Last modified on Nov 06, 2023 16:49

Contributors: Kevin Hodges (University of Reading)

Issued by: Kevin Hodges (University of Reading)

Issued Date: 09/06/2021

Ref:  C3S_435_LOT3_KNMI_2020 – Tier1 Indicators

Official refence number service contract: 2020/C3S_435_Lot3_KNMI

Acronyms

1. Introduction

European winter windstorms are a major cause of losses to the insurance sector. To help the sector better understand this risk the Operational Windstorm Service for the Insurance Sector has been developed. The development of the service follows from a Proof of Concept for a Sectorial Information Service to provide information about European windstorms, which is the Windstorm Information Service (WISC), part of the Copernicus Climate Change Service (C3S). This document describes the Tier 1 indicators and how they are produced by the University of Reading. The Tier 1 indicators provide summary statistics for wind storm activity per year and per European country.

1.1. Executive Summary

The summary Tier 1 indicators, available from the Climate Data Store (CDS), are derived from ERA5 reanalysis data for the period 1979 to 2021 using the following methodology. Extratropical cyclones are first identified and tracked in the ERA5 reanalysis data for the October to March periods of 1979- 2021 using an automated cyclone tracking algorithm based on the method described by Roberts et al, (2014) and described in the Product User Guide for the Operational Storm Tracks. The Tier 1 indicators use the cyclone tracks and ERA5 maximum land 10m winds to produce summary statistics of the Storm Severity Index (SSI) by country.

1.2. Scope of Documentation

This document describes the C3S Tier 1 dataset using the standard C3S format for product descriptions, i.e., in terms of product target requirements, product overview, input data and methodology as well as use of the dataset. It is the primary document for users.

1.3. Version History

Version 1.0. The underlying methodology used to derive the Tier 1 indicators has been consistent within this project and the previous project, WISC. The earlier WISC Tier 1 indicators were derived from ERA-Interim and ERA-20C since these were produced before ERA5 became available.

2. Product Description

2.1. Product Target Requirements

The storm tracks were sourced from the ERA5 reanalysis with storms identified using an automated cyclone-tracking algorithm applied to the 850hPa relative vorticity, based on (Hodges, 1995, 1999), i.e., the same approach as used in the eXtreme WindStorms (XWS; Roberts et al, 2014) and C3S Windstorm Information Service Copernicus (WISC) activity. This used the 3-hourly analyses from ERA5 as opposed to the mixture of analyses and forecasts from ERA-Interim to allow 3 hourly data as used in XWS and WISC. The vorticity threshold used for the extended winter storm tracks was 1x10-5s-1 and tracks were required to exist for at least 1 day and to have travelled at least 1,000km. This provided tracks of the 3-hourly locations of the following six variables, the last 5 at full resolution, for each storm:

• maximum T42 (corresponding to about 310 km model grid size) 850 hPa relative vorticity
• minimum Mean Sea Level Pressure (MSLP) within 5° of vorticity centre
• maximum 925 hPa wind speed within 6° of vorticity centre
• maximum 10m wind speed within 6° of vorticity centre
• maximum 925 hPa wind speed over land within 3° of vorticity centre
• maximum 10m wind speed over land within 3° of vorticity centre

The spatial range requirement for the tracks is Pan-European covering an area defined by 15W to 25E, 35N to 70N though the storms were tracked over their full lifecycle from formation over the Atlantic.

The indicators are calculated across a number of regions (shown in Figure 1) which include:

• Europe: All land areas from 15W-25E 35N-70N (as used in the XWS project; Roberts et al., (2014))
• The British Isles: Great Britain and Ireland
• Iberia: Spain, Portugal and Andorra
• France
• Germany
• BeNeLux: Belgium, Netherlands, Luxembourg
• BeNeLuxMark: Belgium, Netherlands, Luxembourg, Denmark
• Scandinavia: Norway, Sweden, Finland

Figure 1: Tier 1 indicator regions

A storm is said to pass through a region if the land only 10m wind speed maximum (within 3° of the vorticity center) passes through the region. A range of statistics are computed, including:

• the number of storms per year and per decade based on the vorticity and the wind maxima,
• mean of maximum 10m wind speed for maximum in region,
• number of extreme windstorms, per year and per decade for different thresholds of 15.6 m s^{- 1}, 20 m s^-1 and 25 m s^-1, and
• mean severity of storms, per year and per decade.

The choice of the thresholds is based on the work done for WISC. The Storm Severity Index is defined as:

Where A is the area over land in km² and 𝑢_10𝑚 is 10m wind speed from the reanalysis data. This is equivalent to the SSI used in Dawkins et al., (2016).

2.2. Product Overview

Tier 1 indicators are computed per Oct-Mar season and then converted to decadal averages for the final product.

2.2.1. Data Description

Table 1: Overview of key characteristics of the Tier 1 indicator dataset.

2.2.2. Variable Description

The Tier 1 indicators, which are provided in Excel format, include the following fields:

• Number of windstorms per year and per decade (vorticity)
• Number of windstorms per year and per decade (wind)
• Mean maximum 10m wind speed for maximum in region, 0 m s^-1 threshold
• Number of extreme windstorms, per year and per decade, 15.6 m s^-1 threshold
• Mean maximum wind speed greater than 15.6 m s^-1 threshold, per year and per decade
• Number of extreme windstorms, per year and per decade, 20 m s^-1 threshold
• Mean maximum wind speed greater than 20 m s^-1 threshold, per year and per decade
• Number of extreme windstorms, per year and per decade, 25 m s^-1 threshold
• Mean maximum wind speed greater than 25 m s^-1 threshold, per year and per decade
• Mean severity of extreme windstorms, per year and per decade, 15.6 m s^-1 threshold
• Mean severity of extreme windstorms, per year and per decade, 20.0 m s^-1 threshold
• Mean severity of extreme windstorms, per year and per decade, 25.0 m s^-1 threshold

Table 2: Overview and description of variables

2.3. Input Data

The input data to the cyclone track and Tier 1 production is summarised in Table 3 and described below.

Table 3: Overview of climate model data for input to Operational Storm Track, summarizing the model properties and available scenario simulations.

2.3.1. Input Data 1

ERA5 Reanalysis
Data from the ECMWF ERA5 reanalysis (Hersbach et al, 2020) extracted directly from the mars archive for the period 1979-2020 at 3 hourly intervals for the seasonal period of October to March when the majority of European windstorms occur. The 850hPa relative vorticity is spectrally filtered prior to applying the tracking algorithm. Full resolution MSLP, 925hPa winds and 10m winds are also added to the cyclone tracks.

2.4. Method

2.4.1. Background

The same tracking methodology has been applied to the ECMWF ERA5 data set as was used with ERA- Interim (Dee et al, 2011) in the Windstorm Information Service Copernicus (WISC¹) and eXtreme Wind Storms' (XWS²) catalogue (Roberts et al, 2014) projects. However, since ERA5 has 3-hourly analyses there is no need to use the forecast splicing to get 3-hourly data as was used for WISC and XWS. The ERA5 3 hourly analysis fields are used to be consistent with WISC and XWS. The Tier 1 indicators make use of the cyclone tracks and ERA5 10m wind speeds.

2.4.2. Model / Algorithm

The cyclone tracking and cyclone track data is described in the Operational Storm Track product user guide.

Number of storms

This indicator is calculated based on the extended winter storm tracks described in the Operational Storm Track product user guide. A storm is said to pass through a region if the location of the storm tracked vorticity center or the associated land-only 3-hourly 10m wind speed intersects that region (defined as a GIS polygon as shown in Figure 1; downloaded from Natural Earth http://www.naturalearthdata.com/tag/countries/).

Total number of extreme storms

This indicator is calculated similarly to the total number of storms; however, the track must also have an associated 3-hourly land only 10m wind speed over the region which is greater than a threshold. In the insurance industry, a common threshold over which 10m wind speeds may start to cause loss or damage is 25ms^-1. Damage caused by wind speeds exceeding this threshold is generally due to wind gusts. Here three thresholds are considered 15.6 m s^-1, 20 m s^-1 and 25 m s^-1. The 15.6 m s^-1 threshold was chosen as this was also used in WISC.

Mean maximum wind speed greater than a threshold

This is calculated by applying a regional mask and then a wind speed threshold mask to the ERA5 10m winds. For the resulting wind speeds the maximum is taken and average per season computed. This gives an indication of the highest land-only 10m wind speed which could be experienced in a country.

Storm Severity Index

Storm Severity Index (SSI) is defined as:

Where A is the area over land in km² and 𝑢_10𝑚 is 10m wind speed calculated from the re-analysis data. This is equivalent to a definition of SSI used in Dawkins et al., (2016), with the only difference being the threshold of 10m wind speed used. This metric is also calculated from the land masked, and the ERA5 masked wind speeds.

2.4.3. Validation

As with the cyclone tracks there is effectively no "truth" to contrast with, so the comparison is made with the Tier1 data produced for WISC using ERA-Interim to gauge the differences between the two data sets. The same procedures as used in WISC have been used to compute the Tier 1 indicators for ERA5 based on the 10m wind intensity over land. The indicators include values for the number of storms passing through a European country, the number of extreme storms defined by three threshold values (15.6 m s^-1 as used in WISC and 20 and 25 m s^-1), the mean wind intensity for the extreme storms and the Storm Severity Indexes (SSI). Some significant differences have been found between the ERA5 and ERA-Interim Tier 1 data which is the result of the differences in the location of the wind maxima, the intensity of the 10m winds and possibly the use of different land-sea masks, the latter two being related to the differences in resolution of the two reanalysis data sets.

3. Concluding Remarks

The operational storm tracks are derived from ERA5 reanalysis data for the period 1979 to 2021 using the following methodology. Extratropical cyclones are identified and tracked in the ERA5 reanalysis data for the October to March periods of 1979-2021 using an automated cyclone tracking algorithm based on the method described by Hodges (1995, 1999) and previously used for WISC and XWS (Roberts et al, 2014). The storm tracks were used as the basis for the statistical downscaling of storm footprints. The Tier 1 indicators are computed from the cyclone tracks and the ERA5 10m wind speeds and provide a set of summary statistics presented as decadal averages.

References

Dawkins L. C., Stephenson, D. B., Lockwood, J. F. and Maisey P. E. (2016) The 21st century decline in damaging European windstorms, Natural Hazards and Earth System Science, 16, 1999-2007, doi:10.5194/nhess-16-1999-2016.

Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A.J., Haimberger, L., Healy, S.B., Hersbach, H., Hólm, E.V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A.P., Monge-Sanz, B.M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553-597.

Hersbach, H, Bell, B, Berrisford, P, et al. The ERA5 global reanalysis. Q J R Meteorol Soc. 2020; 146: 1999– 2049.

Hodges, K. I. (1995) Feature tracking on the unit-sphere. Monthly Weather Review, 123 (12): 3458- 3465. doi:10.1175/1520-0493(1995)123;

Hodges, K.I. (1999) Adaptive Constraints for Feature Tracking, Mon. Weather Rev., V127, 1362-1373. Roberts, J. F., Champion, A. J., Dawkins, L. C., Hodges, K. I., Shaffrey, L. C., Stephenson, D. B., Stringer,

M. A., Thornton, H. E., and Youngman, B. D. (2014) The XWS open access catalogue of extreme European windstorms from 1979 to 2012, Nat. Hazards Earth Syst. Sci., 14, 2487-2501

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