Why Is It Hard To Predict A Hurricane's Intensity?

Melissa Block speaks with Hugh Willoughby, meteorology and research professor at Florida International University, about why it is so hard to predict the intensity of hurricanes. He says it's much easier to make a good prediction about where a storm will go than it is to predict how strong it will be. He says one thing that will make hurricane predictions better in the future is the steady march toward more powerful computers.

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MELISSA BLOCK, host: So how accurate were the forecasts for Irene in the end? Hugh Willoughby is a professor of meteorology at Florida International University. He studies the dynamics of hurricane motion and intensity. Professor Willoughby, welcome to the program.

HUGH WILLOUGHBY: Glad to be here.

BLOCK: It sounds like the hurricane came ashore where forecasters predicted, but then, as we've just heard, it did veer off what the predictions were. Is that right?

WILLOUGHBY: It wasn't exactly on the track that they forecast, but it was certainly within the usual errors. One of the things that is a problem often with track forecasts is the presence of mountains or just land will cause the storm to bend in ways that we don't predict particularly well. It makes a big difference to the people under the storm, but it's kind of in the noise of what the forecast process can handle.

BLOCK: Had forecasters warned of this, this historic deluge that ended up hitting Vermont and upstate New York?

WILLOUGHBY: Everybody I talked to before the event, they were all saying this is going to be a flooding event and with two concerns. One is it was the time of the new moon, where the tidal range is the largest. So the high tides are higher. And it was moving so slowly that we were guaranteed that somebody would get the storm surge at astronomical high tide.

And secondarily, these storms that affect New England are always big rain producers. You don't have to run a model to know it's gonna rain a lot. The question is, who's it gonna rain on?

BLOCK: Right. And in terms of what happened in Vermont and upstate New York, was that an area that the forecasters said that - had said, you better look out, this is coming your way?

WILLOUGHBY: My rating of the official forecasts, as they were coming out, was that really everybody in New England needed to be concerned that it would be a big flooding event.

BLOCK: We heard on the program on Friday, the head of the National Hurricane Center say they have gotten much more accurate in predicting the path of a hurricane. But in terms of predicting the intensity of a storm, that accuracy is still not there. And the head of FEMA today said they have a lot of work to do in being able to accurately predict how intense a storm will be. Why is it harder to predict the intensity? What are the variables that go into that?

WILLOUGHBY: Hurricane intensity is a combination of a lot of factors. How does the wind change with height around the hurricane, the wind shear, ocean temperature? Is there a deep layer of warm water above the cold water that fills the deep ocean? Is there land near the storm such that dry air coming off the land can keep it from intensifying?

Oddly enough, dry air from the Sahara Desert actually gets as far west as U.S. waters. And sometimes a storm will be surrounded by Saharan air that will keep it from intensifying. And evaluating how these factors interact with each other and interact with the present state of the storm, it's just a lot more complicated problem than predicting where it's going to go.

BLOCK: So what would it take to improve the accuracy in modeling just how intense a hurricane will be?

WILLOUGHBY: Computing power is always a limiting factor in weather prediction. You know, a computer for weather forecasting model has to run a lot faster than the weather to really be useful. So there's a limit as to how elaborate you can make the equations that represent physical processes. So, you do what's called parameterization, which is to represent a complicated process by a simple formula. And the simpler the formula is, the more it degrades accuracy. As computers get to be more powerful, you can represent things in more detail. So, that's a big factor.

We've also come to understand some things better. So, a combination of observations and experimenting with the models to make them better and experience with running forecasts helps you tune the model. It's an art rather than a - well, it's a science but it's also an art, I guess is the way to describe it.

BLOCK: Professor Willoughby, thank you very much.

WILLOUGHBY: Thank you.

BLOCK: That's Hugh Willoughby, professor of meteorology at Florida International University in Miami.

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