Yes, at WTN we do both.

 

While exposure is sector-agnostic, vulnerability depends on the type of asset, the economic activity of the company, and many other factors.

 

For example, the same heat wave will affect a livestock farm differently than an automotive manufacturing facility. We therefore calibrate vulnerability by asset class and use case, combining sector benchmarks with site-specific information when available.

 

An example of the underlying climate data useful for the vulnerability assessment and impact modeling is shown here in this Figure.

 

This graph illustrates the time series (upper plot) of Heat Waves and the corresponding probability assessment (bottom plot) for the same critical threshold. It's asset-level risk assessment for 42.92 N and 12.55 E, covering both, historical period and forward-looking scenario analysis for three scenarios. This example reflects one climate model: CNRM-CM6-1-HR.

 

 

Figure: The upper graph shows the time series of heatwaves, defined by the 3-day average of daily maximum temperature. Black and grey lines represent historical data. The dashed black line shows observations, and the solid line shows the historical climate model simulation. These two time series are not supposed to match! Three colored lines represent forward-looking scenarios: SSP1-2.6 (orderly), SSP2-4.5, and SSP5-8.5.

 

The lower graph on this Figure  shows the annual probability of an extreme event (39.7 °C). This critical threshold is calculated for this specific location from historical observations for the reference period 1980 - 2020. While in the past such an anomaly occurred roughly once every 11 years, by 2050 the same heatwave is projected to occur every other year under SSP5-8.5.

 

The climate model data reconstructs annual temperature anomalies at this selected location for the period 1950 - 2100 (see Figure). Both observations and the climate model indicate an overall warming trend in the hottest 3-day episodes. While historical data show the 3-day average of the maximum daily temperature remaining below 39.4 °C, this threshold is projected to become the new ‘normal’ after 2040. These time series of heatwaves demonstrate a clear upward temperature shift between historical and future decades.

 

What does this time series tell us?

 

Suppose the loss is X $ per event exceeding the critical threshold. With this data, you can assess the number of such events and evaluate the expected loss decade by decade, both historically and forward-looking. The corresponding probability data is always linked to the predefined critical threshold. Certain use cases require this metric as an input parameter.

 

For the vulnerability assessment, the corresponding critical threshold can be defined by the WTN team or suggested by the client, asset by asset.  You can set a unique critical threshold for each location, or use the same one for all locations. For example, the thresholds for airport operations and for a farm will differ.