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By Matthew Green
LONDON, Feb 8 (Reuters) - Misuse of climate models couldpose a growing risk to financial markets by giving investors afalse sense of certainty over how the physical impacts ofclimate change will play out, according to the authors of apaper published on Monday.
With heat waves, wildfires, massive storms and sea-levelrises projected to intensify as the planet warms, companies areunder growing pressure to disclose how the disruption couldaffect their businesses.
But the authors of a peer-reviewed article https://t.co/oVO3rI6YyT?ssr=truein Nature Climate Change warned that the drive to integrateglobal warming into financial decision-making had leap-froggedthe models used to simulate the climate by "at least a decade".
"In the same way that a Formula One Grand Prix car is notwhat you would use to pop to the supermarket, climate modelswere never developed to provide finessed information forfinancial risk," said Andy Pitman, a climate scientist at theUniversity of New South Wales and a co-author of the paper.
Improper use of climate models could lead to unintendedconsequences, such as "greenwashing" some investments bydownplaying risks, or hitting the ability of companies to raisedebt by exaggerating others, the authors said.
The problem is that existing climate models have beendeveloped to predict temperature changes over many decades, atglobal or continental scales, whereas investors generally needlocation-specific analysis on much shorter time frames.
Neither are climate models designed to simulate extremeweather events, such as storms, which can cause sudden financiallosses.
To bridge the gap, the authors called for the development ofnew forms of climate projection to support the financial sector,backed by "climate translators" qualified to help regulators,investors and companies make better use of the science.
"Businesses like using models, because the numbers give thema sense of security," said Tanya Fiedler, a lecturer at theUniversity of Sydney and lead author of the paper. "It doesn'tnecessarily mean the numbers are reliable."(Reporting by Matthew Green; Editing by Hugh Lawson)