comparemela.com

Thank you so much for coming and braving the weather, what a great day to have a book about the weather. If you have been following the weather, who does not these days, you will have noticed at least two things, first it is getting weirder and wilder with bigger storms, hotter and more freezing temperatures and greater extremes seemingly all times of the year. Second the forecaster are Getting Better at predicting what is about to hit us, they still do not get it right 100 of the time but their accuracy is definitely improved and so has the timeliness of the report. These days were where not only of one weather model but of multiple ones simulating the fruifuture space of the atmosphe is north of a model, european model, global, and a number of others and their forecasting not just todays weather or tomorrows but whether over the next ten days and beyond. Andrew blum got interested in the stuff, he was not satisfied with explanations that attributed the advances and whether science for the supercomputers and better satellite. The journalist was a knack for making complex systems assessable and he did in his previous book which was a tremor on the physical infrastructure of the internet. And he saw and Weather Forecast a similar 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 a daily weather report. Andrew recounts how forecasting has evolved from scattered stations to the uns world logical organization. He introduces readers to scientists, subtle and supercomputers that make up the world forecast assistance. He will be in conversation this evening with washingtons own expert forecasters, jason who is the weather at the Washington Post and chief meteorologist of the capital weather game. Jason himself has been fascinated by the weather since growing up in the d. C. Region as a High School Student he interned with bob ryan who at least some of you know and will recall for years the chief meteorologist for the local nbc affiliate, he went on to study atmosphere science in graduate school and worked as a Climate Change analyst at the epa in 15 years ago he established capital weather. Com, the first professional weather blog on the internet, the Washington Post absorbed the blog and 2008 and jason and his gang are now assessed read for anyone interested in the weather in the d. C. Area. Please join me in welcoming andrew and jason. [applause] hello, thank you all for coming and thank you for the good introduction. Ive been here before and really wanted to come back. Im glad to have the chance with the new book. I was a little nervous on the train when washington was washing away. Jason had a busy day, i was particularly pleased that jason agreed to be here, we met when i started this project several years ago, i went to the meeting of the Neurological Society and new i wanted to write something about this topic and was trained to figure out what might be in having all of the world meteorologist in one place was definitely a great starting point to figure out how it was put together. I did realize there was a Weather Museum and the second was there i was i warmly embracd and theres about 25 people. Which jason was assisted, but is great to have them here. We will talk for halfhour and then open it up for questions. In the past enough to. Its a pleasure to be here tonight, funny story the first time i ever took a number was with andrew from the american reader Logical Society meeting in atlanta to the airport. Back in 2014. Anyways as preparation that i did have to read the book, i have to say it was a joy. I found myself smiling and sometimes youre watching a great concert or great singer and a smile comes across your face because you moved by how powerful the performances and the writing is elegant and lots of excellent narratives and antidotes so it definitely earns my high recommendation. Anyway lets get started with the q a and lets begin with the motivation for the book and what made you sit down and decide that you wanted to write a book about the history of Weather Forecast. Theres a few different threats which we have time to go into print my background is mostly writing about architecture in writing about places, you cannot write about places without thinking about the weather. But weather is hard to write about especially if youre not a meteorologist or scientist, its very loosely in the words slip away. There is a constant challenge between you forget your umbrella in my dress properly for the day and catastrophic. I think that combination to you meteorologist and write about the weather in that way. It had stuck with me for a while. What stuck me was Hurricane Sandy in 2012. Which was a moment the weather models reveal themselves. There were suddenly public conversation about the American Weather model in the european weather model and only that but an astonishing forecast, 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 meteorologist were capable in terms of human ability and their own pattern recognition and manual stimulation of data. Clearly they had built systems that worst on astonishing. And the question of what are the weather models and how do they work was hard to interpret it was an incredible black box and that type of complex infrastructure was what got me going to recognize if i can figure out how these models worked, i could understand them to tell a story about them. And thats what like there was a story to be told there. And i underestimated complexity. Does anyone work in weather models . Okay. None. On underestimated their complexity because theres a very small group of people to work on them and improve them. And the entry to recognize what their parts and pieces were was significant. But it check the box that was so important for me for system that we touch every single day. The first book about the internet, heres a complex global system that we carry around in her pocket and is really a black box and it was a story and wanted to tell. And of course you cant tell it without going back in time to some of the history and how it develops. Lets talk about the history and the pioneering scientist in the 1800s who laid the foundation for modern day weather prediction, they were scientist in england and norway that you talk about in your book, lets go to the early contributors and how important the work they did was to be advancements that we see in weather production today. There is to histories of weather, there is a history of the Storm Chasers and watching sky and to see this heroic story of wind speeds in weather maps and all that. And theres another history of mathematicians and when i started to think about how to tell the so the history it was distinct from the other histories in a very much begins with a meteorologist bill, he occupied both histories, he came up with the idea to return to bennington century in the 20 century, 1904 was his main paper to calculate the weather and using equations of physics to describe the atmosphere would do next and with the main insight that each day calculation could be itself a hypothesis. And if you could calculate the weather you could prove whether cut collations were right or wrong and refine those calculations on a daily basis which is a process of improvement to a credible place right today. I feel like i should lay out that a audible place. But to say over the last 40 years, a fiveday forecast is a good of the 40 forecast ten years ago or today forecast 30 years ago. And that rate is not mentioning is increasing the talk of a two week forecast by 2025 so this made an improvement and it goes back to his idea of seeing if you can calculate the weather then each day is assigned six permit and you can try it again the next day. But then he cannot kick it like the weather of course, the biggest mathematician tried to cut to the weather and he realized he would need 64000 computers and 60 per thousand people we thought could be arranged in a stadium unit could each get their square of corresponding atmosphere and at that square they do the calculations and pass them up to the front and maybe that would work to calculate the weather fast enough for useful prediction. Because to calculate it has to be done before the weather comes or its not useful. That inability to calculate, the lack of observation, the lack of a computer to calculate them was essentially meant that their ideas had to wait 50 years until computers and satellites began to come in and had to wait in nearly 50 years, so the last 30 years to be useful beyond the human scale not just guidance but to exceed the capabilities of human meteorologist to the point, there is a human check but you would not find its hard to find meteorologist who say it dont work. Its remarkable how good the Weather Forecasting models are. Trillions of calculations per Second Period its amazing. One of the critical developments in American Weather prediction, we fastforward to the 1950s and 1960s, we alluded to this already, Weather Satellite. Talk about the history of Weather Satellite and how they played an integral role in the development of forecast and major discovery with technology. The key idea i fell in world with was a longerrange forecast for two and three and four you need a global view, it cannot just be and youre not just looking at the weather in north america, youre talking about the weather globally to talk about the entire global atmosphere. You need a global instrument, the stopper satellite drive, in the 60s he began to have the first inklings of that. It also amazes me that the monto comes out as a sink and joined civilian scientific and military effort that you have no satellite without the dollars spent and you have no Weather Satellite without the dollars spent for surveillance satellite in a scientific idea and military ideas are handinhand and until quite notably until kennedy, in the spring 1961 speech that we put a man on the moon before the decade is out, that was bullet point number one in bullet point number two was Nuclear Rockets for deep space travel, number three was comedic asian satellite and number four was Weather Satellite. Its amazing that you have a basic and fitness for global view in the same speech as a moonshot speech and the most famous infra structure speech. And then you have it rooted in an idea that its a national corporation. Sure enough, that speech in the leader speech in the fall of the human, the nuclear and isolation speech, the answer that kennedy proposed for togetherness in an alternative for peace was cooperation on weather observation and control. The control part got left behind but that idea from the very beginning about diplomatic collaboration between meteorologist from every country in order to make global data out of infrastructure to support global models kinda gives roots of cooperation that begins in the 19th century but current incarnation is inspired by kennedys idea of a Global Mission and that continues today, somewhat quietly and we often dont 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 model whether youre talking about the weather balloon data, groundbased sensors and you just talked about whether satellites and whether satellites are superexpensive and cost governments billions of dollars but without them are forecast would not be where they are. So obviously the Weather Satellite data, the observations from groundbased sensors, weather balloons, feed these models and you went to two Different Centers to learn more about whether models. Angel went to the European Center for the forecast. I went to the national Weather Service but i did not put in the book. Talk about your experiences visiting the centers in the appreciation you gained for these models. You touched on this a little bit bullet here in depth of what makes these models work, the amount of intellects required to run these models, who are the people in these works and how have they been able to be so successful in improving Weather Forecast overtime. I think this competition between the american model and european model is shorthand but it was amazing and visiting both places, the journalist and cleaner stories for more legible stories, and its amazing that cleaner stories come from cleaner places and the places have a coherent organization and have a very focused Mission Statement and are much easier to describe and write about. And are often more successful because of that. So we weather model the fact that we take the starting point and theres a weather model war and european model to see and go visit the source of that for me too read Weather Forecast which is outside and is a collaboration funded by 32 European Countries that are contributing scientist and money with a singular goal of running the global model. And they do it by combining the research people, Weather Operations model people in the same building and an amazing cafeteria, cafeterias are becoming a cliche in the tech culture but i cannot believe that anyone got any work done because cafeteria was always full. And they had beautiful hot machines. But that constant day by day effort to consider what the model was doing, what it was spitting out and how it can be improved as the system was really tangible. It was built and not just in daily internal wiki of comments on this weird wise of doing it in with weekly meetings and quarterly meetings which are observed and read about. Its a constant sense of what is the model doing and how can they do better. I think the key point is when you say and talk about it a little, is not about a meatgrinder and whether the present was in in the future comes out, its about having an ongoing simulation of atmosphere that every six hours or 12 hours is compared to the most recent observations of the real atmosphere and corrected slightly to better match. In that is assimilated atmosphere or clicking Forward Together to run faster in time to give us the forecast. It makes you realize to make the forecast better to make the simulation better. Not just in assisted school and passed weather, its more about using these equations to simulate the atmosphere in a way that is close enough to reality that when it is run forward faster in time is bits of the weather of the future. And to see how eager the people at the center were to make sure they were getting it right which is not just to say they were getting the forecast right but to say the simulation they were building most closing resembles the real atmosphere for all the right reasons. That the actual physics match not just getting lucky repeatedly. And that is not Machine Learning or not a predicted problem in the way we think of elections or other Group Baseball or other predictive problems. It is unique and uniquely successful too. This is something that we as everything will day and mostly right. Does that answer your culture question . Did you find they were competitive and wanted to beat the other Modeling Centers around the world . When you say why are you doing this they say we want to be the best. And theres an ongoing discussion about the modern competition and as we were talking before theres a sense that it keeps everybody improving their model foster that there is a sense that they do it the u. S. Models are alluded by having to serve different masters and models and they say we run 12 models and they only run one, while that is true, the single focus on this tenday simulation of the atmosphere makes their collaboration in the competitiveness very productive. Im much more of a streamline process. Obviously we have talked a lot about great Weather Forecast. But theres a saying, your Weather Forecast can be 100 accurate but if people make the wrong decision based on an accurate forecast, the forecast is useless. When i began to understand of what makes a good forecast,. How does the forecast inform decisionmaking and does the forecaster provide the user the information they need so if there is a winning reception coming up that they will have a tent or not have a tent to keep it dry. In the aspect in your book. You think Weather Forecasting centers in the european in europe and the United States do think theyre gaining a better appreciation in the social science connecting the physical science which is the forecast with the decision . Its a per svice or the broader enterprises are excelling, the new links between the forecast and the decisions you make based upon. I write about a guy named tim palmer who is in oxford at the European Center and he tells an amazing story, is not a simple if its going to rain or knock wondering, how short are you and the visions are based on it. If youre having a party and a picnic and the queen is coming, a 20 chance then an 80 chance might not be enough to order tent. And if that sense of what is the use of a better forecast if it does not help our decisions. I think that is reasonable with the daytoday forecast, just because it was clear in going to rain monday morning four days ago, it was not clear how it was going to rain or we were talking before, what point this morning that it seemed like things were getting intense and then what decisions would people have made differently had this days forecast been clear. And that idea you can strive for perfect forecast but if it doesnt help you make decisions then the ball is out of record, it is only out of your court if you recognize the technical superiority in the technical achievement of the forecast itself. I think we knew whether forecast of come along way and were good at capturing what we call synoptics weather system, largescale systems, low pressure systems, when it comes down to forecasting individual thunderstorms which we had this morning, models are just developing in the area and we have what we call conduction allowing models which try to get thunderstorms, correct. In that you can only do sometimes within a couple of hours. Even at 5 00 a. M. And 6 00 a. M. This morning it was not clear that conflict of thunderstorms was going to light up and track straight through the d. C. Area. There is still a lot of progress we need to make even as a forecast weve got to do better each decade and you spoke about it, it is really localized fine scale forecast where theres a lot of progress where i think we can still make. Its a good segue to my next question. The importance of observation because they require observation and we have talked about all the different types of observations which are needed for robust numerical weather prediction system but there are some concerns in the larger private international whether community about where will be collecting data in the future, theres a lot more new data sources coming online, private companies which are launching Weather Satellites which want to sell their data rather than making them free, you have Remote Sensing systems on automobiles and transportation, he also phones in your pocket which are collecting data, how is that data sold to the government, talk about this issue and is coming up in the organization as a thorny issue as to historically weather data has been International Partnership among governments by your introducing the private sector which is a profit noted into this enterprise, how do you deal with that and talk a little bit about how your book addresses that. This was something that i realized the folks who were involved in the daytoday forecasting in the u. S. And particular because the System International system worked so well it was very quietly, a woman who is former chief scientist of those trillion Weather Service said we have not been a squeaky wheel ever, or collaboration over the world pulling them together and sending them back out over the world has worked so well and weave when under the radar and people dont appreciate how essential that is. And i think that is the peace and the fact that it is not reckonings is becoming a cause for concern. I shift toward private companies and observations. The tradition always has been but the Companies Share their information and get data back. Have private companies, offering data and the question then is if they sell it to one government, can they share it with every other government quests such a challenging Business Model if youre running a satellite company. Your to sell your data to as many as possible. If you cant sell the data or share it with our government, you have a risk of fracturing the entire system. The exchange is shut off and you end up a few observations, less improvement because you have all these new observation streams no longer a part of this global pool of data. Wont no longer appropriated into Global Infrastructure offerings global forecast. Thats a challenging place to be. Its a real shift with bigger bucks involved. More money at risk, more money to be made with weather extrem extremes, before it was unheard of, they would spend the 20 million on a supercomputer model. Now those dollar values seek more reasonable because of the greater climate risk. And more capabilities. I think it creates a Business Opportunity and there have been private forecasters for a wild. The shift would be if its no longer about a global pool of data taking the data for better forecasts. Its instead about fragmentation of new kinds of data thats not been shared. Its uncharted territory and had something a lot of the weather people, the representatives are taking part in that and its something that the Administration Pushes forward to make sure these new companies are able to be profitable. That is the, its not unique emphasis but a unique desire but its a unique emphasis. Its shifted to say we want to make sure these new companies can blossom and its not clear the stakes are for that global data exchange. Its coming from the combination of factors, the macro factors i think are very clear. Its very under the radar which is an observation. Its interesting because there should be a day where ibm has better for the Weather Forecast and the national Weather Service. They are developing their own model and theyve got brilliant scientists there who can create their own, do their own supercomputing. Then they can sell that information. Weather forecasting which is historically a public good now all of a sudden, if you want the best information rather than getting it free, you may have to pay for it. As a potential cuppa publicly provided Weather Forecast can become inferior unless the Weather Service develops partnerships with these private companies and weight status making agreements with. The reality is if it werent for, when you think about the satellite data, its the european, the American Weather satellites that contribute the data, not just the pictures we are used to the satellites but the numerical data that comes from other satellites. When you think about how big the contribution is, its a global vote for meteorology. The backstops, you would have at most ten or a dozen countries willing to pay for weather data that would be back. I can see the factors coming together to threaten it and it would be, its a 1150yearold thing. They knew, this storm was going to hit before the national Weather Service, but they be obligated to provide that forecast to everyone free of charge quests. It was striking to me talking to some of the people from around the world who are most concerned about these exchanges. How deeply ingrained sense of meteorology public good is it to see this shift from commodity i think is startling. Should we take some questions now . Yes. If you have a question, raise your hand and ill pass the mic to you. In regard to why we should care about having more accurate forecasts, i was wondering if you could do that with regards to corporations so like how much does it help the government to know a hurricane is going to come two weeks and advanced as opposed to one week . I where the longer not just Weather Forecasts days before in time to make a decision based on but because the forecast was so consistent for so long, the confident in making that decision from the forecast is greater. In india in early may, the people were killed, this time around, not just a longer range, i think it was several days out but the confidence in the forecast to evacuate 1 Million People was really clear. The idea of a high impact event, if that is reliable, we have a weeks warning, the counterexample the spring was a storm that had catastrophic damage and was predicted, it wasnt predicted with enough time or confidence to act on it. I also think examination system in the way of getting the work to the public and Warning Systems, india has a lot of experience in tropical cyclones having dealt with them repeatedly over the years. Theyve seen absolute devastation. They put into place Warning Systems and evacuation plans to get people away. Its interesting, for hurricanes, having a lot of lead time, its incredibly valuable. We could really pinpoint the track of a hurricane within 24 48 hours. Compared to where we were. With tornadoes, there is research that has shown the tornadoes, if you give p much people too much time, you can make worse decisions. Tornadoes might be 15 to 20 minutes, people know i have to do something right now. You give them two hours, they could make bad decisions, maybe wait last minute or drive out of the way, theres Interesting Research going into this. A gap between the forecast and peoples decisions. Without tornadoes in ohio and missouri and kansas, where it was a major tornado, a real victory for the national Weather Service going back to the tort 2011 tornado where 160, these are moments where its not just about the duration of the forecast but the fact that theres confidence in it. Back there. You kind of touched on this a bit but why is it that the european model is different than the american model . How does one become better or what is different . The physics on either side of the atlantic i think the basic, the limitations of the model, the resolution, the model is not a molecule simulation in the atmosphere, there are a lot of approximations made. A lot of the differences are happening. I think it really, the way tha that but i was surprised by is the importance of this writing up of observed weather and stimulated weather, data simulation and how challenging it is to take the data youve collected and find the right time and model scale insert that data and make it light up. A lot of advantage of the european model comes from their data simulations. The woman who is now the director started this, a way of lining up and correcting the weather inside the model and observing whether from outside. Thats the ability to constantly check the way the model is working and be better at putting the model back on course each step forward in time. Physics is physics but the ability to actually observe the atmosphere is supersized. I want to add one more point. The difference between the models arent that great. For years, theres no denying that. Ive always had time to look at one model, only had one access to one model. Its not the best buy a lot and its not the best in every situation so when the forecast forecaster, they have to understand the biases of the model and once you use one model import situation, there are times when the american model has better forecast than the european model. Sometimes winter storms, the american model has a better forecast for snow in the mid atlantic you just have to, as a forecaster, you have to look at the universal models collectively. His uk, canadian, models in japan and other international centers. You look at the ensemble approach, you try to look at where do they have things in common . Where are they on forecasting alike . What are the differences and then you make a forecast and communicate the uncertainty based on where the models disagree. The models are higher resolution than reality which is to say that, with the given conditions are far more places from model than we actually observe them. The models are where all the data is. The actual observed weather is a very small portion of the amount of detail the models are protecting. The models have more higher resolution than reality. Thanks for writing the book. Im curious if there are any bottlenecks. For my field, theres tons of researchers and 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 the most improvement be made . One of the things thats striking to me, this shift that happened in meteorology, its become about cast of improving models is a different skill set and the traditional meteorological training. When you see all the action in the system, its not clear to me if american meteorology programs have gotten that. As with so many other things, because the same, because of this skill set and data science, because theres so much people on that for the private sectors in silicon valley, i think that is also a bit of a drag as well. I was doing talking to the administrator and a strong capsf computer scientists on board, they continue to try to improve the american system so clearly you do need physical scientists, every part of the model system relies on observations to keep improving that. You have to keep on adding observations to the system and making sure the observations are high quality and so forth. Need them involved in that and testing of model and finding where the model is not working correctly. Publishing research on how to better represent the processes in the atmosphere so moving that research the operations, which is this whole operations question, its been far superior to the u. S. Approach. Its one of the reasons people who have studied this issue concluded that the european have better collaboration that is Research Operations if they spent a lot more time and effort on the research but jacobs recognizes that and hes trying to beef up the Research Within the Weather Service. So they can continue to make progress there. I would be more critical of that, while there is talk of improving with a new center, its a step in the right direction, but the drag is enormous. Its an entire structure of the american modeling system. It has been changing over the years. When you look at the clarity, even of the uk office, you have to recognize what we dont have at the moment. So thats not the kind of thing funding for this solves. I think its this first effort, its a step but a very small step. I can speak more freely about that. What are the motivations behind this model . Movie american model system into the cloud and allow researchers at universities to run the model in parallel and test things out and then send improvements and identify errors that send those back to the Software Engineers within this new Modeling Center so they can over time, in cycles, improve the model. Thats what they are trying to do. Time will tell whether or not its successful but they are working on it. Whether they can accomplish it in a year end a half or five years, we will see. Questions about the information like forecast in general, getting the book on the phone regarding flooding and basically, you see it moving toward that model completely . I googled the old part and they are revitalizing that, i dont know if that fell by the wayside or if its still going on. Local weather, is that falling by the wayside . Or are we moving something toward Something Different . He has a whole chapter in his book, you talk about the consumers use to get Weather Forecasts now, the way information is received is changing, whether you are taking about weather, sports, increasingly people overwhelmingly are receiving Weather Information on mobile devices. A Smart Phone App for mobile web, android, iphone, whatever. One of the reasons we have been successful, or by the team, we have been digital first. Since we started in terms of providing interactive platforms or Weather Information for people not only receive Weather Information but send stuff back and ask questions. With the app, program cities that are interested in getting cap forecast in the trike therefore when you wake up in the morning. When the weather is highly impactful, you get alerts. This interpretation two if you have the cloud, it doesnt tell you that much. When the stakes are high in the forecast, you understand the range of hostility is, and how it will impact me. If you want more details, you do need people to get into whatever platform youre in, you need the information presented to you in some of the automated ways of obtaining that information. So theres a need for a human in that process. The moment where there is a lag between the forecast and the models are technically able to present, into the way in which thats kind of the highs and lows of that, they are switched out in the apps, inc. Deliberate kind of touching. I think that is quite clear. ~ think that is clear in a frustrating way some of the forecast is competent and sometimes its not. Sometimes it might rain. Its not something we want to hear. I think that is a lag between the system is technically spitting out and what we are willing to care. Its very much a process. You can make up for the leg by presenting the range of possibilities for that. You look at a forecast differently now since you have done the book thank you did before . Quite differently. Are not trained as a meteorologist. I recognize the limits. One of the things i have learned is by knowing the rhythm of the models, i can see what the trends are so Weather Underground has the most granular detail. If you know its being updated every 12 hours, you begin to recognize what changes are happening in the forecast. I did an experiment of looking at the eight day forecast in my book, each day and presenting it. It was amazing to see how little the forecast has manifested, how little it changed in eight days. It was a bit of a cheat. He was 50 rain for eight days. Sure enough, the day came and it rained and it didnt rain. So for me, its both trusting the percentages more and not just looking at when the emoji flips over from sun to cloud and recognizing the day is long into the models have a lot more resolution in time so today was a great example. The emoji for the day, it showed showers but its been pretty clear in the last several days. So trusting it more is what its really done for me. One more question . I think one overriding theme which is fixed Crystal Clear and will give you a better appreciation the Weather Forecast the public makes it seem whether its somebody online or wherever, we interpret information and we are just translators. The work which was done to get weather prediction to where it is today was performed by the most brilliant mathematicians in the world. Its incredibly complex and these people, it took decades of incredible hard work and again, to the public, i dont think they get. I think his book makes it clear. Sophisticated and complicated and how rigorous this science is. It requires some of the brightest minds in the world. The faces you see on tv, they are not the people who built the foundation for this. It gives you a great appreciation for the science we are neurology where we have gone today. Out at that it amazes me, the goal is to help people stay out of harms way. I was nervous, we got our apps, which is not the case at all. It was amazing to see the counter narrative, they use this human interpretation, it becomes more dramatic. I would encourage everybody to buy a copy of his book or two. [applause] thank you both. [applause] injury will be over there at that desk signing copies. On our Author Interview program, they interviewed michael about our right politics in america. Is a portion of that program. There is no agreement across the culture other than who the enemy is and the nature of the enemy. There are those who are complete and argus and those who are internationals sense of i will be a citizen in the sense of i dont own a particular nation and those who are America First who will take the country back. You will have very little agreement other than who you are against. When you sit down with people in the group and say what you want, some are in favor of returning to the monarchy. Its hilarious, when you deal with any subculture, Company Different actions there are. You have the hilary types and Bernie Sanders types, they genuinely lows each other. To watch this and other programs in their entirety, visit our website, booktv. Org and click on the afterwards tab at the top of the page. The next book we want to talk about is called roughriders theater roosevelt. The author is mark lee gardner. Doug gardner, how did Teddy Roosevelt get there in 1898 . It was a lot of theater roosevelt said i put myself in the way of things happening and

© 2024 Vimarsana

comparemela.com © 2020. All Rights Reserved.