Using UNSEEN trends to detect decadal changes in 100-year precipitation extremes

Kelder, T.; Müller, M.; Slater, L.J.; Marjoribanks, T.I.; Wilby, R.L.; Prudhomme, C.; Bohlinger, P.; Ferranti, L.; Nipen, T.. 2020 Using UNSEEN trends to detect decadal changes in 100-year precipitation extremes. npj Climate and Atmospheric Science, 3, 47.

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Sample 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.

Item Type: Publication - Article
Digital Object Identifier (DOI):
UKCEH and CEH Sections/Science Areas: UKCEH Fellows
ISSN: 2397-3722
Additional Information. Not used in RCUK Gateway to Research.: Open Access paper - full text available via Official URL link.
Additional Keywords: atmospheric science, climate change, environmental impact, hydrology
NORA Subject Terms: Hydrology
Meteorology and Climatology
Atmospheric Sciences
Date made live: 17 Dec 2020 11:29 +0 (UTC)

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