Study Finds Most Sea Level Research Relies on Models, Not Measurements

Researchers say majority of coastal sea level studies underestimate threat to hundreds of millions of people

Mar. 21, 2026 at 9:00pm

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A new study has found that over 90% of research on rising sea levels is based on computer models rather than real-world measurements, leading to underestimates of the threat to coastal communities. The findings contradict recent media reports claiming scientists have a firm grasp on the extent and pace of sea level rise.

Why it matters

Accurate data on sea level rise is critical for communities to prepare and adapt to the impacts of climate change. If research is overly reliant on flawed models, it could lead to a false sense of security and inadequate planning for the risks facing hundreds of millions of people living in low-lying coastal areas.

The details

The study examined the methodologies used in a large sample of published research on coastal sea levels. Researchers found that the vast majority of studies - over 90% - utilized computer models and simulations rather than direct measurements of water levels. This over-reliance on modeling has resulted in underestimates of how high sea levels already are in many regions, with some areas seeing levels up to 3 feet higher than previously thought.

  • The study was published on March 21, 2026.

The players

NOAA

The National Oceanic and Atmospheric Administration, a U.S. government scientific agency that monitors and reports on climate and environmental data.

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What they’re saying

“The rate of global sea level rise is accelerating: it has more than doubled from 0.06 inches (1.4 millimeters) per year throughout most of the twentieth century to 0.14 inches (3.6 millimeters) per year from 2006-2015.”

— NOAA

The takeaway

This study raises serious concerns about the reliability of much of the existing research on sea level rise, which appears to be overly dependent on imperfect computer models rather than direct measurements. It suggests the threat to coastal communities may be even more severe than previously understood, underscoring the urgent need for more rigorous, empirical research to guide adaptation efforts.