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The Climate Change- Attributed Economic Cost of Extreme Weather
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<p>Climate change is changing the nature of extreme weather events across the globe. Extreme event attribution is used to quantify the extent to which anthropogenic climate change is responsible for the change in frequency or severity of a specific extreme weather event. Using this quantification, we can estimate the proportion of economic costs from a specific extreme weather event that are attributable to climate change. However, research is yet to use this approach to estimate the value of climate change-attributed economic costs from extreme weather that have already been experienced globally. In this paper, extreme event attribution data has been collected, allowing us to estimate an average fraction of attributable risk (i.e. the portion of risk for which climate change is responsible) for different classes of extreme weather events – including heatwaves, droughts, floods, storms, wildfires, and cold waves. We then combine this with existing economic cost data from EM-DAT, including the number of deaths (converted using a value of statistical life) and economic damages, to approximate the climate change-attributed global cost of extreme weather using extrapolated reasoning. From this, we estimate that US$2.90 trillion in economic costs from extreme weather are attributable to climate change over the period from 2000 to 2019, equivalent to an annual average cost of US$145 billion. This shows that present estimations of the global cost of climate change are largely underestimated. This attribution-based estimate is higher than estimates from some Integrated Assessment Models, including William Nordhaus’s DICE model, which are designed to measure the total economic impact of climate change inclusive of, but not limited to, extreme weather-related costs. This demonstrates that the crude nature of climate inputs in existing climate-economy modelling has a limited ability to capture costs from tail-end extreme weather events. The experimental attribution-based approach to global estimation is a best first-attempt which provides a new, alternative tool for measuring the costs of climate change.</p>
Title: The Climate Change- Attributed Economic Cost of Extreme Weather
Description:
<p>Climate change is changing the nature of extreme weather events across the globe.
Extreme event attribution is used to quantify the extent to which anthropogenic climate change is responsible for the change in frequency or severity of a specific extreme weather event.
Using this quantification, we can estimate the proportion of economic costs from a specific extreme weather event that are attributable to climate change.
However, research is yet to use this approach to estimate the value of climate change-attributed economic costs from extreme weather that have already been experienced globally.
In this paper, extreme event attribution data has been collected, allowing us to estimate an average fraction of attributable risk (i.
e.
the portion of risk for which climate change is responsible) for different classes of extreme weather events – including heatwaves, droughts, floods, storms, wildfires, and cold waves.
We then combine this with existing economic cost data from EM-DAT, including the number of deaths (converted using a value of statistical life) and economic damages, to approximate the climate change-attributed global cost of extreme weather using extrapolated reasoning.
From this, we estimate that US$2.
90 trillion in economic costs from extreme weather are attributable to climate change over the period from 2000 to 2019, equivalent to an annual average cost of US$145 billion.
This shows that present estimations of the global cost of climate change are largely underestimated.
This attribution-based estimate is higher than estimates from some Integrated Assessment Models, including William Nordhaus’s DICE model, which are designed to measure the total economic impact of climate change inclusive of, but not limited to, extreme weather-related costs.
This demonstrates that the crude nature of climate inputs in existing climate-economy modelling has a limited ability to capture costs from tail-end extreme weather events.
The experimental attribution-based approach to global estimation is a best first-attempt which provides a new, alternative tool for measuring the costs of climate change.
</p>.
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