The Economics of Everyday Things - 49. Weather Forecasts

Episode Date: May 20, 2024

With industries relying on them and profits to be made, weather forecasts are more precise and more popular than ever. But there are clouds on the horizon. Zachary Crockett grabs an umbrella. SOURCES:Steve Adelman, head of Adelman Law Group, PLLC and vice president of the Event Safety Alliance.Peter Neilley, director of weather forecasting sciences and technologies for The Weather Company. RESOURCES:"Traders Have Turned Betting on the Weather, a Technique Pioneered by Enron, Into a Booming $25 Billion Market," by Dylan Sloan (Fortune, 2024)."Why Your Weather Forecasts May Soon Become More Accurate," by Dan Stillman (The Washington Post, 2023)."The High-Tech Race to Improve Weather Forecasting," (The Economist, 2023)."Study: Climate Change Has Increased Atmospheric Instability Over Past 40 Years," by University at Albany (Phys.org, 2023)."Beyoncé Concert In D.C. Suburb Highlights Complex Weather Challenges," by Marshall Shepherd (Forbes, 2023)."Forecast Process," by the U.S. National Weather Service. EXTRAS:"How Will We Handle the Heat?" by Freakonomics Radio (2022)."The Folly of Prediction," by Freakonomics Radio (2011).

Last August, more than 50,000 people made their way to a stadium in the suburbs outside of Washington, D.C. They were there to see Beyonce during her Renaissance world tour. But Mother Nature wasn't making it easy. There was a storm front rolling in. People were waiting outside. The organizer said, you don't want to go out to the seats where you're exposed to lightning strikes.

Stay in the concourse. That's Steve Adelman, Vice President of the Event Safety Alliance. He's a sports and entertainment lawyer who works on live events. And he spends a lot of time thinking about how things could go wrong. His biggest concern is usually the weather. The organizers of the Beyoncé concert, the only thing

they didn't account for is that on a hot steamy August night in the D.C. area, putting thousands upon thousands of people in the concourses becomes a health and safety disaster because people got dehydrated and started fainting in the concourses Edelman works in just one of the many industries that hinge on weather live event planners airlines Retailers farmers. They all have to plan ahead and make weather-related decisions. Because, as it turns out, there's a lot at stake. When is the storm likely to arrive? What is the nature of the storm?

The downside risk of leaving everyone in harm's way when there's lightning in the forecast is extremely bad. For the Freakonomics Radio Network, this is the economics of everyday things. I'm Zachary Crockett. Today, weather forecasts. From the time he was eight years old, Peter Neely knew exactly what he wanted to be when he grew up. You'll see this kind of thing time and time again for those in our profession. You know, they were five years old

and they saw a tornado at their grandmother's house or they experienced a big blizzard and they just sort of knew it. Young Peter Neely was right. He's now director of weather forecasting sciences and technologies for The Weather Company. We're probably best known by some of our brands like the Weather Channel, Weather.com, Weather Underground.

Predicting the weather requires a number of skills. First of all, fundamentally understanding the physics of how things work, like hot air rises. Well, how much will it rise and how quickly will it rise? How does a raindrop form? Will it stay in the cloud or will it fall out of the cloud and become precipitation? That's all sort of governed by details of what we call the cloud physics. We then can embody those details of the physics in algorithms that describe the evolution of the atmosphere based on a current state of the atmosphere.

To start, meteorologists read the current state of the atmosphere from a huge host of observational tools that continually record data. We've had instruments to measure humidity, temperature, and barometric pressure for more than 500 years. But it wasn't until the 19th century that organized weather observation networks were formed across the United States. Over the following decades, tools like the telegraph, the radio sound, and radar allowed meteorologists

to collect a wide range of data and detect patterns that could create a forecast. By the 1940s it started to become clear that making accurate predictions required a lot of fast calculations. Making it the perfect task for a computer. And over the last 75 years since the advent of supercomputers, they've just incrementally gotten better and better. Supercomputers digest all that data and feed it into algorithmic models crafted by scientists. The meteorologists then interpret the output to predict what is most likely to happen next in our atmosphere. The precision by which we can run these models increases as there's more computer capacity going on, the science that's in the models gets better.

And so our forecasts have gotten better by about a day per decade. And what that means is the forecast for five days in advance today is about as accurate as the forecast for three days in advance 20 years ago. That improvement has meant good business for Neely and his colleagues. In 2023, a morning consult survey put the weather company in the top 10 most trusted brands alongside UPS and Kleenex. It serves more than 300 million people each month through its digital properties alone. And it was recently acquired by a private equity firm for more than a billion dollars.

There's a good chance if you're watching the six o'clock news tonight, you're seeing a weather show which is largely produced by the weather company, or at least using the technologies and data from the weather company. Yet, when it comes to predictions, even the weather company can't account for everything. We fundamentally don't know the temperature five miles above the ground out over the South Pacific Ocean right now. We can make a good guess of it, but we fundamentally don't know it. And we'll never be able to know what the temperature and the precipitation, the moisture

and everything is at every place all the time. There's just this little gap between how good we are now and the theoretical limit to how good we ever could be. Lots of folks are trying to narrow this gap. But can they? That's coming up. Interest in the weather has never been greater, which means there's money to be made. The global market for forecasting services has recently been valued at over $2 billion.

That includes things like subscriptions, apps, advertising revenue from weather stations, and special weather services purchased by businesses. Wall Street has taken an interest in weather, too. There's now a $25 billion market built around buying and selling weather derivatives, basically bets on future weather patterns within a certain period of time. Yet up until the last decade, the mightiest tools for gathering weather data, like satellite and radar systems, belonged mainly to government agencies. systems belonged mainly to government agencies. The weather company's Peter Neely says that's been changing.

Increasingly in the last 10 years or so, there's been an advent of commercial enterprises deploying their own weather observing equipment. And oftentimes it's some new technique that will provide us a different way to observe or learn some more about what the atmosphere is. Private companies have been able to launch satellites into space to measure atmospheric conditions all because the cost of doing so has dropped significantly over the last few decades from hundreds of millions of dollars to around five million in some cases. Although satellites have been contributing mountains of additional data, which helps increase the accuracy of forecasts.

For these companies, the cost is worth it. My study a couple decades ago estimated that over 30% of the total US economyS. economy is dependent on the weather in some form or other. Agriculture is foundationally dependent on the weather. Transportation is disrupted by weather events a lot. Construction and onward and onward. There's a lot of ingrained dependency in the weather.

Few fields are more dependent on weather forecasting than the aviation industry, where expensive decisions are made on a minute-by-minute basis. Certainly at the Weather Company, we have meteorologists who are embedded inside some of the major airlines around the country, sitting next to dispatchers and helping them make decisions, for example, should we put a little bit more fuel on this flight? Because when the flight gets to New York, there might be thunderstorms in the area, which will cause the flight to need to circle around for a little bit because of delays of arrivals into the airport. And if we put a little bit more fuel on that flight, the chances that it might actually

need to be diverted to an alternative airport go down. When it comes to the airlines, it's easy to see the value of ever more precise weather predictions. So forecasters find ways to measure how confident they can be in their forecasts. One big factor is what's known as atmospheric stability, which is notoriously hard to measure. Yeah, that gets a bit tricky and it has to do with the chaotic nature of our atmosphere. When it's unstable, the little differences at the beginning translate into big differences at the beginning translate into big differences at the end. The thunderstorm is a representation of a very unstable atmosphere. And so, if we don't get the temperatures exactly right,

we may not know whether or not the atmosphere is going to be stable or unstable. According to the National Oceanic and Atmospheric Administration, since 1980, the U.S. has seen 383 weather events, with damages exceeding a billion dollars. And so, meteorologists are increasingly turning to another tool to help individuals and businesses try to make better decisions when it comes to weather. Artificial intelligence has hit the scene only in the last two or three years or so, and the progress has been nothing short of stunning. AI tools have been able to spot patterns that might elude human meteorologists. In some cases, AI can do this before anyone even understands the underlying science. A study was published late last year on an AI-powered weather prediction model built

by Google, which outperformed government models that have existed for decades. There's so much enthusiasm for how much this approach can bring to our ability to forecast weather. A new factor, however, is making prediction harder. And it's one that AI and supercomputers can't fully account for. Climate change. Forecasts that rely on historical data can struggle as the atmosphere becomes more unstable than ever before. Last year, insurance marketplace Lloyd's of London

said that global economic losses due to extreme weather events could top $700 billion in the next five years. Every professional meteorologist has told us it's harder to make an accurate prediction because the models are all based on historical data. But the historical data is based on pre-climate change circumstances. Again, that's live events attorney Steve Adelman.

Storms rise faster now than they used to. They become more violent more quickly now than they used to. They become more violent more quickly now than they used to. And so even the weather trigger charts that we rely on to say, all right, we have 30 minutes to evacuate the house before the storm arises, that 30 minutes may now be 27 minutes because of climate change. Temporary structures generally have wind ratings, but they were designed for a different climatic world than the one that we're living in now. Despite all of this chaos,

the amazing thing is that weather forecasting is more accurate than ever. And in general, you can feel confident that the weather you'll encounter on an average day will look a lot like what your weather app predicts. As long as you don't expect 100% certainty. Whatever my family asks me about what the weather forecast is, I always give them the standard answer, partly cloudy chance of showers.

For the economics of everyday things, I'm Zachary Crockett. This episode was produced by Julie Canfer and Sarah Lilly and mixed by Jeremy Johnston. We had help from Daniel Moritz-Rapson. Are the clouds a thousand feet above the ground or two thousand feet above the ground? It's just clouds to us. The Freakonomics Radio Network. The hidden side of everything.