Scientists warn against misuse of climate models in financial markets


LONDON, Feb 8 (Reuters) – The misuse of climate models could pose a growing risk to financial markets by giving investors a false sense of certainty about how the physical impacts of climate change will unfold, according to the authors of a article published on Monday. .

With heat waves, wildfires, massive storms and sea level rises projected to intensify as the planet warms, companies are under increasing pressure to reveal how the disruption could affect their businesses.

But the authors of a peer-reviewed paper here in Nature Climate Change cautioned that the push to integrate global warming into financial decision-making had outpaced the models used to simulate climate in “at least a decade.”

“In the same way that a Formula One Grand Prix car is not what you would use to go to the supermarket, climate models were never developed to provide accurate information on financial risk,” said Andy Pitman, a climate scientist at the University of NY. South Wales and co-author of the article.

Inappropriate use of climate models could have unintended consequences, such as “green-whitening” some investments by minimizing risks, or affecting companies’ ability to increase debt by overstating others, the authors said.

The problem is that existing climate models have been developed to predict temperature changes over many decades, on a global or continental scale, while investors generally need location-specific analysis in much shorter periods of time.

Nor are climate models designed to simulate extreme weather events, such as storms, that can cause sudden financial losses.

To close the gap, the authors called for the development of new forms of climate forecasting to support the financial sector, backed by qualified “climate translators” to help regulators, investors and companies make better use of science.

“Companies like to use models, because numbers give them a sense of security,” said Tanya Fiedler, a professor at the University of Sydney and lead author of the paper. “It doesn’t necessarily mean the numbers are reliable.” (Reporting by Matthew Green; Editing by Hugh Lawson)

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