And wilder with bigger storms, hotter and more freezing temperatures and greater extremes at seemingly all times of the year. And second, that forecasters are Getting Better at predicting whats about to hit us. They still dont get it right 100 of the time, of course, but their act rahs is city has definitely accuracy has definitely improved and so has the timelessness of their reports. In fact, these days were aware not only of one weather model, but of multiple ones simulating the future space of the atmosphere. Theres a north american model, the european model, the global one and a number of others, and theyre forecasting not todays weather or tomorrows, but weather over the next ten days and beyond. Andrew blum got interested in this stuff. He wasnt satisfied with the past explanations that attributed the advances in weather science simply to faster supercomputer ands better satellites. Andrews a journalist with a knack for making complex systems accessible as he did in his previous book which was a primer on the physical infrastructure of the internet. And he saw in Weather Forecasts a similar kind of story. His new book, the weather machine, is an engaging look at what goes on behind the scenes. The international, collaborative effort that it takes to give us the daily weather report. Andrew recounts how forecasting has evolved from scattered stations to the u. N. s World Meteorological organization, and he introduces readers to the scientists, satellites and supercomputers that make up the worlds current forecasting system. Andrew will be in conversation here this evening with one forecasters, jason. Hes the weather editor at the Washington Post and chief meteorologist of the capital weather game. Jason himself has been fascinated by the weather since his days growing up in the d. C. Region. As a high school student, he interned with bob ryan who at least some of you, no doubt, will recall was for years the chief meteorologist for the local nbc affiliate. Jason went on to study Atmospheric Science in college and graduate school, then worked as a Climate Change analyst at the epa. And 15 years ago established capital weather. Com, the first professional weather blog on the internet. Ing the Washington Post absorbed the blog in 2008, and jason and his gang are now essential reading for anyone whos interested in the weather in the d. C. Area. So, ladies and gentlemen, please join me in welcoming both andrew and jason. [applause] hello. Thank you all for coming. Brad, thank you for the great introduction. I was here not here, on connecticut avenue, and really wanted to come back with a new book. I was a little nervous on the train this morning when washington was washing away [laughter] as jason definitely had a busy day. I was also particularly pleased that jason agreed to be my interlocutor tonight. We met when i first started this project several years ago. I went to meeting of the American Meteorological Society in atlanta, and sort of knew that i wanted to write about this topic and was trying to figure out what the shape might be. And having all of americas or a lot of the world meteorologists in one place was definitely a great starting point to figure out how it fit together. What i didnt realize was that there was a weather journalism community, and the second that i was there was sort of formally embraced and invited out to dinner with about, how many . About 25 people. Yeah. Sort of the American Press corps of which jason [laughter] i think a fair count. But it was a big help for me starting out, so its great to come full circle to have jason here tonight to do that. So were going to talk for about a half an hour, then open up for questions, and ill pass it off to you. Sounds great. Well, its a pleasure to be here tonight, and a funny story is that the first time i ever took an uber was with andrew [laughter] from the American Meteorological Society annual meeting in atlanta to airport back in 2014. That was the i wasnt going to say the year, but, okay. [laughter] yeah. So five years ago. Anyways, i, as preparation for this event, i did have to read the book, but i have to say it was a joy. I frequently found myself if smiling, like i was sometimes youre watching a great p concert, youre watching a great singer and, you know, a smile just comes across your face because youre moved by the, how powerful the performance is. And the writing with is really elegant, lots of excellent narratives and anecdotes. So it definitely earns my high recommendation. Anyway, so lets get started with the q a. Lets begin with the motivation for the book and what made you sit down and decide all of a sudden that you wanted to write a book about the history of Weather Forecasting. Yeah. There are a few different threads, which we have time to go into tonight. The longer answer. For my my background is mostly writing about architecture, writing about places. And you cant write about maces without thinking about places without thinking about the weather. But weather, it turns out, is very hard to write about especially if youre not a meteorologist or atmospheric scientist. The words kind of slip away, and theres this constant challenge between the banal, you know, did you forget your umbrella are, you know, am i blessed proper dressed properly for the day and the catastrophic. And i think its that combination to be a meteorologist and to write about the weather and to be dealing with the weather professionally in any daily basis, being able to switch registers from, you know, from the cheery to catastrophic, i think, is one of the Biggest Challenges and sort of had stuck me for a while. Kind of what unstuck me, knowing i always kind of wanted to write something about the weather was Hurricane Sandy in 2012 which was the moment where i think for a lot of us the weather models revealed themselves. You know, there was suddenly a sort of public conversation about the American Weather model can and the european weather model. Not only that, there was this astonishing forecast, an eightday forecast. Sunday afternoon was the first inkling for sandy, which arrived in new york city the following monday night. And that exceeded all my understanding of what meteorologists were capable of in terms of their human ability, in terms of their own sort of pattern recognition and more manual assimilation of data. Clearly, they had built systems that were astonishing and had far exceeded my understanding of how they worked, and yet to see the sort of, this question of, okay, weather models and how do they work was very hard to answer. It was an incredible black box, and that type of, that type of complex infrastructure story was really what got me going to sort of recognize that if i could figure out how these models worked, if i could understand them in a way to tell a story about them, that felt meaningful. That felt like definitely there was a story to be told there. I might have underestimated their complexity. Does anyone here work in weather models . No . No professional weather modelists . Okay, phew. [laughter] i think i might have underestimated their complexity because theres a very small pool of people in the world who really work on them and improve them. And they, the sort of barrier to entry to recognize what their parts and pieces were was significant. But it even, it sort of checked the box that was important to me of, frankly, its banal the city, this system that bay banality, the idea of the internet, this incredibly complex global system that we carry around in our pocket and yet is really a a black box was definitely a story i wanted to tell. And, of course, you cant tell it without going back in time to some of the history and how it developed. That was really the way that i approached that. Yeah. So lets talk about the history a little bit and some of those pioneering scientists in the 1800s who sort of laid the foundation for modern day numerical weather prediction. There were scientists in england and in norway who you talk about in your book. Tell us a bit about some of those early contributors and how important the work they did was to the advancements weve seen in weather prediction today. Its funny, theres kind of two histories of weather. Theres the history of the sort of Storm Chasers and the watching the sky and, you know, the sort of this kind of heroic stories of wind speeds and, you know, weather maps and all that. And then theres this other history of mathematicians. And its when i started to try to think about how to tell this other history, it really felt quite distinct from a lot of the other history. It very much begins with an original meteorologist who was kind of amazing because he occupied both histories. He came up with the idea at the turn of the 19th century, turn of the 20th century, i should say 1904 was his main paper to calculate the weather, to use the equations of physics and thermodynamics to actually describe what the atmosphere would do next. With the main insight that each days calculation could be itself a kind of hypothesis. And if you could calculate the weather, you could prove the next day whether your calculations were right or wrong and then rethose calculations on a daily basis, which is this process of improvement that has gotten us to this incredible place were at today. I feel like i should sort of lay out that incredible place. Bradley sort of framed it, but to say that the meteorologist talks about a day a decade, which is to say that the models, the forecasts have improved by a day each decade or, basically, over the last 40 years. A fiveday forecast as good as a fourday forecast ten years ago. Not that that rate is diminishing, its increasing. The talk at the moment is of a two week forecast by 2025 for extreme events. So this improvement really goes back to idea of saying, okay, if you can calculate the weather, then each days forecast is its own sort of science experiment, and you can try it again the next day. But then he couldnt calculate the weather, of course. There was a famous mathematician who tried to calculate the weather, realized he would need 64,000 computers, which is 64,000 people who he thought could be arranged in a a stadium, and they could each get, you know, their square of corresponding atmosphere, and that square they would do the calculations and sort of pass them up to front, and maybe that would work to actually calculate the weather fast enough for a useful prediction. Because, of course, you cant just calculate the weather, it has to be done before the weather comes, otherwise its not useful. So i think that inability to calculate, the lack of observations, the lack of a computer to calculate them was, its actually meant that the ideas of 1904 had to wait 60 years until computers and then satellites began to come in. And it had to wait nearly another 50 years, just to really the last 30 years, for the weather models to be useful beyond the human scale. Not just guidance, but really to exceed the capability of human meteorologists to point that now, i mean, i you wouldnt find yes, theres a sort of human check on it, but its hard to find meteorologists who will still say they dont work. Although i found one. [laughter] its remarkable how good the Weather Forecasting models are. They do trillions of calculations per second. Its amazing. One of the critical developments in the American Weather prediction, we fast forward to 1950s and 60s, and you alluded to this already, was weather9 satellites. Yeah. Talk a little bit about the history of Weather Satellites and how theyve played such an integral role in the development of forecasts and some of the sort of major discoveries and breakthroughs with that technology. I think that the key, the idea that i fell in love with really early was that for longer range forecasts, for, you know, two and three and four i think beyond a couple days you need a global view. It cant just be youre not just looking at the weather in north america, youre really talking about the weather globally, to look at the entire global fire. Atmosphere. You need a global instrument. Its it also amazes me that the satellites, i mean, the sort of month of apollo, the week of apollo, but they come out of the same conjoined sort of civilian scientific and military efforts that you have no satellites without the dollars spent for the missell race missile race, you have no Weather Satellites without the dollar spent for surveillance satellites. And the sort of two the scientific ideas and the military ideas are kind of hand in hand. Until, quite notably, until kennedy. Theres the moon shot speech, the spring 1961 speech, you know, that we put a man on the moon before the decade is out, that was bullet point number one. Bullet point number two was Nuclear Rockets for deep space travel. Point number three was communication satellites, and point number four was Weather Satellites. And its just amazing to me that you have the sort of basic impetus for a global view in the same speech as the moon shot speech and the sort of most famous infrastructure speech. And then you have it baylesed, rooted in the based, rooted in the idea of international cooperation. Kennedy liked the weather because it was a point of cooperation. And sure enough, as soon as that speech and a later speech in the fall at the u. N. , the sort of Nuclear Annihilation speech, the sort of answer that kennedy proposed for togetherness, for an they were for peace was an alternative for peace was cooperation on weather observation and control. The control part got left behind, although not to some people. But the, but that idea that from the very beginning it was about diplomatic collaboration between meteorologists from every country in order to make global data out of Global Infrastructure to eventually support global models kind of gives it its roots of cooperation that begins the 19th century. But its current incarnation was very much inspired by sort of kennedys idea of a global vision. And thats pretty, that continues today. Somewhat quietly, and i think we dont, we often dont look beyond the sort of American Weather service, but everything depends on this global pool of data. Absolutely. And so, i mean, clearly the data is so critical to todays weather models, whether youre talking about the weather balloon data, youre talking about groundbased sensors and, coffining, you just talked and, of course, you just talked about Weather Satellites. Weather satellites are super expensive, cost governments billions of dollars. But without them, our forecasts would not be where they are. So, obviously, the Weather Satellite data, the observations from groundbased sensors, weather balloons, they feed these models. And you went to two Different Centers to learn more about weather models. You went to National Center for Atmospheric Research in boulder, and you went to European Center for mediumrange and i did go to National Weather service, but i didnt put it in the book. [laughter] okay. There you go. Talk to us about your experiences visiting these centers and the appreciation you gained for these models. Touched on this a little bit, but lets hear more in depth about what makes these models work, what amount of intellect is required to run these models, who are the people who are doing this work . And how have they been able to be so successful in improving Weather Forecasts over time . Yeah. The i mean, i think this competition between the american model and the european model is sort of shorthand for it, but it was amazing in visiting both places, i mean, as a journalist the kind of cleaner, i mean, looking for cleaner stories, for more legible stories, and its amazing to me always that cleaner stories come from cleaner places. You know, the places that sort of have a coherent organization and that have a very focused Mission Statement are much easier to describe and to write about and are often, i find, more successful because of that. So with weather models, the fact that we sort of take the starting point that, okay, theres this weather model war and the european model is the best, to see to go visit the source of that, the European Center for mediumrange Weather Forecasts which is a collaboration funded by, i think its 32 yeah, 32 European Countries that are contributing, sending both scientists and money with the singular goal of running the best Global Weather model. And they do it by combining the Research People and the weather, the model operations people in a single building and in this amazing cafeteria calf tiers have become a bit of a chi they in tech cliche in tech culture. I couldnt believe that anyone got any work done, because the cafeteria was always full, and they had the most beautiful coffee machine. [laughter] but they, that constant, day by day effort to consider what the model was doing, what it was spitting out and how it could be improved as a system was really tangible. Where its built in, you know, not just in daily sort of internal wiki of comments on this is weird, why is it doing this, then codified with weekly meetings and then quarterly meetings, one of which i observed and wrote about. The sort of, okay, what is the model doing and how can it be doing it better. But i think the key point is when you talk about the weather mold, its not about, you know, a sort of exiewmp computational meat grinder, but its really about having an ongoing similar ration of the atmosphere that every six hours, twelve hours is compared to the real atmosphere and then corrected slightly to better match that. And thats sort of, you know, that sort of duet of the simi