s41612-020-00149-4.pdf (4.16 MB)
Using UNSEEN trends to detect decadal changes in 100-year precipitation extremes
journal contribution
posted on 2020-12-03, 15:52 authored by Timo Kelder, M. Müller, L.J. Slater, Tim MarjoribanksTim Marjoribanks, Robert WilbyRobert Wilby, C. Prudhomme, P. Bohlinger, L. Ferranti, T. NipenSample sizes of observed climate extremes are typically too small to reliably constrain return period estimates when there is non-stationary behaviour. To increase the historical record 100-fold, we apply the UNprecedented Simulated Extreme ENsemble (UNSEEN) approach, by pooling ensemble members and lead times from the ECMWF seasonal prediction system SEAS5. We fit the GEV distribution to the UNSEEN ensemble with a time covariate to facilitate detection of changes in 100-year precipitation values over a period of 35 years (1981–2015). Applying UNSEEN trends to 3-day precipitation extremes over Western Norway substantially reduces uncertainties compared to estimates based on the observed record and returns no significant linear trend over time. For Svalbard, UNSEEN trends suggests there is a significant rise in precipitation extremes, such that the 100-year event estimated in 1981 occurs with a return period of around 40 years in 2015. We propose a suite of methods to evaluate UNSEEN and highlight paths for further developing UNSEEN trends to investigate non-stationarities in climate extremes.
Funding
Norwegian Meteorological Institute
Loughborough University
TWEX project (grant 255037)
History
School
- Social Sciences and Humanities
Department
- Geography and Environment
Published in
npj Climate and Atmospheric ScienceVolume
3Publisher
Springer NatureVersion
- VoR (Version of Record)
Rights holder
© The AuthorsPublisher statement
This is an Open Access Article. It is published by Springer under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/Acceptance date
2020-10-12Publication date
2020-11-27Copyright date
2020ISSN
2397-3722eISSN
2397-3722Publisher version
Language
- en
Depositor
Prof Robert Leonard Wilby. Deposit date: 24 October 2020Article number
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