Inside Howden’s AI Lab: Can Microsoft Azure’s Climate Risk Model Protect Investors from Future Losses?

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Microsoft's Aurora AI predicts deadly storms with better accuracy than humans—and does it thousands of times faster.

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When Typhoon Doksuri threatened the Philippines in 2023, official forecasts got it wrong. Aurora correctly predicted its path four days ahead.

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Traditional weather forecasting needs massive supercomputers and hours of calculations. Aurora delivers 10-day forecasts in seconds.

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"For the first time, an AI system can outperform all operational centers for hurricane forecasting," says Penn researcher Paris Perdikaris.

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Aurora isn't limited to rain and sunshine—it accurately predicted a massive sandstorm that sent thousands to hospitals in Baghdad.

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Trained on over one million hours of atmospheric data, Aurora outperformed traditional models in 91% of forecasting tests.

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The secret? Aurora is a "foundation model" that understands Earth systems, not just weather patterns.

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Even the European Centre for Medium-Range Weather Forecasts—the gold standard in prediction—was beaten by Aurora in 92% of tests.

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Beyond storms, Aurora accurately tracks ocean wave heights during typhoons—critical information for shipping and coastal communities.

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What happens when poor countries can't afford supercomputers for weather forecasting? Aurora could level the playing field.

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But AI isn't perfect—researchers warn these systems struggle with rare "gray swan" events and could "make up something completely crazy" without oversight.

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As extreme weather increases worldwide, will AI forecasting mean better warnings, faster responses, and lives saved?

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