Loss potentials based on an ensemble forecast: How likely are winter windstorm losses similar to 1990?

Abstract

In this paper we investigate the feasibility and added value of using the seasonal hindcasts of the ECMWF System 4 as a hazard event set for European winter windstorms damage calculations. The windstorms are identified for every ensemble member and every year by an objective windstorm tracking algorithm. The damages are calculated directly from the obtained wind footprints via the open source natural catastrophe damage model CLIMADA for Germany, the UK, France and Spain and compared to the loss from ERA‐Interim. The results show that the ensembles of losses in System 4 nicely capture the inter‐annual loss variability of the reanalysis. Due to more than 1,500 years of “virtual reality” windstorm data from the hindcasts, the return levels of extreme losses can be estimated fairly accurately. Based on System 4, the losses in the scale of 1990 (January, February, March and December including the prominent windstorm Daria) represent a 20‐year event in Germany whereas they represent a 100‐year event for the UK. Thus, a considerably shorter return period compared to return periods calculated from ERA‐Interim alone. Further we investigate the link between the annual losses and large‐scale drivers derived from mean‐sea‐level‐pressure (MSLP) data in System 4. We can show that within System 4 there is a significant link between increased loss potentials for strongly positive North Atlantic Oscillation (NAO) phases for Germany and the UK as well as a reduced loss potential for Spain. The link between the other analysed indices is weak bar the East Atlantic (EA) pattern index. Thus, if the NAO in System 4 is correct we can assume that the windstorms in System 4 are useable. If this premise is given our study shows that the loss estimates and ultimately the return levels of losses from System 4 can be used in an operational way.

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

“…Furthermore, the UNSEEN-BC ensemble shows that an event of 1.5 times the magnitude of the highest observed event could arise. This application of the UNSEEN approach is similar to previous research on the 2013/14 winter floods in the UK 15 and for the 1990 windstorm losses over Germany and the UK 21 . A difference to the previous studies is that we run the analysis on a 3-day resolution based on the latest ECMWF seasonal prediction system SEAS5, whereas monthly averages and other prediction systems were used elsewhere.…”

“…Our results for Western Norway highlight the strength of UNSEEN in evaluating design-levels and present-day climate hazards, backed by a growing body of literature [12][13][14][15][16][17][18][19][20][21][22] . For example, UNSEEN might be helpful in reviewing design standards used to rebuild infrastructure after the severe damage caused by the 2005 and 2014 flood episodes.…”

“…An emerging alternative to traditional observation-based extreme value and weather generator analyses is to pool ensemble members from numerical weather prediction systems [12][13][14][15][16][17][18][19][20][21][22] -the UNprecedented Simulated Extreme ENsemble (UNSEEN) approach 15,16 . This technique creates numerous alternative pathways of reality, thus increasing the event sample size for statistical analysis.…”

“…For example, the 2013/14 winter flooding in the UK had no observational precedent, but could have been anticipated with the UNSEEN approach 15 . Similarly, estimates of storm surge levels of the River Rhine 12,13 , global ocean wind and wave extremes [17][18][19] , and losses from extreme windstorms 21 have all been improved with the UNSEEN approach. UNSEEN can also enhance food security through better drought exposure estimates 14,22 and can assist policy makers and contingency planners by quantifying and explaining the most severe events possible in the current climate, such as heatwaves in China 16 .…”

“…Previous UNSEEN studies used the Hadley Centre global climate model, HadGEM3-GC2 [14][15][16]22 and the European Centre for Medium-range Weather Forecasts (ECMWF) ensemble prediction systems [17][18][19][20] and earlier versions of the seasonal prediction system 12,13,21 . Here, we are the first to use the latest ECMWF seasonal prediction system SEAS5 32 with an open access, highresolution, large ensemble, multidecadal, homogeneous hindcast period .…”