Abstract

Wind speed extremes in the sub-Arctic realm of the North-East Pacific region were investigated through extreme value analysis of wind speed obtained from wind simulations of the COSMO-CLM (Consortium for Small-scale Modelling, climate version) mesoscale model, as well as using observed data. The analysis showed that the set of wind speed extremes obtained from observations is a mixture of two different subsets each neatly described by the Weibull distribution. Using special metaphoric terminology, they are labelled as “Black Swans” and “Dragons”. The “Dragons” are responsible for strongest extremes. It has been shown that both reanalysis and GCM (general circulation model) data have no “Dragons”. This means that such models underestimate wind speed maxima, and the important circulation process generating the anomalies is not simulated. The COSMO-CLM data have both “Black Swans” and “Dragons”. This evidence provides a clue that an atmospheric model with a detailed spatial resolution (we used in this work the data from domain with 13.2 km spatial resolution) does reproduce the special mechanism responsible for the generation of the largest wind speed extremes. However, a more thorough analysis shows that the differences in the parameters of the cumulative distribution functions are still significant. The ratio between the modelled Dragons and Black Swans can reach up to only 10%. It is much less than 30%, which was the level established for observations.

Highlights

  • This paper focuses on extreme wind events

  • The analysis showed that the set of wind speed extremes obtained from observations is a mixture of two different subsets each neatly described by the Weibull distribution

  • The COSMO-CLM data have both “Black Swans” and “Dragons”. This evidence provides a clue that an atmospheric model with a detailed spatial resolution does reproduce the special mechanism responsible for the generation of the largest wind speed extremes

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Summary

Introduction

We analysed wind velocity archives obtained from a 30-year simulation of the COSMO-CLM model over the North-East Pacific Ocean region [11]. 3. Comparison of Modelled Near-Surface Wind Velocities for Different Grid Spacing and Observations. The COSMO-CLM model reproduces the spatial distribution, seasonal and synoptic variability of temperature and wind velocity adequately. The comparison of different spatial resolutions shows that there is greater agreement for data that adhere to the domain with 6.6-km grid spacing This advantage is insignificant and does not matter in practice. Increasing the horizontal resolution from 13.2 km to 6.6 km gives practically the same results, as well as for extremes Considering this conclusion, we will use the data from the domain with 13.2 km spacing in the further analysis. We use this data because they occupy a smaller volume and it is much easier to work with them

The Weibull Distributions in Station Observation Data
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