Preprints
https://doi.org/10.5194/egusphere-2022-288
https://doi.org/10.5194/egusphere-2022-288
 
16 May 2022
16 May 2022

Skillful Decadal Prediction of German Bight Storm Activity

Daniel Krieger1,2, Sebastian Brune3, Patrick Pieper4, Ralf Weisse1, and Johanna Baehr3 Daniel Krieger et al.
  • 1Institute of Coastal Systems – Analysis and Modeling, Helmholtz-Zentrum Hereon, Geesthacht, Germany
  • 2International Max Planck Research School on Earth System Modelling, Hamburg, Germany
  • 3Institute of Oceanography, Universität Hamburg, Hamburg, Germany
  • 4Institute of Meteorology, Freie Universität Berlin, Berlin, Germany

Abstract. We evaluate the prediction skill of the Max-Planck-Institute Earth System Model (MPI-ESM) decadal hindcast system for German Bight storm activity (GBSA) on a multiannual to decadal scale. We define GBSA every year via the most extreme three-hourly geostrophic wind speeds, which are derived from mean sea-level pressure (MSLP) data. Our 64-member ensemble of annually initialized hindcast simulations spans the time period 1960-2018. For this period, we compare deterministically and probabilistically predicted winter MSLP anomalies and annual GBSA with a lead time of up to ten years against observations. The model shows limited deterministic skill for single prediction years, but significant positive deterministic skill for long averaging periods. For probabilistic predictions of high and low storm activity, the model is skillful at both short and long averaging periods, and outperforms persistence-based predictions. For short lead years, the skill of the probabilistic prediction for high and low storm activity notably exceeds the deterministic skill. We therefore conclude that, for the German Bight, skillful decadal predictions of regional storm activity can be viable with a large ensemble and a carefully designed approach.

Daniel Krieger et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Review of egusphere-2022-288', Anonymous Referee #1, 23 May 2022
  • RC2: 'Comment on egusphere-2022-288', Anonymous Referee #2, 26 May 2022
  • RC3: 'Comment on egusphere-2022-288', Anonymous Referee #3, 17 Jun 2022

Daniel Krieger et al.

Daniel Krieger et al.

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Short summary
Accurate predictions of storm activity are desirable for coastal management. We investigate how well a climate model can predict storm activity in the German Bight 1–10 years in advance. We let the model predict the past, compare these predictions to observations, and analyze whether the model is doing better than simple statistical predictions. We find that the model generally shows good skill for extreme periods, but the prediction timeframes with good skill depend on the type of prediction.