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This climate study made a big error. One piece of data was to blame

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By illuminem briefings

· 3 min read


illuminem summarises for you the essential news of the day. Read the full piece on The Washington Post or enjoy below:

🗞️ Driving the news: A landmark 2024 climate study predicting catastrophic global GDP losses due to climate change has come under scrutiny after researchers identified a critical data error involving Uzbekistan
According to a new commentary in Nature, Uzbekistan’s flawed GDP figures — including implausible 90% economic swings — skewed the study’s results
Removing the country from the dataset significantly revised the projected 2100 GDP loss from 62% to 23%

🔭 The context: The original study, published by researchers at the Potsdam Institute for Climate Impact Research, quickly became one of the most cited climate papers of 2024 and was used in global financial planning by institutions like the World Bank
Its alarming findings tripled previous climate damage estimates, drawing intense public and policy attention
The new analysis from Stanford researchers has sparked debate about data integrity, methodology, and scientific transparency

🌍 Why it matters for the planet: Accurate projections of climate damages are vital for guiding global adaptation funding, investment decisions, and mitigation targets
Overstated damage estimates could erode scientific credibility or misguide resource allocation, while understated risks may delay urgent climate action
This case underscores the importance of data quality and model validation in climate economics — a field with growing influence over global policy

⏭️ What's next: Nature is currently reviewing the original paper, and may take editorial action pending its assessment
The original authors stand by their conclusions, asserting that updated models with corrected data still show substantial climate-related economic harm
Critics argue, however, that methodological changes used to uphold the conclusions raise concerns about scientific rigor
The debate is likely to continue across academic, policy, and financial sectors that depend on reliable climate impact models

💬 One quote: “Science doesn’t work by changing the setup of an experiment to get the answer you want,” — Solomon Hsiang, director of the Global Policy Lab at Stanford University

📈 One stat: Removing Uzbekistan from the dataset reduced projected global GDP loss by 2100 from 62% to 23% — a nearly threefold decrease in estimated economic damages

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