B1662
Title: The effect of a short observational record on the statistics of temperature extremes
Authors: Olivier Pasche - University of Geneva (Switzerland) [presenting]
Joel Zeder - ETH Zurich (Switzerland)
Sebastian Sippel - ETH Zurich (Switzerland)
Sebastian Engelke - University of Geneva (Switzerland)
Erich Fischer - ETH Zurich (Switzerland)
Abstract: In June 2021, the Pacific Northwest experienced a record-breaking heatwave event. Return levels estimated based on observations up to the year before the event suggested that reaching such high temperatures should not have been possible in the current climate. The suitability of the prevalent statistical approach is assessed by analyzing extreme temperature events in climate model large ensemble and synthetic extreme value data. It is demonstrated that the method is subject to biases, as high return levels are generally underestimated and, correspondingly, the return period of rare heatwave events is overestimated, especially if the underlying extreme value distribution is derived from a short historical record or in a changing climate. Furthermore, analyses triggered by an extreme event suffer from additional selection bias introduced by the implicit stopping rule. An alternative approach to non-stationary return level and endpoint uncertainty estimation is also discussed, using localized profile likelihood.
