Transcripts For CSPAN2 Andrew Blum The Weather Machine 20240714

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 National Weather 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 convection allowing volatiles which try to get thunderstorms small scale weather features correct and that you can only do sometimes within a couple hours. Even at 5 00 a. M. 6 00 a. M. This morning it wasnt clear that that complex of thunderstorms was going to light up and then track straight to the dt dc area and unleash the event. There still progress we need to make even as the forecast of gun better each decade as you spoke about its really localized fine scale forecasts where theres a lot of progress where i think we just dont make which i think was a good segue to my next question was the importance of observation because in all models they require observations and weve talked about all the different types of observations which are needed for a robust numerical weather Production System but there are can some concerns right now in the larger Public Private International Weather community about where we will be collecting data in the future there are a lot more new data sources coming online private Companies Launching Weather Satellites which want to sell the data rather than making them free you have Remote Sensing systems on automobiles and different modes of transportation you have cell phones in your pocket collecting data who owns the data. How is the data then sold to the government . Talk a little bit about this issue and its coming up in the one meter elko organizations as a phony issue as to historically weather data has been an International Partnership among governments but now you are introducing the private sector which is a profit motive into this enterprise. How do you deal with that . Talk a little bit about how your book addresses that. This is an exciting topic for me because it was something that i realized the folks who were involved in the daytoday of forecasting in the u. S. In particular because the System International system worked so well it operated very quietly thats what somebody a woman who was former chief scientist to the australian Weather Service said we havent been a squeaky wheel ever. Our collaboration of exchanging weather observations all over the world when them together sending them back out all over the world has worked so well we flown under the radar and people perhaps dont appreciate how essential that is. I think that is the peace the fact that it isnt recognized i think is becomes a cause for concern. When you have these new kinds of weathers observations. And in particular with new weather observations that are no longer after 150 years of meteorology being something done most by governments and web server observations weather stations being operated both satellites operated mostly by governments you have a sort of shift toward private companies observations. The tradition always has been that the governor Meteorology Office share their data and get lots of data back. The more recent evolution is that you have private Satellite Companies essentially offering data as subscription and the question is if they sell it to one government cannot government then share with every other government. Which is a challenging Business Model if you are running a satellite company. Obviously you want to sell your data to as many people as possible. The flipside is that if you cant sell the data to other government, if you cant share the data with other governments then you have a risk of in fracturing the entire system where this exchange is shut off and you end up with fewer observations or at best less improvement because you have all these new observation streams that are no longer part of the global pool of data and no longer incorporated to the global models as part of a Global Infrastructure offering global forecast. That is a challenging place to be its a real shift particularly with the bigger box involved with cheaper satellites with more money at risk or more money to be made with weather extremes so if before it was sort of unheardof that a private company would we run flights on Weather Satellites or spend 20 million on its own weather supercomputer model now those dollar value start to seem more reasonable because of this combination of greater climate risk. And more capabilities. The shift would be its no longer about a global pool of data that Companies Like accuweather taking the data for better forecast but instead about fragmentation of new kinds of data thats not been shared. Its uncharted territory and i think it is something that a lot of the weather diplomats the folks who are the representatives in the Meteorological Organization are thinking hard about and its something that the Current Administration has been very eager to push to make sure that these new companies are able to be profitable. That is the emphasis and is not a unique emphasis but its not a unique desire but its a unique emphasis. Its a balance has shifted to say we want to make sure the new companies can blossom and its not clear what the stakes are for that for the Global Data Exchange this 150 year tradition of meteorological data as a Global Public good. Its coming. The sort of combination of factors. Its very under the radar. Its interesting because there could be a day where ibm for example has better Weather Forecast and the national Weather Service. Like today. They are developing their own model. They got brilliant scientists who can create do their own supercomputing and then they can sell that information. Weather forecasting, which Weather Forecasts have historically been a public good now all the sudden if you want best information rather than automatically getting it you may have to pay for it. Theres a potential that the publicly provided forecast could become inferior unless the Weather Service develops partnerships with these private companies in a way which is taken broker agreements. If you did, the reality is if it were not for the predominantly satellite date of the European Consortium that runs the european satellites and Weather Satellites that contribute the lion share of data not just the pretty pictures we are used to from the strand satellites but a lot of the numerical data that comes from a polar opening satellites. When you think about the contribution and billions of dollars b all boat for global meteorology. If that exchange stops then you would have at most 10 or a dozen countries that would be able to pay for weather data. Is 150 year tradition. It does raise questions. To see this sort of shift from public good to commodity if you have a question past the mic and. You spoke in some regards why we should care about having more longer and accurate forecasts. I was wondering if you could do that with regard to disaster preparation so how much does it help the government to know that a hurricane is going to come two weeks in advance as opposed to one week in advance. I think you see these moments where not just a storm was in the forecast for days before or three days before in time to make a decision based on it but that because the forecast was so consistent for so long the confidence in making decisions for the forecast was greater. The amazing recent example was from cyclone fanny india early may very similar storms than 20 years ago were tens of thousands of people were killed this time around not just a longerrange forecast i think the forecast was several days out but the confidence in the forecast to be able to evacuate a Million People was very clear. So the idea you have a high impact event with two weeks morning if that forecast is reliable and you have a weeks warning the counterexample the spring for fanny was in bergen beak. Ive also think the dissemination system and the way of were getting the word out to the public and the Warning Systems are not as sophisticated as they are in india because india has a lot of experience with tropical cyclones having dealt with them repeatedly over the years. Theyve learned from their experience to see absolute devastations. For hurricanes obviously having a lot of lead time is incredibly value in our check forecast has gotten so much better. Compared to where they were in the 1970s we can really pinpoint the track of a hurricane within 24 to 48 hours. With the good dear deal of specificity. Whats interesting is with tornadoes is actually been research which has shown tornadoes you give people too much lead time it can make worse decisions so the sweet spot for tornadoes might be 14 to 25 minutes. So people know ive got to do something right now because you give them two hours they can make bad decisions maybe they want to decide they want to wait for the last few minutes. There is interesting social Science Research going into it. Bridging the gap between the forecast and peoples decisions. The example of the spring with the tornadoes in ohio and missouri and kansas where it was a major tornadoes in populated areas. It was a real victory for the national Weather Service going back to the joplin tornado. These are these moments where its not just about the duration of the forecast but the fact that with duration comes confidence. You kind of touched on this a bit about serving different masters but why is it that the european model is different than the american model then maybe what is better is physicist aphysics is physics. What is different . Thats a good question. Its an interesting way, i think that the basic the answer is in the limitations of the model which is to say that the resolution the model is not a molecule to molecule assimilation of the atmosphere so theres a lot of approximations made. I think a lot of the differences in those approximations with a given set of when they are happening but i think the way that what i was surprised by buses the importance of the lighting up of the observed weather and assimilated weather this process is the date assimilation. And how challenging it is to take the data youve collected and actually find the right time time and model scale in place and model scale to insert the data and make it light up. A lot of the advantage of the european model comes from the date assimilation scheme they call for the bar and the woman now the director was her graduate research that started this particular way of lighting up and correcting the weather inside the model but the observed weather from outside. That sort of ability to constantly check both the way the model is putting the model back on course which each step in time the differences between the models arent that great. For years the european model has been the most accurate in the world. I tell people if i only had time to look at one model only had access to one model i would pick the european model. Its not the best buy a lot. Its not the best in every situation. One of the jobs of a forecaster one of the things they have to become skillful at is understanding the biases in the model and when to use model in one situation. There are times the american model has better forecast than the american model. Theres been hurricanes were the american model has better tracked forecast. Sometimes winter storms the american model has a better forecast for snow in the midatlantic. So as a forecaster you have to look at the universal model collectively theres not just european and american theres canadian theres uk model there are models in japan and other international is. You look at them all be called an ensemble as such. You try to look at where they have things in common . What are they all forecast and the like where are the differences . Then you make a forecast and try to communicate the uncertainty based on where the models disagree. I like to think about how powerful they become is that the models are higher resolution than reality, which is to say that we can say with the given conditions are far more places from the model that we actually observe them. The models are where all the data is. The actual observed weather is just a very small portion of the amount of detail the models are presenting. Its a strange thing that the model is more has higher resolution than reality. Im curious if theres any bottlenecks in the pipeline to make improvements. For my Academic Field there is ton of researchers not a lot of funding can you see a lot of improvement coming from just money or do you need more graduate students doing research . Where can most improvements be made . One of the things striking to me is the shift thats happening in meteorology. Benefits really become about Software Design. I think the task of improving the models is a somewhat different skill set than the traditional meteorological training. When you see all the action and the improvement in the system but its not clear to me if american meteorology programs are have gotten sense of that and as so many other things because the same abbecause the sole set of the Software Design and data science is the kind of broader term because there are so much poll on that for private sector for Silicon Valley i think that was also a bit of a drag as well. Does that mention . Obviously i was talking to neil jacobs the acting administrator and he emphasized the need for them to have obviously a strong cast of computer scientists on Board Software engineers as they continue to try to improve the american modeling system. Clearly you need that. You need physical scientists i think every part of the modeling system relies on observations and data assimilation to keep improving that steve got to keep adding observations to the system and making sure the observations are high quality the model physics which is what the physical scientists work on you need them involved in that and testing the model finding the where the model is not working correctly Publishing Research on how to properly represent certain process in the atmosphere and moving the research into operations which is actually this whole Research Operations question the European Center has been ab its been far superior to the u. S. Approach. Thats one of the reasons people who study the issue have concluded the European Center model superiors because they have better collaborations and Better Research to operations processes in place and they spent a lot more time and effort on the research. I think neil jacobs whos running miller right now recognizes that and is trying to beef up the Research Operations. So they can continue to make progress there. I would say id be a little more critical of that while there is talk of improving with the new center stemming in the right direction the institutional drag is enormous. Just the entire structure of the american modeling system its getting convoluted over the years and you look at the European Center in the uk office the other national Weather Service you recognize what we dont have at the moment from a bureaucratic standpoint thats not the kind of thing that funding for new supercomputer solves ann wyatt think that the first effort the new project called epic is a step but a small step. The motivations behind epic the new modeling initiative in the u. S. Is to move the american modeling system into the cloud. And allow researchers at universities to run the model in parallel and test things out and then send it improvements and identify errors and send them back to the Software Engineers within this new Modeling Center so they can over time in cycles improve the model. Time will tell whether it successful. They are working on it. Its one of the key priorities at no under the Trump Administration is to get the american model at least to the level of the european model. Thats a goal whether they can accomplish it in a year and and a half or five years and and a half depending on what happens we will see. Im not sold. [laughter] question about the dissemination of information like forecasts in general. Getting the blip on the phone this morning regarding the flash flooding and basically do you see it moving just toward that model completely are things abi googled the old 9361212 and problem article you wrote like five years ago how they were revitalizing that. I dont know it fell by the wayside or is something that still goes on or even local Weather Forecast on your channel 7 news is that falling to the wayside or we moving to Something Different . You talk about the technologies consumers use to get Weather Forecasts now. I think increasingly people overwhelmingly are receiving Weather Information on their mobile devices. Whether talking about a Smart Phone App or the mobile web android or our aiphone. I think thats one of the reasons we been successful. Our weather team, we been digital first. Since we started in terms of providing an interactive platform for providing Weather Information where people cannot only receive Weather Information but some stuff back at us. Ask questions, who have answers to experts. New Program Certain cities you are interested in getting the forecast for and in a second its right there for you when you wake up in the morning. When the weather is highly impactful you get dealers. I think one of the things one of things whether Smart Phone Apps dont do which i think theres a need for and continue to be a need for is the human interpretation to serve. You got an icon with the cloud when the stakes in the forecast are high you want to understand what the branch of possibilities are. You want to understand how this is going to impact me. If you want a more detailed Weather Information you need people in whatever platform you prefer weather video or text or graphics you need the information presented to you that way in some of the automated ways of obtaining that information dont do that for you. I still think there is a need for a human in the decision process. I wish we had a capital gain in new york. Still truly the moments where there is a lag between what the forecast and particularly the models are technically able to present stop raining at this time, and the way in which that is kind of the highs and lows of that are switched out in the app. Very deliberate hedging i think thats quite clear. The other thing that is clear but in a frustrating way sometimes the forecast is very competent and sometimes it is not. Sometimes the forecast is that it might rain. I think the leg between what the system technically is spitting out and what we are willing to hear and how much we are willing to trust that is very much in process. In awe of the way the you may wake abthanks for that. Andrew, let me ask you something. How do you look at a forecast differently now since youve done the book . In the way you did before . Quite differently. Im not trained as a meteorologist and i recognize what the limits are and the way i look at it. I think one of the things i learned is by knowing the rhythm of the models i know i can sort of see what the trends are even in the apps. Weather underground has the kind of most granular detail and what its presenting if you know that its essentially being updated every 12 hours you begin to recognize what changes are happening in the forecast. I just did as a game i did an experiment of looking at the eight day forecast for the publication day of my book each day and presenting it and it was amazing to see how little forecast manifested in the weather app how little it changed over eight days. It was a bit of a cheat because it happened to be it was 50 rain basically for eight days. But sure enough the day came and it rained and it didnt rain it is a bit of both. For me its both trusting the percentages more. And not just looking at when the emoji flips over from sun to cloud. And also recognizing that the day is long. The models have a lot more resolution in time to stop today was a great example. The emoji for the day in dc mightve shown showers but it was pretty clear the last several days that by 2 00 p. M. It was brighter. Trusting it more. One of overriding theme which angelas book makes it Crystal Clear and will give you a better appreciation for the Weather Forecast the public may face a Weather Forecast we are just interpreting information which we are sort of we are just translators. The work which was done to get weather prediction to where it is today was performed by some of the most brilliant mathematicians and physicists in the world. Its incredibly complex and these people it took decades of just incredible hard work and required some of the brightest minds. To the public i dont think they get and i think andrews book makes it really clear. How sophisticated how complicated and how rigorous meteorological science is it requires some of the brightest minds in the world to get the weather models we have these days and the people with the pretty faces you see on tv they are not the people who built the foundation for this. It gives you a really great appreciation for the science and meteorology and how we got to where we are today. I would just say and add to that that it amazed me that the goal is to serve people. The goal is how people stay out of harms way and the sort of straightforward righteousness in which the meteorologists approach that was pretty startling. I was a little nervous i was saying who needs meteorologists anymore we got apps. Which was not the case at all. It was amazing to see and merge the counter narrative of course the system is made and requires human interpretation particularly whether it becomes more dramatic. While the weather is a complicated subject andrew, as you did with your book on the internet you made a very accessible very readable. I would encourage everybody to buy a copy of andrews book. Thank you both andrew and jason. Thank you jason. And you will be signing copies at that desk. Tonight at 9 00 p. M. Eastern on after words in the new book justice on trial the federalist Molly Hemingway and Judicial Crisis Network Carrie Severino examine the confirmation of Supreme Court justice rick cavanaugh. In the future of the court. They are interviewed by los angeles time Supreme Court corresponded david savage. We were trying to figure out in talking to these people who was it we saw a very different judge kavanaugh when he interviewed much more bush approach. Then on thursday when he really came out strong it was fascinating to learn that in fact that was the person he really had been early on as the court has become more political in its decisionmaking when it makes laws rather than interpreting the law when its written that creates a very political situation is not altogether surprising that it becomes the process itself becomes more political. At 11 00 p. M. Eastern cbs news legal analyst quinn whaley offers her guide to reading and understanding the u. S. Constitution. In her new book how to read the constitution and why. A question i get a lot on television and regular conversation is, can he do that. Can the president do that. My answer is, thus the wrong question. The question is, if he does that, weve had up until now president to not cross certain boundaries, whats the consequence . What are the processes for holding the president accountable . Watch booktv every weekend on cspan2. Good evening everyone. Thank you so much for joining us tonight. My name is megan bedstead on behalf of Harvard Bookstore and very pleased to welcome you to this evenings event with thomas abt discussing his new