Following the weather so first is getting weirder and wilder and greater extremes and second the forecaster is better at predicting what will get us. But their accuracy has definitely improved and so has the timeliness of their reports. These days not only one weather model but those simulating the future space of the atmosphere the north american model, european model and those over the next ten days. And then to get interested in this and then supercomputers with a knack of making complex systems accessible and he saw a similar kind of story. His new book, the weather machine is an engaging book behind the scenes International Collaborative effort to recount the forecasting to the Un World Meteorological Organization with a satellite in supercomputers to make up the conversation with one of the forecasters the editor of Washington Post in those fascinated by the weather growing up in the dc region and to recall this for year the chief meteorologist from the local nbc affiliate to study Atmospheric Science with Climate Change and 15 years ago establish capital weather. Com the first weather blog on the internet. And jason and his gang are now with anyone who was interested in whether of the dc area. So please join me to welcome andrew and jason. [a thank you for the introduction i really want to come back. And then and then definitely had a busy day. And when we first started the process several years ago i went to the meeting of the American Meteorological Society and knew that i wanted to write about this topic trying to figure out the meteorologist in one place is a great starting point how to put it together but i didnt realize was that there was a Journalism Community and when i was there i was warmly embraced and invited out to dinner with about 25 people. The American Weather press corps. So its great to go full circle. And then we will open for questions. The first time i ever took in uber was from the meteorological society. So as preparation for this event i had to read the book but it was a joy i found myself smiling like youre watching a great concert and smiles comes across your face. And how powerful the performances. And with those narratives and to earn my high recommendation so lets get started with q a. And then what made you decide to write a book about Weather Forecasting quick. And then my background is writing about architecture and you cannot write about places without thinking about the weather. And it is that there is a constant challenge did you forget your umbrella and my dress properly for the day and to be dealing with the weather professionally on a daily basis to switch registered to from the catastrophic is the biggest challenge and that stuck me for a while. So wanting to write something about the weather but Hurricane Sandy in 2012 which and for a lot of us suddenly there was a public conversation about the model and with the eight day forecast on a sunday afternoon the first inkling for sandy which arrived in new york city the following monday night. For what we are capable of in terms of their ability and the more manual designation of data. Clearly they have those systems that are astonishing and far exceeding my understanding of how they worked. But what are the weather models and how do they work . And incredible black box sated that type of infrastructure story got me going to recognize if i could just figure out and understand in a way to tell a story about them that is a stephanie to be told there. I may have underestimated their complexity because there is a very small pool of people who work on them and improve them and the entry to recognize is significant but to check the box is important to me some of my first book of the internet it is incredibly complex system we carry with our mind in our pocket is really a black box with the story that i wanted to tell. Of course you cannot tell that without going back in time with history. Thats a way that i approach that. We will talk about the history a little bit and the scientist in the 18 hundreds to lay the foundation for modern day numerical prediction there were scientists in england and norway and with those contributors. Wind speeds and weather maps and then theres this other history of mathematicians and when i started to try to think about how to tell this other history it felt like distinct from a lot of the existing history. It very much begins with a norwegian meteorologist ait was amazing because he occupies both histories. He came up with the idea in the 20th 19 century turn of the 20th century. 1904 was his main paper to calculate the weather. To use the equations of physic to describe what the atmosphere would do next. With the main insight that each day calculations could be its own hypothesis. If you could calculate the weather you can prove the next day whether calculations were right or wrong and then we find those calculations on a daily basis which is this improvement thats gotten us to this incredible place we are today. I feel like i should lay out that incredible place. To say the meteorologists love to talk about a day a decade which is to say the models in the forecast have improved by a day each decade over the last 40 years. Five day forecast today is as good as a four day forecast 10 years ago or today forecast 30 years ago. With not just diminishing increasing. The talk at the moment is to week forecast by 2025 for extreme events. So this improvement goes back to gerkins his ideas saying we can calculate the weather each days forecast is its own science experiment and you can try to get the next day. Then he couldnt calculate the weather of course. Realized he would need 64,000 computers which is 64,000 people who he thought could be arranged in a stadium. And they could each get the square of corresponding atmosphere and that square they would do that calculations and pass them up to the front on a navy that would work to actually calculate the weather fast enough for useful production. You cant just calculate the weather it has to be done before the weather comes or else its not useful. I think that inability to calculate the lack of observation the lack of computer to calculate them was essentially meant this idea from 1904 had to wait called 50 years until computers and satellite began to come in. And nearly and another 50 years the last 30 years for the weather models to be useful beyond the human scale, not just as guidance but really to exceed the capabilities of human meteorologist to the point that now yes there is a human check but you wouldnt find its hard to find meteorologist who will still say they dont work although i found one. Its remarkable how good the Weather Forecasting models are today. The trillions of calculations per second its amazing. One of the critical moments in the American Weather prediction we fast forward to the 1950s and 60s you alluded to this already the Weather Satellites. Talk about history of Weather Satellites and how they played such an integral role in the developmental forecast and some of the major discoveries and breakthroughs with that technology. I think the key idea that i fell in love with early was that for longer range forecast for two and three and i think beyond the couple days you need a global view. It cant just be you not just looking at the weather in north america you are talking about the weather globally to look at the entire global atmosphere. For global view you need global instrument. Its not really until satellites arrived in the 60s he began to have the first inklings of that. Its also amazes me that the satellites the month for week of apollo. They come out of the same conjoined civilian scientific military effort that you have no satellites without the dollars spent for the missile race you have no Weather Satellites without the dollars spent for surveillance satellite and the sort of scientific ideas and the military ideas are handinhand until quite notably until kennedy. Theres the moonshot speaks the spring 1961 speech 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. Its amazing to me that you have this basic impetus for global view in the same speech as the moonshot speech and the most famous infrastructure speech. Then you have it rooted in the idea of International Collaboration that kennedy left the weather because it was a point of cooperation and sure enough for students to speech in a later speech in the fall at the un the Nuclear Annihilation speech the answer that kennedy proposed for togetherness and alternative for peace was whats cooperation on weather observation. He says cooperation in weather observation and control the control got left behind. Although not if you asked some people. But the idea that from the very beginning it was about the diplomatic collaboration between meteorologists from every country in order to make mobile data auto Global Infrastructure to eventually support global models kind of gives this route of cooperation that begins in the 19th century but its current incarnation was very much inspired by kennedys idea of a global vision. Thats continues today. Somewhat quietly i dont think we often look beyond the American Weather service but everything depends on the global pool of data. Absolutely. Clearly the data is so critical to todays weather models whether you are talking about the weather balloon data talking about groundbased centers and you talk about Weather Satellites. Weather satellites are superexpensive cost governments billions of dollars but without them our forecasts would not be where they are. Obviously the Weather Satellite data observations from groundbased sensors weather balloons they feed these models. He went to Different Centers to learn more about what the models the National Center for Atmospheric Research and boulder and the European Center for forecast. And i did go to the national Weather Service but i didnt put it in the book. There you go. Talk to us a little bit about your expenses visiting these centers and the appreciation you gain for these models you touched on it a little bit of material little bit 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 Forecast over time. I think the competition between the american model in european model is short had but it was amazing and visiting both places as a journalist the cleaner and looking for cleaner stories for more legible stories and its amazing to me always that cleaner stories come from cleaner places that the places that sort of have a coherent organization and that have a very focused Mission Statement are much easier to describe and write about and often i find more successful because of that. We weather model the fact that we sort of take the starting point there is this weather model war on european model is the best to go visit the source of that the European Center for Weather Forecast outside of london and redding ended collaboration funded by 32 European Countries that are contributing sending both scientists and money with the singular goal of running the best global model. They do it by combining the Research People and the model operation people in a single building in this amazing cafeteria to become a bit of a clichc for tech culture but at uc mwf i couldnt believe anyone got any work done because the cafeteria was always full. They had the most beautiful machines. [laughter] 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 not just in daily internal wiki of comments on this is weird why is this doing this then codified with weekly meetings and quarterly meetings which i observed to note about. The sort of constant thing about what is the model doing how can be doing it better i think the key point is that when you say talk about the weather model its not about a meatgrinder with the weather but its really about having an ongoing simulation of the atmosphere that every six hours every 12 hours is compared to the most recent observation the real atmosphere and then corrected slightly to better match that. That sort of do act of the assimilated atmosphere in the real earth clicking Forward Together with the assimilated earth running faster in time to give us what we now call forecast. Makes you realize that to make the forecast better begins to make the simulation better. Not just in some certainly not the statistical improvement based on past weather its more about actually using these equations to stimulate the atmosphere in a way that is close enough to reality that it actually can then when its run forward when it is running forward faster in time it spits out the weather of the future. And to see how eager the people at the European Center were to make sure they were getting it right which isnt just to say they were getting the forecast right but to say that the simulation they were building most closely resembled the real atmosphere for all the right reasons. But the actual physics match not that it was just getting lucky repeatedly. And thats not machine learning. Its not the kind of predictive problem in the way we think of elections or other sort of baseball or other predictive problems. Its unique and uniquely successful. This is something we all use every single day. And its mostly right. Can i do that answer your culture question i was gonna say did you find they were competitive that they wanted to beat the other Modeling Centers around the world. Thats all they talked about. When you say why are you doing this . They say we want to be the best. Theres a lot of theres an ongoing discussion about this modeling competition and we were talking before. Theres a sense that it keeps everyone a fire that keeps every improving their model faster. But there is a sense that they need to do it the u. S. Models are sort of convoluted by having to serve different masters in different models everyone says, we run 12 models and they only run one. I think while that is true the singular focus on this 10 day simulation of the atmosphere makes the collaboration in their competitiveness very productive. And much more of a streamlined process. Obviously we talked a lot about how great Weather Forecasts are. Theres a saying you are Weather Forecasts can be 100 accurate but if people make their own decision based on accurate forecast, forecast is useless. That was a big, when i began to understand that difference of what makes a good forecast. How does the forecast informed decisionmaking and does the forecaster provide the enduser the information they need so that if theres a wedding reception coming up they are going to for example have a tent or not have a tent to keep their guests drive. You talk about that decisionsupport aspect in your book. Do you think Weather Forecasting centers both in the european aare they starting to gain a better appreciation of the importance of the social science connecting the physical science that the forecast with the decision . I think its actually the place where the American Weather not Just NationalWeather Service but broader enterprise some of the folks call it is really excelling is these new links between the forecast and tactical sense and the decisions you make based on it. I think ai write about a guy tim palmer at oxford in the European Center he tells an amazing story about its not as simple as is it going to rain is a knock in the rain . Its how sure are you and what decisions can be based on it if you having a party and a picnic and the queen is coming 20 chance is enough to order a tent but if its just your friends an 80 chance might not be enough to order a tent. If that sort of sense of whats the use of a better forecast if it doesnt help our decisions think thats reasonable with the daytoday forecast because it was clear it was going to rain monday morning in dc from four days ago it wasnt clear how it was going to rain we were talking before what point this morning at what point it seems like things were getting intense and then even more significantly what decisions would people have made differently had the days forecast been clear. I think that idea that you can strive technically for a perfect forecast but if it doesnt help you make decisions, thats where meteorologists and others have acknowledged they are right but the ball is out of your court. But its all the way out of your court if you recognize the technical superiority and the technical achievement of the forecast itself. But you still get angry emails. For sure. I think Weather Forecasts have come a long way and we are really good at capturing what we call synoptic scale weather systems. These are largescale systems but when it comes down to forecasting individual thunderstorms this is what we had this morning models are still just developing in that area we have what we call convect