/1, NE/M020452/1). Finney was supported by the Natural Environment Research Council/Department for International Development (NERC/DFID, NE/M02038X/1) via the Future Climate for Africa (FCFA) funded project, Integrating Hydro-Climate Science into Policy Decisions for Climate-Resilient Infrastructure and Livelihoods in East Africa (HyCRISTAL). Ascott and Macdonald publish with permission of the Executive Director, British Geological Survey (UK Research and Innovation). Cite as: Wilby, R.L., Dawson, C.W., Yu, D. et al. Spatial and temporal scaling of sub-daily extreme rainfall for data sparse places. Clim Dyn 60, 3577–3596 (2023). https://doi.org/10.1007/s00382-022-06528-2
Keywords:	regional climate downscaling; extreme rainfall; intensity-duration-frequency; Tropics; flood;
Academic Unit:	Faculty of Social Sciences > Geography Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
Item ID:	17739
Identification Number:	https://doi.org/10.1007/s00382-022-06528-2
Depositing User:	Conor Murphy
Date Deposited:	26 Oct 2023 11:29
Journal or Publication Title:	Climate Dynamics
Publisher:	Springer
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads