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SPEAKER_16: we find out whether the future of our society is best off in the hands of government science done for the public good or big business out to make a buck. Comes to us from our reporters,
SPEAKER_16: Simon Adler and Annie McKeown. Okay, the only thing I'm going to ask Annie is that you stay
SPEAKER_13: like right up on your mic. Yeah, okay, Simon. Not a problem. Okay. So, we're here to talk
SPEAKER_13: to you guys about the thing you talk about when you don't know what else to talk about, which is the weather. That's cute. That's great. But while talking about the weather might be the smallest of small talk, we're going to start with the story where it was anything but. It's early June 1944. World War II is raging. And the Allies.
SPEAKER_17: They're getting ready for Operation Overlord, which is the D-Day landing.
SPEAKER_13: The largest invasion in human history. And not to put it too fine a point on it,
SPEAKER_17: they were dealing with really crappy weather. Big swells, strong winds. Rain.
SPEAKER_13: This, by the way, is meteorologist and historian Chris Harper. Professor at the University of Copenhagen.
SPEAKER_13: And she says the weather was so bad that Eisenhower was concerned they might not be able to do the invasion at all. Are we going to have to postpone this by two weeks? If we have to postpone this by two weeks or a month, then like we've amassed all of these troops. Like the element of surprise goes out the window.
SPEAKER_17: And so Eisenhower needed to know when there would be some calm periods, some breaks, so that they could go ahead and make the landing. He needed a forecast.
SPEAKER_17: And I mean, there were only a handful of meteorologists in the military.
SPEAKER_13: And so he grabbed who he could get. This tall, dapper man. Irving P. Crick.
SPEAKER_21: Eisenhower needed to forecast out a week in advance in order to do this. This is him in an old TV interview. And in it, sporting this white shock of hair hunched
SPEAKER_13: over a desk covered with weather maps.
SPEAKER_13: He says he was told to make this impossibly high-stakes forecast. ["The Star-Spangled Banner"]
SPEAKER_16: Literally life and death. Like, if the waves are too big, one of those boats is going to capsize and all those people are going to drown. Right.
SPEAKER_21: ["The First World War,"
SPEAKER_21: and eventually, ["The First World War,"
SPEAKER_13: June 6, 1944.
SPEAKER_07: ["The First World War,"
SPEAKER_13: and when that date arrived, ["The First World War,"
SPEAKER_09: ["The Day You Were Here," ["The Day You Were Here,"
SPEAKER_21: ["The Day You Were Here," and then the day you were here." What kind of a day was it?
SPEAKER_21: Well, it was a day in which every element of the combat team, the amphibious forces, the gliders, the bombers, everyone could operate. And it was bad up around Calais, where the Germans thought we were going to land, which was good. Because the Germans and their forecasters said we would not come. They were fooled and then sent reinforcements to Normandy until it was too late, and told Rommel he could go on.
SPEAKER_13: ["It turned out okay." Thank God. ["Yeah." And of course, this victory became a huge news story.
SPEAKER_21: ["Alive forces have succeeded in their initial landings in France." ["The plans for the invasion were more complex than any before."
SPEAKER_13: And our man Crick…
SPEAKER_21: ["Imagine being the man who had to come up with the D-Day forecast."
SPEAKER_25: He became this hero. ["Dr. Crick successfully fixed June 6th, Dr. Crick, the man who predicted D-Day."
SPEAKER_19: Gosh, go Irving.
SPEAKER_13: Yes, but only sort of. ["This is, this is where the issue, the issue came in."
SPEAKER_13: Like, to be clear, while Crick was getting all the credit, there were multiple teams of meteorologists who worked on this with him. ["Two British teams and an American team."
SPEAKER_17: Okay. ["And in fact, Crick's forecast was overridden by these other guys who pushed it off for a couple of days." Ooh. ["Ooh. Yeah, right."
SPEAKER_13: Yeah, he didn't get the forecast right. But when reporters would ask him about it… ["The regular weather service, both in this country and in England,
SPEAKER_21: did not feel confident in that type situation." …he'd take credit. ["They couldn't forecast beyond two days, really, and there was one storm after another coming across the Atlantic and needing a week. They simply didn't want either or to take that risk."
SPEAKER_16: Wow. Irving! Oh, man. That just feels unnecessary.
SPEAKER_17: ["Yeah, it was really bad. But, but this wasn't odd."
SPEAKER_13: Chris says, long before World War II, Crick had a reputation for pushing the ethical boundaries. I mean, back in the 1930s, when he was working at Caltech, he got a phone call, and it was the producers of Gone with the Wind, and they said, hey, we need to burn down the city of Atlanta. ["What's that?"
SPEAKER_25: ["A gal in Atlanta must have sent fire to the warehouses near the depot." We can't have big gale-force winds coming in.
SPEAKER_13: Like, what's the best day we can film this? And so, you know, he gave them a forecast. ["Which is not inherently bad if you want to do forecasts for Hollywood. Super!
SPEAKER_17: But he made this forecast on university time with U.S. Weather Bureau equipment and got paid for that. Wow. ["You know, like, you just don't go there." You could piss a lot of people off with that one.
SPEAKER_13: ["Yeah, you just don't go there." And so, while these two famous forecasts ["Conditions had to be just right for the burning of Atlanta."
SPEAKER_02: made him sort of a star in the eyes of the public,
SPEAKER_13: ["Dr. Irving Crick, the most successful weatherman in the world."
SPEAKER_17: ["The hottest thing in meteorological history."
SPEAKER_13: Professionally, it was a very different story.
SPEAKER_17: ["After D-Day, most meteorologists didn't want to be necessarily associated with Crick. And so, the president of Caltech was so embarrassed by the whole thing, and so he just completely shut down the entire meteorology department."
SPEAKER_19: So Buddy needs another place to take his skills. Yeah.
SPEAKER_16: Not feeling so bad for him, but yeah. Yeah.
SPEAKER_19: At all.
SPEAKER_13: I don't think we need to feel bad for him. He sort of made his bed and is now lying in it. Yeah. And because what he did next, well, it shook meteorology and changed our relationship to the weather in ways we're just beginning to fully feel today.
SPEAKER_10: ["Crick was, uh, Crick was clever."
SPEAKER_13: This is meteorologist Howard McNeil. He was a contemporary of Crick's.
SPEAKER_10: ["Yeah, he was a very prismatic individual. And, uh, he was his own man."
SPEAKER_13: And so, Howard says, after Crick got fired, he was basically like, ["F*** you. If you don't want me, I don't want you. And in fact, I don't need you. Because you know what I got? I've got fame. And that thing I did for Gone with the Wind, providing a personalized forecast and getting paid for it? Like, I'll just do that."
SPEAKER_10: ["Private weather service. And in those days, that was a pretty radical thought."
SPEAKER_13: And so Crick started his own company, this sort of shadow weather bureau, hiring people like Howard, ["I went to work for Crick." and offering forecasts to anyone who would pay. And before long,
SPEAKER_17: ["Business was booming for him."
SPEAKER_02: ["Thanks to his talent, Crick's list of clients reads like a world atlas." His work has brought praise from a host of private clients,
SPEAKER_21: ["We were doing all this consulting work for the motion picture studios and power companies and agriculture."
SPEAKER_13: wanting to avoid costly rescheduling or delays. Farmers hired him to tell them when to water. Film crews hired him to tell them when to film. ["Civil engineers working on bridges, construction people."
SPEAKER_13: Builders went to build. ["To the US, Canada, Europe, and North Africa."
SPEAKER_13: To help his retail clients, ["Daymar is your saving stone."
SPEAKER_13: He did things like direct shipments of umbrellas to stores where it would be raining, and sunblock shipments to places where it'd be sunny. He even dabbled in marketing. ["Hurling wet, heavy snow, 32 below."
SPEAKER_26: ["We use it year-round." ["The prior rainy days weren't so tricky."
SPEAKER_13: I mean, in a matter of years, the guy did what no one thought was quite possible, which was he turned the weather into this product. ["Now's the time to shave."
SPEAKER_02: ["I'm really scorching." ["A beautiful day tomorrow, mostly sunny."
SPEAKER_20: Wow. Crick, Crick, Crick, Crick, Crick.
SPEAKER_19: Are we on his side now? We're still not liking him? No, no! I'm less on his side.
SPEAKER_13: Well, you're not alone.
SPEAKER_17: ["Okay, do you remember anything about what the meteorological community's view was of Crick?" ["Well, he just didn't like the idea of selling them."
SPEAKER_13: Chris Harper actually interviewed a bunch of meteorologists from back then about this very thing. Meteorologists like Edward Lorenz here. ["So part of the concern was that he was selling the forecast?"
SPEAKER_17: ["Yes. People didn't know it was a bit, this was, was that what they,
SPEAKER_13: this was what they really know how he has to run it." And as he explained to Chris, up until this point ... ["I mean, the US government was meteorology in the United States,
SPEAKER_17: and they were totally focused on the public good and keeping people safe." But Crick, you know, he was doing it for profit.
SPEAKER_13: Which sometimes meant stretching the truth.
SPEAKER_25: ["Okay, I think that's it." ["All right. Okay."
SPEAKER_13: Like here in this TV interview.
SPEAKER_25: ["Hey doctor, first question is, just for those who don't know, commercially, what can you offer a client in terms of long-range weather?" ["Well, we can offer them temperature and precipitation far out into the future.
SPEAKER_21: Sometimes for years in advance." ["Whoa."
SPEAKER_00: ["Okay."
SPEAKER_13: Yeah, he claimed he could forecast a year out. Which, even today, if you ask a meteorologist, they'll tell you, it just isn't possible.
SPEAKER_21: ["Uh, now the way we've discerned it is unique, because, uh..." ["We don't make a theory and then try to fit nature to our theory. I learned this 50 years ago when studying with Einstein. He said, don't try to..." Einstein? Yeah. ["Just, uh, you watch nature and let nature tell you what it's doing, and then you'll have the answers, and that's basically what we've done."
SPEAKER_13: And just for the record, Crick may have bumped into Einstein once or twice at Caltech, but he certainly didn't study with him. Like, Proffitt got involved and he was no longer just a scientist.
SPEAKER_17: ["He's, he's a, he's a salesman, is what he is."
SPEAKER_13: And ironically, all of the data he was using to make these forecasts, to make this money, it was all government data. And yet, for reasons that remain sort of unknowable, the man seemed to have a vendetta against the very institution providing it to him. ["In fact, Crick's basic, he told me privately one time, he said,
SPEAKER_10: I'd like to close down the National Weather Service.
SPEAKER_10: That's what my goal is, to close them down and have it all turned over to private enterprise." Whoa. That's so...
SPEAKER_19: That's a super villain thing to say.
SPEAKER_16: Yeah. Wow. Then he cackled maniacally after he said it every time. I don't know. Clap of thunder. Yeah, yeah, right, exactly. Then lightning.
SPEAKER_13: Now, Crick kept making forecasts up until his death, and his company is actually still around today. But of course, you know, he didn't manage to take down government weather.
SPEAKER_20: ["Well, it's hot as balls."
SPEAKER_13: And thank goodness. ["Where are we?"
SPEAKER_20: ["We're at the weather palace of the United States of America."
SPEAKER_13: ["And it is a palace." Because I gotta say, like, in the years since Crick, government weather has become our, maybe our best. ["It's a glass building that has..." Maybe our only remaining example of a true marriage between government serving the public good and the highest levels of science.
SPEAKER_13: ["Hello." And so to see this up close, we went to the National Oceanic and Atmospheric Administration, NOAA, to meet some of the people who pull this off every day. ["What do you have on your tie here?"
SPEAKER_14: ["This is earth and weather satellites." ["And did you wear it for us, or do you wear something like this every day?"
SPEAKER_20: ["Uh, I mix it up, yeah.
SPEAKER_14: I like to show a little bit of weather in my attire. I don't have my lightning socks on today." ["Oh, you didn't wear your lightning socks?" ["No, I tried to find something." And hanging out with these folks, like meteorologist Jordan Gerth here,
SPEAKER_13: ["My actual title is leveraged observations lead."
SPEAKER_15: LOL.
SPEAKER_13: It was clear that weather forecasting is this incredible triumph of data capture and analysis. ["Weather data are the basis of prediction.
SPEAKER_15: So we collect so many different kinds of observations that the amount of data that comes in is absolutely enormous. It's just the, it's the best big data problem that I think we have on this planet."
SPEAKER_13: So yeah, let's talk about that for a minute. How many observations will you all be taking in this day?
SPEAKER_15: ["In innumerable amount. Billions." Billions? ["Billions."
SPEAKER_13: Six point three billion. This stuff gets fed into computer models and lands on the desks of scientists like, ["I'm constantly switching between different surface observations."
SPEAKER_14: Ian Russell and Alison Santorelli,
SPEAKER_13: ["Yeah, so I'm working on fronts in the medium range period."
SPEAKER_13: who blend that data with other data, ["During that period that I'm forecasting for."
SPEAKER_13: compare it to historical data, ["There's Jason.
SPEAKER_16: He's working on ocean prediction."
SPEAKER_13: and simply put, synthesize it into the forecast that you and I get for free every day.
SPEAKER_19: All of this so that we can decide whether to wear a light coat or a heavy coat. Exactly.
SPEAKER_13: And also, ["The National Weather Service in Indianapolis has issued a tornado warning for..."
SPEAKER_13: you know, prepare for the worst. I mean, these forecasts and these warnings save an untold number of lives each year, which, you know, in our divided times is sort of strangely unifying. NOAA is equally looking out for all of us. And nobody's like, you know, those Democrats, they've been putting their finger on the scale and saying it's going to rain. In the water, or like whatever. Yes. Like everyone's basically like, ["Ah, good, yeah, yeah, yeah, OK, I'm going to plan using this information that the government has provided to me." Does feel neutral. Yes. People, by and large, trust them.
SPEAKER_13: But, yes, here's the but. We're now at a moment in time where the government's scientific dominance when it comes to the weather and this view of weather forecasting as a public good, these are both under threat. And in a sense, Irving Crick's dream is finally coming to fruition.
SPEAKER_03: ["Minor changes in weather can trigger major business impact."
SPEAKER_13: I mean, private weather forecasting is currently a 17 billion dollar a year industry in the US.
SPEAKER_14: ["Use weather forecasts to improve customer service."
SPEAKER_03: ["Embed weather into your business for deep..." With one report saying there are as many as 45,000 different companies involved.
SPEAKER_13: 45,000 Irving P. Crips. ["Take control of tomorrow today."
SPEAKER_13: And on our trip to visit NOAA, ["In a quarter mile, you will arrive at your destination."
SPEAKER_20: So where are we going? We actually drove out to meet one of them.
SPEAKER_13: This silver-haired, always smiling guy by the name of Don Bershoff. ["CEO of True Weather Solutions. They call me the weather don in the business."
SPEAKER_05: ["He is the weather don." ["That's so good." ["They do, right? I mean, yeah."
SPEAKER_20: ["Are you wearing socks with umbrellas on them?"
SPEAKER_05: ["Yes I am."
SPEAKER_13: Before starting True Weather Solutions, Don was kind of a big deal inside the National Weather Service. ["I was a science and technology director. I had a 130 million dollar budget.
SPEAKER_05: My job was to find the best science, the best technology, and try to integrate it into operations." Anyhow, we met up with him at a drone range,
SPEAKER_13: this big open field where people can test their unmanned aircraft. ["We're gonna see his drone. And there's Don with his drone."
SPEAKER_20: And the reason we were there was actually to see one of his.
SPEAKER_13: ["Look at this thing. Okay. Can I pick this thing up?" ["Yeah, go ahead." It was all black, weighed about five pounds. ["It's very light." Looked a lot like a curling stone with a bunch of propellers attached to it. ["It's science quality. Measures temperature, wind, pressure. It's fully automated. It's amazing."
SPEAKER_13: And this little drone, it represents a huge shift that's underway. Because while Crick had to rely on the government for data, Don, with a fleet of these drones and other devices, is beginning to collect and sell his own.
SPEAKER_05: ["We've never had this kind of data before."
SPEAKER_13: ["Okay, well, so we were at NOAA, and they were saying 6.3 billion observations every day. How is this going to make a dent in that?"
SPEAKER_05: ["Well, maybe what NOAA didn't tell you is that we have a data void below 5,000 feet. The satellites do very well at detecting wind and moisture and things like that above that level. But below that level, the only thing we have today to measure temperatures and winds and pressure is weather balloons. It's ridiculous!"
SPEAKER_13: Yeah, turns out the government's best way to collect atmospheric observations is still launching balloons up into the sky twice a day.
SPEAKER_05: ["So having something like this going up every 90 minutes and giving you data, it's going to be the game changer. But it's not just this that's going to help us."
SPEAKER_13: Next, Don walked us over to this mini fridge-sized device with an eyeball-looking mirror on the top of it. ["This is just basically a laser that pops straight up and looks up in the sky."
SPEAKER_05: ["So right here, out of the eye, bzzzzzzz." ["Yeah, and can see particulate matter moving." ["Like raindrops or what?" ["No, no, dirt. Dust. And then it computes the winds from the movement of those particles and tells us what the winds are doing up to 800 feet at 10 layers. It gives us 10-layer wind measurement. Again, we don't have that data today."
SPEAKER_13: ["And why, why are you doing this? And why isn't NOAA doing this?" ["You really want me to answer that question?" ["Yeah, of course I do."
SPEAKER_05: ["All right, so something like this is very difficult to get into the budget because it requires resources. And I'm not sure it's necessary to meet their mission."
SPEAKER_13: Don says the government's goal is to make big national forecasts. And to do that, there are better things for them to spend their money on. But companies, obviously, they have very different goals and therefore need very different kinds of data. ["Walmart super inflation buster sale blast through the inflation barrier with big discount sales."
SPEAKER_02: I mean, just as one example of what these companies are up to, several years back,
SPEAKER_13: Walmart came out and explained that, cross-referencing their weather and sales data, they found that clouds and wind influenced the beef people buy. Meaning, if it's hot, cloudy, and windy...
SPEAKER_05: ["I want a cut that's tender, that's juicy, and it's aged just right." For some reason, people tend to buy steaks.
SPEAKER_05: ["...natural steaks from Walmart."
SPEAKER_13: But the minute those clouds go away and the wind's lessened, people want burgers. And knowing this, Walmart is serving you different digital ads based on the weather at your zip code. I mean, companies are beginning to use weather data to guide their business in the same way Facebook and Google use user data.
SPEAKER_13: And Don says, for lots of these companies, the government's data, it's just not what they're looking for. It's not precise enough.
SPEAKER_05: ["So we actually are going to bring precision to the game." ["Said like a true salesman." ["No! Spoken like a true scientist. No, I'm a scientist. I'm not selling you here. I'm telling you. I know that we can do better."
SPEAKER_13: Now, Don's quick to point out that his data, it could be used to help improve government forecasts.
SPEAKER_05: ["Noah is going to want to buy this data, and I talked to the weather service the other day about this. ["I'm not trying to hide it, because when you combine these types of observations with the government data, ["put it into our models, now you're going to have unimaginable knowledge of what's happening."
SPEAKER_13: But just because Don's willing to share doesn't mean that every company is going to be so open. And so, while any company out there can get all of the government's data for free, there's no promise that the government or you or I or any government agency is going to have access to their data. ["You got it. They have commercial data sets that the government may not be getting.
SPEAKER_05: ["And so at some point, there's going to be a company here that's going to outperform the government forecasts. ["And at that point, you know, what's the future of government weather?"
SPEAKER_13: Or more pointedly, you know, what's the future of how we use the weather to make decisions?
SPEAKER_11: ["You know, we've just started working with cities as well. The city of Hoboken is an example."
SPEAKER_13: Lastly here, this is Dan Slagan. He's the CMO of a commercial forecasting company called tomorrow.io. Like Don's company, they are collecting their own data. ["We take into account both public and private data sets."
SPEAKER_13: They're launching a satellite later this year, and they're doing crazy things like looking at the way a cell phone signal drops between towers because they found they can figure out rainfall from that. ["That's so weird."
SPEAKER_16: ["Wow." Anyhow, he says Hoboken hired them to provide information that the weather service just couldn't.
SPEAKER_13: ["They first started working with us to cut costs around specifically winter snow and icing
SPEAKER_11: operations. So just meaning how many trucks do we need to send out, how much salt do we need to deploy." And while snow removal is harmless enough, ["With climate change, every single city,
SPEAKER_11: every single government, every single country is going to need a climate security and climate resiliency plan." In other words, as the weather gets less predictable and more impactful,
SPEAKER_13: cities are going to have to make all sorts of tough decisions about what building permits to give, where to draw new floodplains, and where to put new cooling centers.
SPEAKER_11: ["Right now we're seeing cities start to understand that you can really use us to make all these types of decisions. So the need for what we're doing is only going to become bigger, and the approach that we've taken, we really expect spec to be the source of truth for weather for the world." Wow. It's that thing. It's like you add — I mean, you have the, you know,
SPEAKER_19: U.S. Weather Bureau, and it just feels like civic goodness, we'll collect, we'll report, we'll be in it together to help each other. And then you add this sort of market incentive, and it just evolves the technology so much quicker. Totally. And I mean,
SPEAKER_13: returning to Crick once more, like despite his faults, the guy was forecasting with a computer before the weather service, and you could argue pushed government weather into the computer age. But with this speed and innovation comes less equity, right? SONIA DARA-MARTIN Yeah.
SPEAKER_04: SIMON ROGERS Hmm.
SPEAKER_13: SONIA DARA-MARTIN Yeah. SIMON ROGERS I mean, what happens when two cities next to each other have to figure out where to put flood walls, and one of them can afford a company with proprietary data, and one can't?
SPEAKER_13: I mean, it appears the weather, this thing we've all had equal access to, is beginning to fracture so that the more money you've got, the better the predictions you can get, and the better you can plan and prepare. And this is happening right as summers are getting hotter, as hurricanes are getting stronger, as rain and thunderstorms are getting stronger, as rain and thunderstorms are getting more intense. So the timing isn't great for all of this to be happening, is what I would argue. SIMON ROGERS That's a very good point.
SPEAKER_16: SONIA DARA-MARTIN Hmm.
SPEAKER_20: So you can take a minute to think about all that, but when we come back, Simon and I dive into a particular place where profit-driven weather prediction might just be the thing, the only thing, that can help us face our changing world. SIMON ROGERS And we'll get to that right after a quick break.
SPEAKER_16: NARRATOR There is a continual battle going on between warm air moving up from the tropics and
SPEAKER_02: cold air coming down from the Arctic. A weather front is where the two air masses meet. The cold air piles in under the warm air and throws it up to where it's cooler. That, in turn, causes it to lose its moisture as rain or snow. That, very simply, is the process of weather. Different fronts and pressure patterns creating every kind of weather imaginable. MARYBETH ABBETH-BELLE Hi. This is Marybeth Abeth-Belle from Oregon,
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SPEAKER_27: the media's deep focus on Hillary Clinton's server hygiene at the expense of policy issues, is history repeating itself? You can almost see an equation again, I would say led by the times
SPEAKER_03: in Biden being old with Donald Trump being under dozens of felony indictments. Listen to On the Media from WNYC. Find On the Media wherever you get your podcasts.
SPEAKER_27: All right, Lulu.
SPEAKER_19: Latif. Radio Lab, we are back. Before the break, we witnessed a parade of salesmen trying to make a buck off the wind and rain. And now we're going to hear a story about a for-profit profit. Who just might be our best hope for the future. Thanks so much for that Lulu. And of course,
SPEAKER_16: for that story, we're going to swivel to the Weather Desk where our crack team of forecasters, Simon Adler and Annie McEwen will take it from here. All righty. So for this next part,
SPEAKER_20: we're going to leave behind Crick and Gone with the Wind and turn to something that is perhaps more worthy. Yeah, definitely. Of the silver screen. Wait, who would play you? Who do you
SPEAKER_18: want to play you? Oh, I don't know. I mean, Sandra Bullock, I take her. Okay. This is Karen. Karen
SPEAKER_20: playing herself. Yes. And the scene opens in 1987, London, England, in a large, high ceilinged, wood paneled room. It was called the, it's still the Lloyd's library. She's at a place called
SPEAKER_20: Lloyd's. Lloyd's of London. The oldest insurance marketplace in the world. Very successful, very prestigious. And so rich, they even insure insurance companies. It's called Reinsurance. Risk-taking is their business. These are the big dogs of the insurance industry. And about 150 of them in well tailored suits are taking their seats. They were all men, very proper
SPEAKER_18: British men. I don't even know if women were allowed in Lloyd's at the time. Probably they were, probably they were, but you didn't see many women there except for the administrative help.
SPEAKER_20: And Karen, who is young and American and a woman makes her way to the front of the room. I was seven months pregnant at the time. Whoa. Waddling around, setting up this computer,
SPEAKER_18: which I don't know if you know what a compact computer is, but a portable computer you kind of had to wheel it in. Stretching the definition of portable. Yes, exactly. And she was there to
SPEAKER_20: give a presentation on a kind of tool that she had just built. My hurricane model. The world's
SPEAKER_20: very first predictive hurricane computer model. Whoa. She showed them how by gathering all this
SPEAKER_20: scientific data on past hurricanes and plugging it into a computer, she was able to generate a very
SPEAKER_18: large catalog of potential future events. A list of possible hurricanes on the horizon.
SPEAKER_20: She then showed them if she slammed those possible future hurricanes into some properties, say on the eastern coast of the United States, she could prove that the loss potential was much
SPEAKER_18: higher than insurance companies thought. The insurance safety net was far too small to cover
SPEAKER_20: the damage that she was there to tell them was coming. And that meant all those men sitting in that room were going to lose money. A lot of money. Right. Wait, question, question.
SPEAKER_19: Is she sniffing out climate change? Well, she's not quite sniffing out climate change. Like this
SPEAKER_20: is the mid 1980s. So it's a little early to be on top of that. It's more like she thought that she could offer something that government services could not. Like the government was letting people know if a hurricane was on its way, but they were not forecasting out 10, 20, 30 years in terms of what hurricanes could look like. And Karen figured that that's exactly what the insurance industry really needs. But when she finished her presentation, instead of a flurry of excitement, It was very silent. I don't think there were any questions. No questions, no questions,
SPEAKER_18: but they were very polite, you know, very respectful.
SPEAKER_13: Is it because they thought you were wrong or the model was wrong? Why weren't they more interested?
SPEAKER_18: Well, you know, they were already re-insuring hurricane risk in the U.S. and they thought they do it very well because they had been making a lot of money in the 1970s. And in the early 1980s, there were no major hurricanes to hit, especially a major populated area in the U.S. So, you know, when it came to hurricane risk, they were already the smartest people on the planet, of course.
SPEAKER_20: But that was not going to last. So we're going to zoom ahead here to 1992. By this time, Karen has started her own company. And she has a five-year-old at home. Yeah, almost five. And she's got also two other kids. So she's got three kids now. Okay. And she's doing the thing. She's doing computer modeling.
SPEAKER_19: Yes. She has about 30 clients. She helps them price insurance, offers day of loss estimates
SPEAKER_20: whenever there's a hurricane. And her clients are using her model. But rather than letting it guide their decisions, they're sort of just using it as one data point of many. In other words, they were not really taking it seriously. Exactly.
SPEAKER_20: Which brings us to a Friday afternoon in late August. There was a tropical storm out there named Andrew.
SPEAKER_19: Oh, okay.
SPEAKER_24: It was pretty far out and nobody was really worried about it.
SPEAKER_00: And speaking of Andrew, you can't help but wonder how the prince is reacting to the latest Royal rocket. Everybody thought it was just going to be a nice weekend.
SPEAKER_18: But eight minutes after six, the first tropical storm of the season getting stronger,
SPEAKER_04: not weaker. Very quickly.
SPEAKER_20: And probably it's going to get even stronger. That changed.
SPEAKER_18: And by 11 a.m. on Sunday morning,
SPEAKER_04: it was a cat for a hurricane.
SPEAKER_05: An absolutely enormous hurricane headed directly for Miami.
SPEAKER_23: People stop driving. It's not safe to be driving on these streets anymore. It is starting to rock and roll out here. The power just went out throughout all of
SPEAKER_12: this area. The ocean has begun to invade the land. Absolutely most intense storm right now
SPEAKER_03: is coming ashore. Get to that interior closet. Get your family in there.
SPEAKER_24: We understand right now we can perhaps get the first look at what's going on up in the air from Sky 4. Rob Pierce, are you with us right now? Yes, I am. We're going to look to show you some
SPEAKER_09: of the devastation down here in the Dayland trailer park. You can talk with both Buddy McKay and Linda Shelley and ask them questions. The distraction that Andrew left behind was
SPEAKER_20: completely staggering.
SPEAKER_20: 65 people died. Thousands and thousands of people lost everything.
SPEAKER_25: And while it was obvious to everyone that Andrew had been a big one, shortly after the storm made
SPEAKER_20: landfall, Karen knew that as soon as possible her clients were going to need to know how much is the
SPEAKER_18: total damage going to be. What is the storm's price tag? And so that same morning, very early
SPEAKER_18: we came into the office, they turned on the lights and fired up the computer model.
SPEAKER_20: They wouldn't know the true extent of the damage for months. And the numbers of course were still flowing in. So that meant that we had to run as fast as possible, as many scenarios as possible.
SPEAKER_18: They plugged into the model estimates on where it made landfall, peak wind, size, as well as
SPEAKER_20: an estimate of all the values of all the properties that have been hit. The homes and the businesses, people's things, people's lives that had been in Andrew's path. And they run the model. And then
SPEAKER_18: change the parameters, rerun the model, tweaking it and running it. Let's look at the uncertainty. Suit jackets had been taken off. Let's run it again. Sleeves had been rolled up. Does that look right? I don't know. Coffee had been spilled. It was pretty frantic. But because it was 1992,
SPEAKER_20: was there one computer? Are you all in computers with headsets? Like just... No, we didn't have
SPEAKER_18: headsets at the time. I don't think headsets even existed. I don't know. We just had one major computer. It was a SunSpark server. It had 16 meg of RAM and one gig of hard disk. But that's what we were running it on. So it was more like agitated waiting for the computer to spit out a number. And the computer's getting really hot. Yes. Yes, yes, yes. The fan is whirring. Exactly.
SPEAKER_20: But finally... Oh my God. They had their number. And then they just kind of sat there staring at
SPEAKER_20: it, asking each other, could that be right? Because up until that very moment, the largest
SPEAKER_18: loss to date had been Hugo in 89. And that was only 4 billion. And the computer model was
SPEAKER_20: currently telling them that Andrew's price tag could exceed 13 billion. Jesus. Whoa. That was three times higher than any hurricane ever. If you're right, and this thing costs 13
SPEAKER_13: billion, what would that actually mean for them? That they had been dramatically under-estimating
SPEAKER_18: the risk and they had been dramatically under-pricing their product. This is what
SPEAKER_20: she'd been trying to tell her clients all along. They'd not been charging people enough money for their insurance and therefore they wouldn't have enough money on hand for what she was arguing would be a much bigger loss than they thought. Karen and her team faxed out that giant number.
SPEAKER_20: And within 30 minutes, the phone started ringing off the hook. Karen's clients in London and New
SPEAKER_20: York refused to believe that number, saying things like, a few mobile homes and an air force base,
SPEAKER_18: how much can it be? And I'll bet you five quid, it won't be more than 6 billion. We were getting so much skepticism. At least that's the kind of reaction she was getting from guys in suits,
SPEAKER_20: leaning back in office chairs. But on the ground, it was a different story. It was unbelievable.
SPEAKER_07: It was just hard to fathom what had happened. This is Danny Miller. And I've been in the insurance industry right at 31 years now. In 92, Danny was a loss adjuster. And three weeks after
SPEAKER_20: Andrew hit, he was down in the wreckage of South Florida. Street signs were blown away. There were
SPEAKER_07: no landmarks. Just trying to do his best to actually find the properties. Trying to reach
SPEAKER_07: policyholders, figure out how to get some cash into people's hands that need it. And every night
SPEAKER_20: when he went back to his hotel, all the people sitting around the dinner table with him had been out working in the field all day too. You had a bunch of electrical workers there. You had a bunch
SPEAKER_07: of insurance adjusters and some military folks. And then you would cook out and you would make the best of it. What was the dinner table conversation like? I listened. I was younger at
SPEAKER_07: the time and talking to adjusters that have been in this business a lot longer than I had. They would talk about the losses. They would talk about the number of claims. I think it was more than 700,000.
SPEAKER_13: Were you getting a sense from these other adjusters that financially this was bigger than anything they had been involved with before? Yeah, absolutely no doubt, Simon. I didn't mean to cut you
SPEAKER_07: off there. But yeah, from day one you knew that it was bigger than anything that the insurance industry had ever dealt with before. You know, it was evident that it was going to change the industry.
SPEAKER_25: This, this is total devastation here at Tamiami Airport. When the total damage in dollar form
SPEAKER_20: finally came in, Karen had been right. It actually turned out to be 15 billion. There is not a roof to
SPEAKER_18: be found in this neighborhood. And kind of overnight people realized the homeowners and the business insurance had been woefully underpriced. And those insurance companies were in big trouble. A couple
SPEAKER_07: of carriers that we worked for became insolvent during Andrew, you know, bankrupt. They just basically went out of business. For some insurance providers there was just no coming back from
SPEAKER_20: Andrew. Some of the guys were more experienced and they would talk about kind of watch the
SPEAKER_07: assignments you were getting, right, because you didn't want to work for free and you don't want to work for pennies on the dollar. And you heard about that happening or people you had worked
SPEAKER_13: for that it happened to? Yeah, I mean, a lot of cooler talk, you know. And the ones that didn't
SPEAKER_20: totally go under started to realize that they were going to have to start charging a lot more. However, those companies, along with worrying about their profits, also have to deal with the government, the state government. And to these insurance companies the government was saying, no way. You can't charge whatever price you want. How are the people supposed to afford insurance?
SPEAKER_18: And obviously the insurance regulators in Florida wanted to tamp down increases to the consumers. And so a lot of these homeowner and property insurance companies just left. And to this day
SPEAKER_18: most of them have not returned. And this all meant that when the dust of Andrew had settled
SPEAKER_20: there were over half a million homes along the coast of Florida that could not find insurance. And you could argue that while that is hard, maybe it's for the best. Maybe people shouldn't be building there. Maybe it doesn't make any sense. But this is where the Florida government steps in again. Because people want to build there and politicians want to give people what they want. And so, you know, you had citizens stand up. The Florida legislature gets together and they create
SPEAKER_20: what becomes known as citizen's property insurance. It became the largest insurer in the state of
SPEAKER_07: Florida. A state-run insurance company which formed to insure any homeowners that aren't able to get
SPEAKER_18: cover in the private market. And they charge far less than the private insurance companies.
SPEAKER_20: If you're in South Florida and you can get citizens coverage at 30 to 40 percent less than
SPEAKER_10: the private market, you're going to do that. And since Andrew and citizens property insurance,
SPEAKER_20: that coast, has kept on booming. There was just a vast accumulation in the tri-county area which
SPEAKER_18: has continued to grow. And this government thing is underwriting all of it. Correct. Wow.
SPEAKER_16: It's crazy to take a bet that you know is going to lose. Right.
SPEAKER_20: And you know it's obvious that it's not just an economic bet they're taking. Because when a hurricane rips its way along the Florida coast, along with all those buildings and properties, it's also destroying lives. People in harm's way. Robin good morning as you can see the sun has come
SPEAKER_28: up here in Naples and it's our first real view of the destruction of devastation left behind by Hurricane Irma. Extremely powerful and extremely dangerous Hurricane Katrina. Charlie heads toward
SPEAKER_03: the Florida west coast. Since Andrew there have been about 50, that's five zero, hurricanes or
SPEAKER_20: tropical storms that have caused damage to property or loss of life in Florida. Hurricane
SPEAKER_18: Wilma barrels down on the Gulf Coast of Florida. Hurricane Ian the strongest September hurricane
SPEAKER_08: to strike the Gulf Coast in more than 15 years. And we now know that climate change is warming
SPEAKER_20: the oceans and making the sea levels higher. And for hurricanes that means bigger, stronger, more destructive storms plowing into more and more heavily built up coastlines and the people who live there. Out on the barrier islands if you're listening please heed this warning that
SPEAKER_23: if things get so bad out there nobody is going to take a chance rescue services the managers emergency operation managers say they are not going to go on suicide missions out to folks.
SPEAKER_20: While the government's actions seem to be ignoring that reality the insurance companies are staring it right in the face. Yeah I mean the insurance industry you're not going to a conference that
SPEAKER_07: does not talk about climate change you know it is an obstacle and a challenge that we're dealing with every day. And after Andrew, Karen's model. It really exploded and you know every re-insurer
SPEAKER_18: had to have it and every insurance company had to have it and of course it grew to other perils, earthquakes, tornadoes, hail storms. And Karen incorporates climate change data into a lot of
SPEAKER_20: her models but whether or not they're effective. At the end of the day it is a political decision
SPEAKER_18: really that you know for example like wildfire in California right now the California Department of Insurance they won't allow the catastrophe models for some reason they don't want the catastrophe models so you know. What the hell is that about? Yeah because they are afraid that it's going to make the premiums go up but as a consequence they have a huge availability problem and they have the same problem after Andrew they have a fair plan which is the state insurer blast resort that's ballooning now because you can't get wildfire insurance in California. Wow. That's insane.
SPEAKER_20: That's totally insane. It's like let's put a blindfold on. Exactly you know it does it doesn't
SPEAKER_18: make sense. And just to be clear California doesn't want that model to be run because then
SPEAKER_13: there would be hard numbers staring them in the face much like yours with Hurricane Andrew about how big the bag they might be holding would be and therefore premiums have to go up therefore everyday Californians need to pay an extra 50 bucks a month for their insurance is that that's the idea? I can't speak to their motivation but we can hypothesize on it and if that's your theory
SPEAKER_18: I'm not going to dispute it.
SPEAKER_09:
SPEAKER_20: I just think it's weird I mean it just kind of swaps out public institutions and for-profit institutions in my head I mean I have this very simplified understanding of corporations as not thinking ahead just getting what they want leaving messes behind you know and I think of the government as trying to not do that and it's just sort of interesting that in this case there's like a flip and there's action happening but it's happening to simplify it like from the bad guys you know? Well and there's a little bit of both on both sides there. This is director emeritus
SPEAKER_20: for the American Meteorological Society Keith Sider and we ran all this by him the story of Irving Crick this insurance situation and his take was oddly comforting? You know market forces
SPEAKER_06: if you want to think in terms of a market that doesn't care about people or about or any of those sorts of things if you want to have it be sort of a uncaring market all by itself is going to try to drive us in the right direction. You know renewable energy now is the cheapest way to make electricity and so the economic drivers are not ones where we have to say oh we have to give up something to get electricity that's clean. Now that's the cheapest way to get it and that gives me optimism because that means that now the people who do not want to see us move in the directions we have to move are working against market forces and it's hard to work against market forces for very long. And so even you know if greed is on your side then you've got a chance to move the ball a lot faster. I want greed on my side all the time. Yeah me too.
SPEAKER_13: Greed is like an incredible wind at one's back.
SPEAKER_19: The road to Eden is paved with bad intentions. Yeah maybe sometimes. It's greed that got us into
SPEAKER_13: this problem. It's the exploitation of natural resources in the name of the almighty dollar that got us into this problem and it's hard for me to imagine a way out that doesn't have those same characters at the forefront. Greed is green. Greed is green.
SPEAKER_16: This episode was reported by Simon Adler and Annie McEwen, produced by Simon Adler and Annie McEwen with sound and music from Simon Adler and Annie McEwen. Mixing help from Arianne Wack and Jeremy Bloom. Special thanks to Zandra Clark, Homa Sarabi, Sanjee Dharmawan, Francisco Alvarez
SPEAKER_19: at Convoy Inc., Maureen O'Leary and everyone at NOAA, Simon Elkebetz of Tomorrow.io, Jack Neff,
SPEAKER_16: Joe Pennington, Brad Coleman, Morgan Yarker, Megan Walker, Eric Bramford, Jay Cohen and
SPEAKER_19: Irving Crick Jr. for supplying us with tons of great archival footage and audio. If you're
SPEAKER_16: curious to know more about the history of weather forecasting go check out Chris Harper's book Weather by the Numbers. Before we go we wanted to let you know that we are working on an
SPEAKER_19: animated video with a very talented artist to illustrate this episode. It'll drop on YouTube in the next couple weeks so keep an eye out on our social media profiles. We're at Radiolab on Twitter and Instagram and you can also find us on Facebook. Also for butterfly and mantis shrimp
SPEAKER_16: members of the lab we will be hosting a live Ask Me Anything session about this episode with producer Simon Adler and a very special guest the god of thunder Thor or Poseidon.
SPEAKER_19: Come and find out. Keep an eye on your inboxes for an exclusive invitation. If you'd like to take
SPEAKER_16: part you can join the lab at radiolab.org join if you aren't already a member cannot wait to see you there. That'll do it for today's News at Nine. Stay safe out there. Bring your umbrella. Get your snow
SPEAKER_16: tires. Radiolab was created by Jad Abumrad and is edited by Soren Wheeler. Lulu Miller and Latif
SPEAKER_01: Nasser are our co-hosts. Susie Lechtenberg is our executive producer. Dylan Keefe is our director of sound design. Our staff includes Simon Adler, Jeremy Blum, Becca Bressler, Rachel Cusick, Aketi Foster-Kees, W. Harry Fortuna, David Gable, Maria Pascu-Tieres, Sindhu Nenasanbandhan, Matt Keote, Annie McEwen, Alex Neeson, Sarah Khari, Ana Rasquette-Paz, Sarah Sandback, Ariane Wack, Pat Walters, and Molly Webster with help from Andrew Vinales. Our fact checkers are Diane Kelly, Emily Krieger, and Natalie Middleton. Hi I'm Erica Inyankers. Leadership support for
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SPEAKER_22: where we take up the big questions of meaning for this world now. In our new podcast season, we're going to have a different human conversation about AI and also the intelligence of our bodies, grief and joy, social creativity and poetry, and so much more. A conversation to live by every Thursday.
