100 Years Of Your Daily Weather Forecast

JOHN DANKOSKY: This is Science Friday. I’m John Dankosky. The American Meteorological Society is celebrating its centennial this year. And a lot has changed in the past 100 years– little things like computers, satellites, the internet. So how have these things changed your local forecast and what meteorologists do day to day? And as the climate changes, how will meteorology have to adapt? 

Joining me now is Richard Alley. He’s the Evan Pugh professor in the Department of Geosciences at Penn State University and coauthor of an article this week in the journal Science looking at the history and future of meteorology. Richard Alley, welcome to Science Friday. Thanks for joining us. 

RICHARD ALLEY: Well, thank you, John. It’s a pleasure to chat with you and your listeners. 

JOHN DANKOSKY: Also joining us is Angela Fritz. She’s an atmospheric scientist and deputy weather editor for The Washington Post. Thanks so much for joining us as well, Angela. 

ANGELA FRITZ: I’m so happy to be here. 

JOHN DANKOSKY: Our number is 844-724-8255. That’s 844-SCI-TALK if you’ve got big weather questions for our guests. Please don’t ask them, will it rain today, but bigger questions about meteorology. And there’s a lot to talk about. Richard, I’ll start with you. How far have we come in 100 years? 

RICHARD ALLEY: Oh, just fantastically. 1938, a hurricane came storming ashore from about where you’re sitting there in New York across the way to Rhode Island. It killed about 600 people. Nobody knew it was coming. It came screaming out of the Atlantic with virtually no warning. When I was a kid, you had a day’s warning. And now we have three days. 

No warning, you die when the storm hits. A day, you might be able to get out of the way. But if it’s a big city, you’re not going to. You don’t have time down to empty the city. Three days, you can do it. And so as more and more people are in the firing line of big storms, fewer and fewer people have to die. 

JOHN DANKOSKY: And it’s not just big storms. It’s just the day-to-day accuracy, too, Richard. You’re able to just tell a lot more about the weather than you used to. 

RICHARD ALLEY: It’s beautiful. So the people who work hard on this– and Angela knows this very well. But they have developed metrics of how well forecasting is doing. And the improvement in forecast skill is really, really clear. It’s really obvious because they figured out how to do it better. 

JOHN DANKOSKY: Angela, tell us about that. How much do you think accuracy has improved over these last 100 years? 

ANGELA FRITZ: Actually, I think in Richard’s paper there’s a really great stat in there that we like to cite a lot. Richard, is it five to one? A five-day forecast now is as good as a one-day forecast used to be mid-20th century. Is that right? 

RICHARD ALLEY: Yes. 

ANGELA FRITZ: Yeah. So it’s incredible. And people like to rag on forecasters and meteorologists all the time. But if you actually look at the statistics, we kind of get it right a lot. 

JOHN DANKOSKY: Yeah. What are the things that have actually helped to improve this so much? Angela, if we look at a one-day forecast versus a five-day forecast, that is a big jump. But of course, we can tell weather pretty accurately 10 days out. What exactly led to these improvements? 

ANGELA FRITZ: There are two big things that we always kind of point out. And the first is just so much more data. We have a lot more observations– so satellite data, more things like thermometers and anemometers on the ground. And so that feeds more information into these weather forecast models that people always hear about. And that’s what helps us determine what the weather is going to be. 

And then on top of that, supercomputers– our computing power has gotten so much better. And that allows us to predict with better accuracy and a higher resolution. Just like your TV has a higher resolution, our forecasts get a clearer picture with more computing power. And so those two things combined have really helped us push forecasting into the 21st century. 

JOHN DANKOSKY: So more data, bigger computers to crunch all that data. But also, you still use things like weather balloons, Angela. a lot of the same old tools that you’ve used for 100 years are still out there. 

ANGELA FRITZ: Absolutely. And that is part of the data that we’re using. And we still look at that weather balloon data to figure out what’s going on in the atmosphere. The old tools are still important and reliable. And the things that we knew about the atmosphere back in the ’50s still hold today. 

So our basic knowledge of how the weather works still holds. And that’s what those weather models are built on. It’s built on fluid dynamics. It’s all physics. And what we’re able to do now is really model that physics and crunch all of the numbers in a very precise way and as close to accurate as possible because of the ability to have so much data and the computing power and, as Richard talks about in this paper, a special thing called “data assimilation.” 

JOHN DANKOSKY: Well, Richard, maybe you can talk a little bit more about that. 

RICHARD ALLEY: Sure. So Angela is completely correct. They’ve also made the models better. But then how do you get the modern state of the atmosphere into the model? How do you let the model know what we know, sort of get the model up and running so it goes through the present as accurately as possible and into the future? 

And this involves these very sophisticated techniques of basically letting the model interpolate between the data and letting the data bring the model back to reality. And this crosstalk between data which are necessarily incomplete and models which don’t know everything has really given us the ability to know better. The faster computers then let them tweak the data little bit within the uncertainties and run you an ensemble of futures until it can tell you what the uncertainty is, as well as what is likely to happen. 

And so all of these put together have been necessary. It really did need better models, more data, better ways to put them together on faster computers, and then one more piece, which is it needed really good people who can take what comes out and make it useful. And it’s easy to overlook Angela and a whole bunch of people like her who make these data useful for you. But they are an essential piece in the end. 

JOHN DANKOSKY: Yeah. They’re those people who, as she said, sometimes get a bad rep. Maybe we’ll come back to that in a little bit. 

[LAUGHTER] 

RICHARD ALLEY: Please do. 

JOHN DANKOSKY: We’re talking about the past, present, and future of predicting the weather if you want to give us a call and ask a big weather question. 844-724-8255 or 844-SCI-TALK. Richard, tell us a little bit more about how this entire forecasting system is set up. There’s kind of a public-private partnership? 

RICHARD ALLEY: Absolutely. So the backbone for a very long time has been the public collecting data and running the models, making forecasts, and making them useful. There actually is scholarship on the payoff on this, how much good that society gets out of their investment in weather forecasting. And the answer is that between 3 and 10 times payoff, an investment that pays 300% to 1,000%. 

So this has long been going on that we invest in this. It’s a public good that needs to be made available for everyone. And then what has grown up is a lot of people have said, we can take what the government produces. And we can make it even more useful to you. 

And so there’s an additional world of targeted forecasting, targeted communications of taking what comes out of this big public effort and making it a public-private effort. A whole lot of businesses with really hard bottom lines that have to pay off are hiring weather forecasters because it pays off. They can use that knowledge in ways that are good. And we have students that come routinely from the military because the military knows they need good forecasts, too. 

JOHN DANKOSKY: Marty has a question along these lines calling from Ellensburg, Washington. Hi there, Marty. You’re on Science Friday. 

MARTY: Hi. 

JOHN DANKOSKY: Hi. What’s your question? 

AUDIENCE: Yeah, hi. Thanks. My question is, we have all these different places TO get weather forecasts. And I’m wondering if they’re all using the same basic information from the US Weather Service or if they all have their own information sources. 

JOHN DANKOSKY: That’s a great question. And Angela, maybe you want to pick up on that because I think people are confused. There’s so many places you can get a weather forecast these days. 

ANGELA FRITZ: Yeah. And Marty’s question is actually something we get asked a lot. The basic backbone is all the same. But the way it’s applied might be different. So there’s the National Weather Service. There’s the app on your phone, Weather Channel, AccuWeather. And then there’s your local TV station. 

So the data that comes in is all the same. And then everyone gets to see the models. Some of the private companies have their own weather models. And some people give that forecast a personal touch. So it’s unlikely that you’re going to see the same forecast across every single app or TV station. 

And so what you actually have to do is– I always just recommend finding a forecast outlet that you like, that you think is accurate, that you can relate to, and that you can trust because it’s important to get the weather right day to day. But it’s also really important to find a trusted source for when the weather is going to be really bad that you can go to and get your emergency information from them. So that’s always my recommendation. 

JOHN DANKOSKY: Speaking of emergencies, I think Richard touched on this earlier. But Angela, especially in hurricane season, we hear about these different models, what they are, why they’re different. Maybe you could just explain a little bit more, especially when it comes to predicting something that’s really as devastating potentially as a hurricane. 

ANGELA FRITZ: Sure. So all of the different models– and the UK has their own set of models. The Europeans do, Canada, the US. They’re all trying to model the basic physics equations of the atmosphere in slightly different ways. They all have different approaches to answer the same questions. 

And within those models, they also run them several dozens of different times with very little tweaks to their initial conditions. So they’re starting points because, like Richard said, we don’t know exactly what the state of the weather is at this very moment. It’s impossible to know exactly what it is. 

So accounting for the fact that we don’t know and we know that there’s going to be some error there, we run it to get that chaos effect into it to get that butterfly flapping its wings and get a little chaos in there so that it generates that spaghetti-string output that you see during hurricane season with all the squiggly lines that you’ll see on TV. It looks a little weird. But what that actually does is– what we get out of that is a consensus because down the middle of that group of squiggly lines is an average. 

And what we have found over the past couple of decades is that the most likely reality, the most likely good forecast is right down the middle. So if you can take several hundred different forecasts from several hundred different models, what actually is going to happen is probably really close to what’s right down the middle. And that has been where weather forecasting has been going over the past couple of decades. 

JOHN DANKOSKY: I’m John Dankosky. And this is Science Friday from WNYC Studios. Richard Alley, I would love to ask you about some of the big impacts on our world that really good weather forecasts have. So it’s not just whether or not you take an umbrella out or even whether or not a bad storm might hit. But there are day-to-day economic impacts that are felt by either good weather forecasts or bad weather forecasts. What can you tell us about that? 

RICHARD ALLEY: Right. So it is very clear that we use weather forecasting in a lot of ways. We check it a huge number of times. And it’s beneficial to us, which is why we do this. And this is why businesses invest. 

What’s coming now is the ability to take the weather forecast and to use it to forecast other things that you really care about. So when they give you the hurricane track, they don’t just say, you will get hit by the hurricane. But they also tell you how high will the storm surge be. Do you really need to get out a ways inland? 

And that comes from taking the weather forecast and coupling it to a targeted model that looks at how the ocean responds to the winds and the pressure. They will join that to a flood forecast, which takes the weather forecast and the rain and puts it into a model of how water runs off the land, how it gets into the river, how fast the river rises. And now you have river experts and ocean experts who are taking the weather and using it to tell you what you can do to make yourself safe. 

We have a world now that see ice is thinning on the Arctic. When the Arctic had a huge amount of sea ice all the time, nobody in their right mind went up there unless you had an icebreaker or a dog sled. And now you have a military ship or a ship full of cars being shipped across the Arctic Ocean or a ship full of tourists. 

And as soon as you have people up there, the sea ice does regrow in the winter to some extent. Now you can get a ship trapped. And you need a sea ice forecast. And they can do sea ice forecasts. 

They can actually forecast bird migrations now. The birds want to go at a particular time of the year. But they want to go when the weather’s right. They want to ride the wind and not fight it. And so you can actually combine knowledge of biology with knowledge of the weather to tell the wind turbine operator, hey, there’s a huge flock headed your way. Shut it down for the night. 

JOHN DANKOSKY: I have to ask you– we just have a couple minutes left. Angela, as Richard brings up sea ice melting, the specter of climate change hanging over all this, how much more difficult does that make your job right now? How much more difficult could it be in the near future? 

ANGELA FRITZ: I think that we’re seeing extreme weather get worse. And we’re seeing things that we haven’t seen in the past. In terms of how difficult it is to predict, I don’t know if it’s making forecasting more difficult. I think it’s just that the events that we’re seeing are more extreme and maybe less believable in advance for some people. And Richard, you can tell me if I’m wrong. But I think that overall, the physics of the atmosphere– fluid dynamics is not going to change unless something really bad happens. 

JOHN DANKOSKY: Yeah. Richard, I’d love your thought on that. A little less than a minute left. Go ahead. 

RICHARD ALLEY: Right. So the physics is right. It works. But climate change is making it harder in the sense that if you get more rain, the flood gets harder to forecast because it comes faster. But they’re doing a great job of it. And they can do this. The physics works, and it’s real. 

JOHN DANKOSKY: And you sound very enthusiastic about the future, Richard. 

RICHARD ALLEY: It’s fantastically bright. If we keep the investment going, the payoff is very clear. The public-private partnership is very clear. It’s moving us forward. We can do great things. 

JOHN DANKOSKY: But it takes a big investment, which is, I think, maybe a topic for another day. Richard Alley– he’s the Evan Pugh professor in the Department of Geosciences at Penn State University. Thank you so much. I appreciate it. 

RICHARD ALLEY: Thank you. A real pleasure. 

JOHN DANKOSKY: Thanks also to Angela Fritz. She’s atmospheric scientist and deputy weather editor for The Washington Post. Thank you, Angela. 

ANGELA FRITZ: Thanks for having me.

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