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The New Climate Math on Hurricanes 86

Climate change has intensified hurricane wind speeds by an average of 19 mph in 84% of North Atlantic hurricanes between 2019-2024, according to new research that links warming ocean temperatures to storm intensity for individual hurricanes.

This year, Hurricanes Helene and Milton slammed into Florida, breaking meteorological records and causing catastrophic damage. The study by Climate Central found that higher sea surface temperatures elevated most hurricanes by an entire category on the Saffir-Simpson scale, with three storms, including Hurricane Rafael, seeing wind speeds increase by 34 mph due to warming.

Researchers calculated storm intensity using models of pre-warming ocean temperatures. "It's really the evolution of our science on sea surface temperature attribution that has allowed this work to take place," said lead author Daniel Gilford, noting that hurricane damage increases exponentially with wind speed. For example, a storm with double the wind speed can cause 256 times as much damage. The methodology enables scientists to determine climate change impacts on hurricanes in near-real time.

The New Climate Math on Hurricanes

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  • AFAIK, wind power is proportional to the cube of wind speed. At least this is the way wind generators are designed. So if you double the wind speed, the available energy in theory increases by just sixteen times.
    • AFAIK, wind power is proportional to the cube of wind speed. At least this is the way wind generators are designed. So if you double the wind speed, the available energy in theory increases by just sixteen times.

      Yeah, this seems to be an example of the word "exponentially" to mean "a lot." You see that misusage a lot these days. (And the word "exponentially" is not there in the actual article [iop.org].)

      That factor of 256 would imply that damage goes as the eighth power of wind speed. I find that difficult to believe.

      • by ThosLives ( 686517 ) on Friday November 29, 2024 @01:12PM (#64979693) Journal

        It's monetary damages, not force damage, if you read the references. Also note that as wind speeds go up, you also get more water damage, and because water damage goes with the inundated area, then you can see that you can easily get another nonlinear increase in damage.

      • Regarding damage, that is not that difficult to believe.

        The houses are designed to resist wind speed X.

        They are over engineered to resist 2*X.

        They are not over engineered to resist 8*X.

        So, you have 1000 houses, during X only one gets damaged. With wind power reaching 2*X, 4 or 5 where the "over engineering" was not good enough get damaged.

        And with 8*X wind power: all houses get flattened.

      • When you expand a surface area you literally have an exponential power in the equation.

        • by ceoyoyo ( 59147 )

          Are you confusing an exponential, n^x, with a polynomial, x^n? Most of us live in an approximately Euclidean universe where the formula for area is 4*pi*r^2. The surface area on a sphere, or an oblate spheroid like Earth is a little more complicated, but it's still effectively a power of ~2 so long as you're talking about reasonably small angles.

          I asked chatGPT if there are any not-too abstract examples of metric spaces with exponential area formulas. It turns out there are, depending on whether you conside

    • It is a little bit more complicated than that when it comes to storm damage though. Still, even a 10% increase in wind speed can easily hit the safety margins for most buildings.

  • by davide marney ( 231845 ) on Friday November 29, 2024 @03:29PM (#64979969) Journal

    FTA: "Hurricanes—especially landfalling hurricanes with high intensities—can act as 'focusing events' that draw public attention (Birkland 1998, Arnold et al 2021, Silver and Jackson 2023). Increased attention during and in wake of storms creates opportunities for public and private discourse around climate and disaster preparedness (Cody et al 2017, Wong-Parodi and Garfin 2022). Climate change attribution plays an important role in these discussions. Social studies have shown that personal experiences with extreme weather and attribution messaging both have strong potential to influence public perceptions of climate risk and decision-making (Ogunbode et al 2019, Boudet et al 2020, Osaka and Bellamy 2020, Ettinger et al 2021, McClure et al 2022, Thomas-Walters et al 2024, Zanocco et al 2024). Presenting scientifically-sound estimates, and carefully, deliberately conveying methodologies can be effective for attribution-driven climate communication (Osaka and Bellamy 2020, Ettinger et al 2021, van Oldenborgh et al 2021, Thomas-Walters et al 2024)."

    The purpose of the paper is to develop an "attribution framework", meaning, a way to separate human influences from natural causes, for the ultimate purpose of communicating climate change to the public. A laudable goal, but frankly looking at their approach does give me some pause. The idea seems to be to model "counterfactual" measurements of how intense storms would be without human influences, and then compare those to current storm intensities. I'm not nearly well-informed enough to know if this approach has any merit, except to note that it leaves up to the study authors to define both the starting AND ending points of the delta, so that sounds like it just magnifies the potential for error.

    But we'll see.

    • by hey! ( 33014 )

      It's what the public always asks scientists -- did this happen because of climate change? That's not a question scientists were prepared to answer, because it's almost too vague to be meaningful. This is an attempt by several scientists to bridge that gap by focusing on one parameter that links anthropogenic climate change and hurricane behavior -- sea surface temperatures. But as the abstract itself notes, "this study introduces a novel rapid attribution framework that quantifies the impact of historic

    • Largely with climate science you can work out the counterfactual by just looking at past measurements.

      With any modelling theres always a dice roll involved (one which you can often bump into "within error bars" territory by running it a lot, and if the models accurate, monte carlo will push you close to reality) but yeah thats just how the game works with meteorology and atmospheric physics. You refine and you refine and eventually you'll get it to a point where its useful, at least for policy making (which

  • Tornado strength, at least in US, has been going down the last decade or so. Interesting...

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