EGU21-12136, updated on 04 Mar 2021
https://doi.org/10.5194/egusphere-egu21-12136
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Seasonal predictions as a high-resolution large ensemble to study extreme events over recent decades

Timo Kelder1, Louise Slater2, Tim Marjoribanks3, Rob Wilby1, Christel Prudhomme4, and Julia Wagemann4
Timo Kelder et al.
  • 1Geography and Environment, Loughborough University, Loughborough, UK
  • 2School of Geography and the Environment, University of Oxford, Oxford, UK
  • 3School of Architecture, Building and Civil Engineering, Loughborough, UK
  • 4European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK

Large ensembles of climate model simulations may be used to assess the likelihood of extreme events, which only have a limited chance of occurring in observed records. In this talk, we discuss how the ECMWF seasonal prediction system SEAS5 can be used to generate a 100-member ensemble over 1981-present. SEAS5 is a global coupled ocean, sea-ice, atmosphere model with a horizontal resolution of 36 km. We introduce an open and reproducible workflow to retrieve Copernicus SEAS5 data and evaluate the ensemble member independence, model stability, and model fidelity. We illustrate how the increased sample size may help risk estimation, detecting trends in 100-year extremes as well as analysing drivers of extreme events that are difficult to discern from limited observational records.

How to cite: Kelder, T., Slater, L., Marjoribanks, T., Wilby, R., Prudhomme, C., and Wagemann, J.: Seasonal predictions as a high-resolution large ensemble to study extreme events over recent decades, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12136, https://doi.org/10.5194/egusphere-egu21-12136, 2021.

Corresponding presentation materials formerly uploaded have been withdrawn.