EGU2020-7763
https://doi.org/10.5194/egusphere-egu2020-7763
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Multi-decadal variability in long-range ENSO predictions (SEAS5-20C)

Antje Weisheimer1,2, Magdalena Balmaseda1, and Tim Stockdale1
Antje Weisheimer et al.
  • 1European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, United Kingdom of Great Britain and Northern Ireland (antje.weisheimer@ecmwf.int)
  • 2University of Oxford, Department of Physics, AOPP, NCAS, Oxford, United Kingdom of Great Britain and Northern Ireland (antje.weisheimer@physics.ox.ac.uk)

Motivated by the high skill in predicting ENSO on seasonal time scales with ECMWF’s seasonal forecasting system SEAS5 and by previous findings of multi-decadal variability in seasonal forecast skill of extratropical dynamics, we have carried out an extensive set of 24-month long coupled hindcasts from 1901 to 2010. The hindcasts were run with SEAS5 in reduced resolution and are initialised from, and verified against, reanalyses of the 20thCentury. They allow us to analyse ENSO forecast skill beyond the first year, to study how skill varies on decadal time scales and to test sensitivities to atmospheric wind forcings and the assimilation of ocean observations in the initial conditions.

First results show a substantial amount of multi-decadal variability in both ENSO mean state and forecast skill. We find periods in the early-to-mid 20thCentury with much reduced levels of skill, in particular after the spring barrier in the first forecast year. Periods at the beginning and at the end of the Century show broadly similar good performances with substantial skill even after the first year spring barrier. Combined effects of the wind forcing and the assimilation of ocean data on the initial state seem to play a crucial role in understanding this behaviour.

How to cite: Weisheimer, A., Balmaseda, M., and Stockdale, T.: Multi-decadal variability in long-range ENSO predictions (SEAS5-20C), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7763, https://doi.org/10.5194/egusphere-egu2020-7763, 2020

This abstract will not be presented.