SPEAKER_04: Every kid learns differently, so it's really important that your children have the educational support that they need to help them keep up and excel. If your child needs homework help, check out iXcel, the online learning platform for kids. iXcel covers math, language arts, science, and social studies through interactive practice problems from pre-K to 12th grade. As kids practice, they get positive feedback and even awards. With the school year ramping up, now is the best time to get iXcel. Our listeners can get an exclusive 20% off iXcel membership when they sign up today at iXcel.com slash invisible. That's the letters iXcel dot com slash invisible. Squarespace is the all in one platform for building your brand and growing your business online. Stand out with a beautiful website, engage with your audience and sell anything. Your products, content you create and even your time. You can easily display posts from your social profiles on your website or share new blogs or videos to social media. Automatically push website content to your favorite channels so your followers can share it too. Go to squarespace dot com slash invisible for a free trial and when you're ready to launch, use the offer code invisible to save 10% off your first purchase of a website or domain. Bombas makes clothing designed for warm weather from soft breezy layers that you can move in with ease to socks that wick sweat and cushion every step. Socks, underwear and T-shirts are the number one, two and three most requested items in homeless shelters. That's why for every comfy item you purchase, Bombas donates another comfy item to someone in need. Every item is seamless, tagless and effortlessly soft. Bombas are the clothes that you want to get dressed and move in every day. I'm telling you, you are excited when you've done the laundry recently and the Bombas socks are at the top of the sock drawer because your feet are about to feel good all day long. Go to B O M B A S dot com slash 99 P I and use code 99 P I for 20% off your first purchase. That's Bombas B O M B A S dot com slash 99 P I code 99 P I. This is 99% invisible. I'm Roman Mars. Andrew Blum is a journalist who writes about some of the biggest infrastructure projects in the world. His specialty is revealing how systems we think of as intangible, like the Internet, are actually made up of very real stuff. The Internet relies on cables and wires and data centers, which are maintained by actual people who keep the whole thing running. A few years back, Andrew got interested in the weather forecast. It's this mundane, everyday service that, like the Internet, is made possible by a vast and interconnected global machine that took decades to build. The system is a huge scientific project, but it's also a diplomatic one. The atmosphere crosses all political boundaries, and so knowing the weather requires international collaboration. As weather becomes more extreme, the forecast becomes increasingly important, but ironically, because of its growing value, there are now forces threatening to undermine the global system that makes it possible. It is fascinating stuff. I talked to Andrew about his book, The Weather Machine, and he told me that he first got interested in the forecast back in 2012.
SPEAKER_03: It was a kind of busy season for me. My first book had come out. My dog had died. My son was born. It all kind of happened at once. And there was a weekend afternoon, a kind of Sunday in October, when I had my kind of newborn in one hand and my phone in the other. And I was on Twitter, and all of a sudden, the meteorologists who I followed kind of went into a tizzy. They all just kind of erupted all at once based on the output of a weather model. And what they were seeing was a storm that they had kind of been watching out in the Atlantic, in the southern Atlantic, but suddenly it was going to turn left towards New York, where I live. And it was remarkable because this was eight days ahead. This was a big storm, potentially. And they all kind of trusted the output of this model. They weren't saying, this is definitely going to happen, but it was so far ahead of sort of what I understood as the work of meteorologists, especially kind of hurricane forecasters. Yeah. And this storm that you could kind of see eight days out eventually became Hurricane Sandy.
SPEAKER_04: It is chaos along the Jersey Shore.
SPEAKER_02: The super storm already stretching across one third of this country from Florida to Canada.
SPEAKER_01: ABC News, I covered New York weather for 25 years. I have never seen water in lower Manhattan. There is water now on the streets in lower Manhattan. I mean, the overall feeling when the storm actually came was that our kind of luck had run out,
SPEAKER_03: that New York City had sort of finally begun to reckon with what the storms of the future might be like. With the subways flooded and shut down, you know, nobody did anything for that week. Along the coast it was months and years. And if you live on the L train, it's still being fixed. You know, the consequence of it was really clear. I mean, 147 people were killed. But when it came, for me it was a recognition that that forecast eight days ago was right, that an eight day forecast is not stuff of science fiction, but had just happened in the most consequential way.
SPEAKER_04: And the real difference here between the idea of knowing a thing that's coming in the way that knowing a cold front is coming or knowing that a tornado is coming is that Hurricane Sandy didn't exist eight days before. It was just particles in the atmosphere moving around. And it was a mathematical model that predicted that it would form into this thing that would affect people so dramatically.
SPEAKER_03: I mean, the experience of Sandy made me want to know not only what the weather models were, but where they came from. Sort of who built them, how they had evolved over time. I mean, I recognize them as this kind of complex global infrastructure, but as is often the case with complex global infrastructures, their authorship was really vague and longstanding.
SPEAKER_04: Right. And so, you know, you've spent a lot of time thinking about physical infrastructure. And there's something about the weather forecast that kind of has this vibe of this about mathematical models and physics and stuff in the air, but it still really is rooted in infrastructure. It kind of dovetailed with the thing that you already care about. So, like, what is the modern weather machine actually physically look like?
SPEAKER_03: Well, to kind of see it like that, you kind of have to have this hallucination about, you know, of a sort of planetary scale. You know, it's made up of so many kind of tens of thousands of tiny little pieces. I always like when you're flying out of LaGuardia Airport in New York, if you're lucky, you kind of pass by the weather station there by the runway. And, you know, it looks like a kind of jumble of equipment. And that's one piece of the weather machine. You know, when we see satellite pictures, you know, the kind of familiar weather satellites, that's kind of another piece of the weather machine. And then that's repeated, you know, tens of thousands of times all over the world.
SPEAKER_04: So as you started looking at the history of the weather forecast and how it started, you found that it was actually a revolution in telecommunications that made the first weather forecast possible. So tell me why the development of the telegraph was important for understanding the weather.
SPEAKER_03: It's really about having this picture of the Earth across space. You know, we have maps, you know, that's kind of one way of imagining the Earth. But until you can communicate instantaneously across distance, you know, basically until you have the telegraph and then all of the communications technology that comes after it, you can't really know what's happening simultaneously in many places all at once. It turns out the kind of first step towards knowing what the weather is going to be in one place at many times is knowing what the weather is at one time in many places. That's the kind of key to it. And so you end up, as soon as the telegraph is invented and as soon as there's a kind of rudimentary telegraph network, the telegraph operators begin sending messages to each other about the weather conditions. And they quickly realize, you know, that especially in the U.S., the weather is often moving from west to east. And they can give some advance notice of what's going to happen that afternoon based on, you know, if you're in New York, what it's doing in Ohio. And that just kind of basic sense that you could move faster than the clouds, that the news could move faster than the clouds, begins to, you know, open up this idea of a kind of holistic view of the planet. Suddenly you can kind of imagine yourself looking down, not just on a map as a political idea, but really live, seeing how the weather is changing over space.
SPEAKER_04: So in the 1840s, the Smithsonian Institute takes this grand theoretical idea and turns it into an actual map, which is a kind of beautiful, quirky, analog, fun thing that I loved your description of. Could you describe the map and how it functioned?
SPEAKER_03: Yeah. You know, I mean, as with any corporate or government headquarters, when they built their new building, the centerpiece in the lobby of the Smithsonian Institution on the Mall in Washington was a big map of the, you know, fledgling United States up on the wall, you know, pre-Civil War, 1840s. And whenever they got a report in from their Smithsonian observers, their kind of brand new network of weather observers, they would put a little paper disc up. And the disc would be, have the temperature, it would be, have a different color for the weather. So white for fair weather, you know, black for rain, brown for clouds, blue for snow. And so when you arrived in the Smithsonian, you could look up at the wall and you could see what the weather was across the country. And you could begin to have that first inference of the weather of the future, you know, the forecast based on how those patterns might be changing. Yeah. So then we get to the 1870s when there's an international coalition forming to expand the weather forecast.
SPEAKER_04: And people are starting to think about how to collect and share weather data more widely. I mean, from the beginnings of essentially international networks of any kind, you know, in the 1870s, you have international telegraph networks.
SPEAKER_03: The postal union is formed, you have, you know, the meter convention. You know, it's this really, this kind of vogue for standardization. And a big part of that is the recognition that if you have brand new national weather services, they need a common language for communicating their observations with each other. And we're each going to maybe make our own forecasts, but certainly knowing what the sky is in your country is useful to my country. And that kind of basic sense of meteorology as a common good of the Earth's atmosphere is continuous, really becomes part of meteorological culture from the beginning. They are very good from a very early stage at cooperating with each other.
SPEAKER_04: Yeah. And so it becomes as much of a diplomatic project as a scientific one. Yeah. Yeah, absolutely.
SPEAKER_04: So how did people go from gathering data about the weather to actually doing something about it? Where did they actually start to look into the future of what was to come?
SPEAKER_03: Well, the first person who kind of codified the process that has become the weather models as we know them today was a Norwegian meteorologist named Wilhelm Bjorkness. And it was in the 1890s that he first began to play around with the idea that you could treat the weather forecast as a hypothesis, as a kind of mathematical hypothesis. That if you could calculate the weather, if you could calculate the evolution of the atmosphere, you know, its temperature, its pressure, its wind direction, and you could do that mathematically, then you could be quite sure the next day if you were right or wrong. And if you were wrong, you could begin to refine your equations and then do it again the next day. Or you could even go back and use the previous day's observations and calculate it again. Right. But the mathematical models, how complex are they and how far in the future can he really look at this point?
SPEAKER_03: Well, his basic equations, which are now kind of known in meteorology as the primitive equations, which I kind of love, his basic equations were right, but he couldn't solve them. He neither had enough observations, especially at different levels of altitude and high up into the atmosphere, nor could he solve the differential equations required to sort of, you know, solve his own equations. He just, he couldn't actually plug the numbers in. So theoretically, he was mostly right. And in fact, the primitive equations are still at the root of the weather models. You know, they're deep in there. They have evolved dramatically, but they're still there. They're still relevant. But practically, he got nowhere. He neither had enough to put into his math, nor was he able to actually calculate what came out.
SPEAKER_04: Yeah. So then people get to imagine these ways to get around this issue of the computation. So a mathematician named Louis Fry Richardson had this crazy idea that I want you to tell us about.
SPEAKER_03: Yeah. You know, so Bjerknes writes his paper in 1904. You know, he says, you know, that we can predict the weather using math and physics. And about ten years later, Louis Fry Richardson, an English mathematician, comes to it and says, well, I think I might actually give this a try. And he actually uses a set of observations that Bjerknes himself had organized the collection of from a single day, you know, above Europe. And he begins this sort of furious six-week process of actually calculating that into a weather forecast. He does it while he's working as an ambulance driver on the Western Front during World War I. He was a Quaker, so he wouldn't fight, but he drove an ambulance. And so he talks about going back to his billet and sort of running the calculations with his slide rule and spending six weeks on this sort of single-afternoon forecast, which famously and spectacularly was wrong, sort of famous errors in meteorology. But he was convinced that if he had better observations and if he had a greater ability to actually make these calculations, you could have a useful forecast. And he comes to the idea that what it would really take would be 64,000 computers, which is to say 64,000 humans, you know, human computers, arranged in a stadium, and there would be a conductor in the middle who would shine a light on them if they were going too fast or too slow, and they would write their calculations and then pass it to the person next to them. And with 64,000 people, you could go fast enough to have a useful weather forecast, which is to say a forecast that is completed before the weather actually arrives. In one day.
SPEAKER_03: I mean, that's the thing. You know, you can have a very detailed forecast, but it's useless if the future comes before your calculations. He also somewhat amazingly predicts, like, the Google campus. He thinks that, like, his 64,000 computers should have, like, ball fields and cafeterias and entertainments and things like that. He also predicts a kind of steampunk aesthetic as well. He describes these offices with, like, you know, levers and desks and things that rise up onto roof decks and basically what Facebook is in Menlo Park today. Yeah. Oh, that's so funny.
SPEAKER_04: So we have these people thinking in these big ways about the weather and how to forecast it, and we have these couple of limitations that they're butting up against. One is computational limitation. The other one is kind of data limitation, like, access to these, measuring these points. So how was weather forecasting moving forward in the rest of the world, and what were they doing to come up with what was going to happen in the future?
SPEAKER_03: When Richardson and Bjerkenes, when their project essentially fails, there's this kind of amazing and pretty successful basically 40-year history of meteorology that actually makes a lot of progress. Weather forecast gets better and useful and helps with early aviation. You know, most famously, you know, the forecast for D-Day was a solid two-day forecast that allowed the Allies to postpone their invasion. It's sort of always pointed out as this kind of forecast that changed the course of history. But none of it had anything to do with these calculations. It's sort of the equivalent of, like, looking at a cloud or a cold front and just seeing it go across the country.
SPEAKER_04: It has not a lot of math in it, but it has a lot of just, like, history and past precedent and stuff that lets you predict what's going to happen in the future.
SPEAKER_03: Yeah, yeah, absolutely. And it wasn't until the post-war era when you have the beginnings of space flight and the beginnings of real computing that the idea of actually functionally creating a weather forecast based on mathematical analysis of the atmosphere becomes possible again.
SPEAKER_04: So after the war, we sort of get into the 50s and 60s, and there's a big breakthrough. So new technologies emerge, and there's the political will to build this whole Earth map and make it really, really good. So tell us what happened in the 60s that makes Dirkness's dream of calculating the weather finally come true. The most important thing is you have this kind of love affair with the Earth, you know, with the Earth as a planet.
SPEAKER_03: You know, you suddenly have this collective societal vision of what the Earth will look like from space. You know, you have all this science fiction. You have the first people orbiting the Earth, and everyone's sort of imagining what it is like to look back. And as soon as you kind of have that in the popular imagination, the idea of a map of the complete atmosphere becomes real.
SPEAKER_02: We go into space because whatever mankind must undertake, free men must fully share.
SPEAKER_03: There's this incredible moment in 1961, right after the Soviets first launched Sputnik, where Kennedy gives a speech where he says, you know, we must put a man on the moon before the decade is out. To provide the funds which are needed to meet the following national goals.
SPEAKER_02: First, I believe that this nation should commit itself to achieving the goal before this decade is out of landing a man on the moon and returning him safely to the Earth.
SPEAKER_03: And that's point number one. And it turns out point number three is $75 million for weather satellites.
SPEAKER_02: Will help give us at the earliest possible time a satellite system for worldwide weather observation. Let it be clear. As familiar as that man on the moon line is, the line about weather satellites comes like 30 seconds later.
SPEAKER_03: And for Kennedy, the global view of this was kind of part of the larger project of the triumph of American ideals around the globe otherwise. So you have this sort of moment where all of the kind of imperial ideals of a kind of American view of the globe and American dominance of the globe become wrapped up in a view of the atmosphere for scientific good, for meteorological good, for what we now think of as this banal project of creating better weather forecasts.
SPEAKER_04: So J.K.'s vision came true in many ways. Throughout the 60s and 70s, a lot of satellites went up into space, both for military surveillance and for weather forecasting. And as the weather machine grew, a worldwide alliance developed between nations. They figured out how to share data and how to maintain the infrastructure that they'd collectively built. The main part of the U.N. that now deals with weather is called the World Meteorological Organization, and they get together every four years to talk about policy. Andrew went to one of these gatherings.
SPEAKER_03: Yeah, in 2015 in Geneva, the World Meteorological Congress is the big event every four years. And it's the world's weather diplomats coming together and sort of methodically kind of hashing through their issues and then breaking for receptions, which is the diplomatic word for party, as it turns out. It's mostly very specific and technical, but the dynamic between the countries that essentially run supercomputers and the countries that don't was increasingly apparent. And not surprisingly, the effects of climate change are sort of more pronounced for less wealthy countries, which is also the countries that don't fly weather satellites and run weather supercomputers. So there was really a sense that they were all in it together, that this was a kind of thing that governments did. And there was a 150-year tradition of governments from around the world, you know, sharing their data with each other, sharing their forecasts with each other. And especially now when storms are more powerful, when the effects of those storms are more pronounced, when there is the sort of growing threat of what will happen with the weather in the future, it was very clear that that cooperation was needed now more than ever. There's this whole notion of the weather machine.
SPEAKER_04: This is this global project. It's carried out by governments. It's done for the public good. But increasingly, private companies are getting into the weather forecasting business. So tell us about that and how this is interacting with the sort of global project that's been going on for decades and decades. Yeah, yeah, well, there has been the assumption, you know, essentially since the birth of satellites and computers, that supercomputers and satellites are things that governments do.
SPEAKER_03: They're too expensive for private companies to do. If you have a weather service, you know, and you need a $30 million computer, that's going to be something that a government buys and it's going to be in service not only to its citizens but to the entire world. But the couple currents are colliding. I mean, one, you have the sort of rise of private space flight. You have the kind of SpaceXes of the world and you have private space observation companies. You have more severe weather and more money at stake to predict that weather. And you have a kind of, you know, rise of the recognition of sort of big data and what we can do with data and how important it is to sort of understand the world using big data. And so you end up now with the idea that private weather forecasting is probably a pretty good business. And so after 150-year tradition of weather forecasting being something that governments do for their citizens, there's now a bit of a gold rush where companies can run their own weather models, can fly their own weather satellites, can collect their own weather observations, and provide a private forecast that is a value that exceeds the usefulness of the publicly available forecasts. And how do you think about that as someone who's seen the long view of the weather machine, it turning towards privatization?
SPEAKER_04: Like what do you think are the complications like now and maybe the complications in the future?
SPEAKER_03: Well, I mean, the first thing that I saw was the real angst among the sort of dyed-in-the-wool government meteorologists over what this meant for the long tradition of government weather services protecting life and property. And that being something that governments do for their citizens. But of course from a technical standpoint, you have the possibility of even better weather forecasts. And so there's certainly a kind of technological thrill with the idea that this could be improved. But it's not hard to recognize the kind of global inequality suddenly appearing in the technology of the weather forecast itself and this real exacerbation of the effects of climate change when you have hurricane forecasts accessible to the rich before they are accessible to the poor. When of course they will affect the most vulnerable more directly. Yeah.
SPEAKER_04: We get to the sort of the crux of this, which is like at this moment being aware of the new extremes when it comes to our climate is more important than ever. We're at this moment where privatization and proprietary data and models could break that apart. And it wouldn't take much is the sort of strange thing.
SPEAKER_03: All the weather observations that are collected by the US government are put kind of right in the global bucket. And in exchange we get all the world's weather observations back. And if for example the National Weather Service decides to buy private satellite observations for one category and that company says no you can't share that and that spigot is turned off. The possibility that other, you know, start with European countries will say well if you're not giving us that data we're not giving you our data. And within two or three days, you know, the entire system falls apart. And it's not as if well we only need observations over the United States for forecasts over the United States. As soon as you're passing three or four days you need that entire global view. And all of the weather models are kind of built on that holistic global view. And so the idea that this is a kind of you know this is within our borders, that this is a kind of local issue, that it isn't entirely international, interdependent is preposterous. And of course it's deep in the kind of global order that the U.S. built up in the second half of the 20th century. You know it is the kind of American ideal of leading the world with technology and cooperation. And at the moment and not only in the Trump era but really over the last 10 years particularly with the kind of new technological dominance of the U.S. And the Googles and Facebooks of the world that the idea of the sort of proprietariness of this data as something that is deep in the heart of our system becomes more consequential in the way that we put together weather forecasts.
SPEAKER_05: Yeah. I think one of the things that's fascinating about all this and all the work that you've done and my thinking on it that has evolved since reading your book is this weird mixing of the idea of weather and knowing the weather being so kind of banal and everyday.
SPEAKER_04: And how much it's about little tiny decisions about whether you bring an umbrella and also about hurricanes. It kind of gets your mind reeling in this very strange way about just like the human desire to know what's coming. Yeah. Yeah. This book took me several years to write.
SPEAKER_03: And in the course of writing it my older child my daughter went from kind of a toddler to like a proper elementary school student. And at the beginning I would be working on this and she would say what's it going to be tomorrow. That would be kind of her last words before going to sleep. She meant like what are we doing. But I would be like oh how do you you know how do you consider the future. You know what does it mean that the sky is coming this way and I'm sort of rooted in place and time and how is this going on. And so I kind of heard it as like you know what's the weather going to be tomorrow. And that sort of contrast between like my watch is going to tell me what the weather is going to be tomorrow and that's just super easy and no worries. And then the existential dread of you know what's it going to be tomorrow was right there with it. It's the most banal thing. You know it is the ultimate small talk. And yet it's also of course the core of our existential planetary dread. And this is in some ways the sort of parable of climate change as well. You know we can be pretty sure about what's going to happen and the ability to change it or to do something about it is completely independent of that foresight.
SPEAKER_04: In other words we have the information we can effectively see into the future. But what we do with that information and how it is used for planning and preparation is up to us. To find out more about Andrew Blum's book The Weather Machine go to 99pi.org. We're going to visit a tiny island in the North Atlantic that is a tiny cog in the gigantic weather machine. After this. The IRC aims to respond within 72 hours after an emergency strikes and they stay as long as they are needed. Some of the IRC's most important work is addressing the inequalities facing women and girls. Ensuring safety from harm, improving health outcomes, increasing access to education, improving economic well-being and ensuring women and girls have the power to influence decisions that affect their lives. Generous people around the world give to the IRC to help families affected by humanitarian crises with emergency supplies. Your generous donation will give the IRC steady reliable support allowing them to continue their ongoing humanitarian efforts even as they respond to emergencies. Donate today by visiting rescue.org slash rebuild. Donate now and help refugee families in need. If you need to design visuals for your brand, you know how important it is to stay on brand. Brands need to use their logos, colors and fonts in order to stay consistent. It's what makes them stand out. The online design platform Canva makes it easy for everyone to stay on brand. With Canva, you can keep your brand's fonts, logos, colors and graphics right where you design presentations, websites, videos and more. Drag and drop your logo into a website design or click to get your social post colors on brand. Create brand templates to give anyone on your team a design head start. You can save time resizing social posts with Canva magic resize. If your company decides to rebrand, replace your logo and other brand imagery across all your designs in just a few clicks. If you're a designer, Canva will save you time on the repetitive tasks. And if you don't have a design resource at your fingertips, just design it yourself. With Canva, you don't need to be a designer to design visuals that stand out and stay on brand. Start designing today at Canva.com, the home for every brand. Do that so you can get out of your negative thought cycles and find some mental and emotional peace. If you're thinking of starting therapy, give BetterHelp a try. It's entirely online, designed to be convenient, flexible and suited to your schedule. Just fill out a brief questionnaire to get matched with a licensed therapist and switch therapists at any time for no additional charge. Get a break from your thoughts with BetterHelp. Visit BetterHelp.com slash invisible today to get 10 percent off your first month. That's BetterHelp. H-E-L-P dot com slash invisible. One of the most fascinating things about the entire system used to protect the weather is how reliant it is on space age satellites orbiting the earth and hundreds of more humble weather stations located on the land. Both technologies are needed to inform our global view. Because the weather machine is so vast and made of so many parts, no one thing exemplifies it all. But I asked Andrew Blum if he could zoom in on one of his favorite places that's essential to the whole data gathering apparatus.
SPEAKER_03: When you try to kind of peel open the weather machine and see what it's made of, you end up with this kind of challenge of choosing a single place to represent all the places, which of course is kind of impossible. It is the nature of places. They are all different. They all occupy a kind of different spot on the map. Partly because of Bjorkness and partly because of this Norwegian meteorological tradition, I latched onto Norway's system of weather observation. And in fact, I fell completely in love with this island called Jan Mayen. That's this arctic island way off, you know, kind of towards Greenland that only has a weather station on it with like an army crew that gets serviced a few times a year and like a couple huskies. And it sounds like this really kind of incredible wild place, which needless to say, you can't go there. Like if you go, you have to like go for three months. So I kind of abandoned that dream of actually visiting this weather station, but found instead a place called Utsira, which is a sort of small island off the coast of Norway. And when I say off the coast of Norway, I mean it's like a 25 minute ferry ride, like, you know, no big deal. It runs a few times a day. But because of its location in the North Sea, it has been an important weather observation point basically for 150 years. And so you have a very early telegraph line there and you have a single spot kind of up on the top of the hill in the center of the island that consistently has been the point where the Norwegian Weather Service has observed the weather. It's a very windy place. Utsira is known for its birding and for its winds. And when you're there, you realize, I realized what it meant for the kind of wind to be rushing by this single point. And I realized that that's kind of what wind is. You know, wind is the passage of the atmosphere past a single spot.
SPEAKER_03: And, you know, that has to then be tied back into the kind of global computational system. You know, you need to sort of send word back to Oslo and Oslo needs to send word back to Frankfurt where the sort of European collector is. And then that gets sent to Virginia and the entire thing kind of gets networked together into typing in, you know, utsira on Google and then the temperature shows up. But all of those things have to fit together and that system has to be deliberately designed. And the kind of design of that system goes back to the middle of the 19th century with the sort of first recognition that not only was it useful to know what the weather was in other places, but it was suddenly technologically possible to get that news pretty speedily. Right. And it's gathered by a human or tended to by a human, you know.
SPEAKER_04: It's tended to by a human. Yeah, he runs the restaurant and he does the weather observations.
SPEAKER_03: So it's four times a day. He goes on his back stoop and he has a cigarette and he kind of looks at the sky. And then he goes to his computer and he logs in and he in the kind of Norwegian weather services dropdown menus, he sort of does a qualitative analysis of what the clouds are according to the sort of rules that he's been taught. And that gets then sort of put in the whole way. And the same thing happens in every airport in the country. Every major airport has a has a round the clock weather observer. Some some person who's like in an office somewhere on the grounds of the airport who, you know, once an hour is checking the observations that the automated system has made to make sure the system is working. And if the clouds are slightly different than the the cilium or the cloud, the cloud observing machine can read to correct those.
SPEAKER_04: Andrew Plum is the author of The Weather Machine, a journey inside the forecast.
SPEAKER_04: Ninety nine percent invisible was produced this week by Delaney Hall mix and tech production by Sharif Yousif music by Sean Real. Our senior producer is Katie Mingle. Kurt Kohlstedt is the digital director. The rest of the team is Emmett Fitzgerald, Vivian Lay, Joe Rosenberg, Chris Berube, Avery Truffleman, Sophia Klutzker and me, Roman Mars. We are a project of 91.7 KOW in San Francisco and produced on Radio Row in beautiful downtown Oakland, California. Ninety nine percent invisible is a member of radio topia from PRX, a fiercely independent collective of the most innovative shows in all of podcasting. Find them all at radio topia. FM. You can find the show and join discussions about the show on Facebook. You can tweet at me at Roman Mars and the show at 99 PI or on Instagram and Reddit, too. But we should really talk about the weather and 99 PI dot org radio.
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