 Hello and welcome to Meet the Experts, Testing the Limits of Weather Predictability. I'm Katie Wolfson with the UCAR Center for Science Education, and we are so excited to have all of you on today with us. We hope that you will have lots of questions for our expert today. This program is our bi-weekly program where we connect you students wherever you are with experts at the National Center for Atmospheric Research, and we've talked to all sorts of amazing folks studying wildfires and hurricanes, working on supercomputers, and that's one of the really neat things about National Center for Atmospheric Research is there are so many different jobs you can have. You can be a scientist, you can be an engineer, you can be a pilot, a mechanic, a chef, an educator, so many different options, and so we're so excited that over this last year, we've had the opportunity to connect you with some of those experts. Today, we have a really great expert for you to talk to, but before we get there, a few quick housekeeping things. I want to invite everybody to please ask questions in the chat. Please feel free to say hello in the chat. If you haven't already, we love having all of you from Colorado and California on with us today, and thank you, Marley. I like my name's pretty cool. I like it. It's great. Your name's great too. Thank you for saying hi in the chat, and I want to ask you all to keep your microphones muted for right now. At the end, I will invite you would like to tell us in the chat, you have a question. You can unmute and ask your question to our expert then. But in the meantime, feel free to type any questions you have, any observations you make in the chat as we go. I also want to let you all know that we do have closed captioning available. You can turn that on and off and zoom down below. So you should see a little button there. So you can turn that on and whatever your preferences. Also, at the very end of this, we are going to ask if any students who are in fifth through 12th grade would like to help us out and let us know what you liked and learned from this program. There's going to be a survey link for you. And we'd really, really appreciate you filling out that survey. So if you can kind of hang tight for the very end of the program, we will share that link with you there. So thank you so much, everybody. Without further ado, I think I'm going to turn it over to our expert today. We have someone really fun for you to talk to today. We have Falco Jupe, who is a meteorologist with the Mesoscale and Microscale Meteorology Lab at the National Center for Abysspheric Research. And we are having some internet connection stuff today. So please bear with us and be patient with us. You can let us know in the chat if you can't hear too well and need us to repeat something. But thank you for your patience there. But without further ado, I'm going to hand it over to Falco. And Falco, do you mind telling us a little bit about who you are and how you got interested in weather in the first place? Sure. Hi, everyone. My name is Falco and I love weather. I love storms. I love snow. The crazier it gets, the more I love the weather. So today I look out of the window and it's sunny and I have to say, well, that's a little bit boring to me. I really love when the wind blows and when it rains, when it storms. So I really love the weather and that's why I became a research meteorologist here at NCAR. I also love planes, by the way. But I wanted to talk to you a little bit about, well, how did I end up where I'm now? How did I become a scientist? Because it wasn't really clear when I was in school. I just knew I love the weather and I love science and I love geeky and nerdy stuff. Yeah. And so I'm going to share some pictures of me. Hold on a second. Of me in school and maybe you can relate it to yourself a little bit. So there we go. So I hope you can see my screen. I, by the way, I grew up in Germany. So these pictures here, that's me with a red shirt in 12th grade. And at the top there, that was my focus class. In Germany, it was chemistry. I'm holding a little model of the molecule there. And I also love nature and geography. And so my second focus class, which you see a picture of in the bottom there, where I'm holding a globe, that was geography. So yeah, in 12th grade, I love chemistry, physics, and geography. I love the weather, as I said, especially when it rains, thunders, and snows. But I didn't know I could actually study the weather. So what I did after leaving school was I went into the military because I mentioned I also love planes and helicopters. I grew up right next to a hospital where there was a rescue helicopter coming pretty much every day. So I thought I want to be a helicopter pilot. So I joined the German army to train to become a helicopter pilot. That's me at age, I think 18 or 19, sitting in the cockpit of a transport helicopter. But it turns out I was actually not born to be a pilot. I was a little scared, and I didn't do too well in the simulator test. So I left the military, and I thought, well, what can I do now? I still love the weather so much. So I went to college to study the weather. I became a meteorologist. And because I love stormy weather so much, and especially hurricanes, the hurricanes don't exist in Germany. So I went to Miami in Florida, a very tropical place, beaches that gets hit by hurricanes very often. So I went to the University of Miami for college to study hurricanes. And that is me probably 10 years ago on the roof of the meteorology building at the University of Miami staring into Tropical Storm Bonnie in 2010 was this. You see my hair there, it's blowing back. That's probably 30 to 40 mile an hour winds. I have to hold on to the railing there to not get blown away. And then it started raining, and I had to take my shirt off. People said, well, Falco, you should come down. It's really bad weather outside. And I said, no, I want to stay up there. And so I took the selfie of me that shirtless in a tropical storm. And what I do when I'm in the storm, I usually measure the wind speed. So I have this little guy here that is called a handheld weather station. And it can tell you the temperature, the pressure, and especially the wind speed. I love strong winds. So I'm going to turn it on now. And hopefully, you can see it says 0 miles per hour there because there is no wind inside my office here, inside my room. But I can blow into it. And you see, oh, it was up to, I think, was 14 or 15 miles per hour. So with this little guy, I go out when it's blowing really hard. And I measured 40, 50 mile an hour winds here in Colorado. And you saw that picture of me there that was a tropical storm. And I had, I think, 30 to 40 mile an hour winds. So really cool. I go, every time I go hiking or outside, I take this little weather station with me. And I'm going to blow into it again. So I was actually up to 20 miles per hour. I can blow 20 miles per hour. Yeah, anyway, so I really love the weather. And I want to, if you like the weather, you should considering maybe when you go to university, you should start thinking until I could study the weather. I could study meteorology. And the good thing is you're not only in the classroom, but you also get to go outside. Let me share my screen again. There's some more cool pictures I want to show you. I hope this is showing up. This is me and a friend of mine at night in the Florida Keys. And we're launching weather balloons. So what's a weather balloon? Well, what we want to do is we want to make hurricane forecasts better. And so we need to gather data about the atmosphere. We need to know where the wind blows at different heights in the atmosphere here. And how do we do the next picture here? That is me, nicely tanned from pulling a Atlantic Ocean. And it gets there by hanging on this weather balloon. And that's me here with a big balloon. And we're just next to a road at night. And we're launching the balloon there at infocast there, especially when there are hurricanes. But the coolest thing of my studies was actually a trip all the way around the world into the Indian Ocean. So that trip actually took two days just to get there. I flew from Miami to Washington, DC, changed planes and flew for 14 hours to Japan. Changed planes again flew for another six hours to Singapore. And then on board of an American US Air Force transport plane, I flew into a tiny island into the Indian Ocean. And how it is to be on a military transport plane while this is a picture. We're there with the equipment. And that's me in the green shirt there, laying on the failure commercial flag that we're on there. But you're rewarded. When you're in the Indian Ocean, we were on a tiny island. And this is what the environment is there. It's a beautiful paradise in the middle of the tropical Indian Ocean. And well, you might ask, why did you go there? Well, we wanted to study the weather there. There's very interesting weather there is in the wild. And we don't really know why it appears. But this island is really famous for another thing, coconut crabs. So what you're seeing here, this brown thing on the right, that's a coconut. And this little guy here, it's not little. It's actually very big as a coconut crab. I have never heard of a coconut crab before. They live on land and they eat coconuts. And they live only on these small islands in the Indian Ocean. The really cool thing what we did as scientists, this is us, the crew of scientists here, we came there with a research plane. So a big plane that measures winds, rain, the chemistry of the atmosphere, everything that you want to know about the atmosphere. There are instruments in the plane and it measures those. It's called a P3. That's the P3 we flew on and all of its beauty. Yeah, so we were in the Indian Ocean and I was a student. And I got out on the plane and then we just flew into the Indian Ocean and well, not into the ocean but over the ocean. And we just measure the winds, the clouds to understand, well, what's the situation of the weather there? Yeah, this is us on that P3 plane and we're dropping what is called an ocean buoy out of the plane while the plane is in the air. So you see a guy there who's holding a tube and in that tube is this ocean buoy. And there's a little hole in the plane and it just drops out of there as the plane is flying. And you can see here the plane that's a picture taken from a boat and there's this little piece coming out of the belly of the plane with a little parachute under the tail of the plane. And that's this buoy that we were dropping to better understand, okay, the ocean there is really warm, there must be a lot of water evaporating from the ocean to the air that's important for those storms. And we measured those ocean temperatures with these buoys. But we also have fun on the plane. So those flights are long and the pilots like to have us up there or scientists up there so we can tell them about the clouds. These are two pilots of the plane and they even let you or in that case me fly the plane for a little bit. Remember I had some experience flying helicopters but I'd never flown a plane before but there in the Indian Ocean where no other planes are around that's where I could actually try out to find a plane, fly a plane. Okay, so that was a little bit about me about how I study meteorology. So I've always been interested in the weather and I love the weather and so I always check my forecast. First thing in the morning, I checked the forecast for this day and for the next couple of days. And I always wondered. So I checked my forecast for this day and the next couple of days but I don't check the forecast for next month or for next Christmas. And I was thinking, well, why is that? So well, probably because we cannot forecast the weather for that fall or out, right? So I'm gonna ask you guys now to type in the chat how far out do you think can you trust the forecast or maybe even a month or a year? So if you think about it, let's say, yeah, what is the length into the future or the time into the future that you would trust the weather forecast? And I'm gonna tell you the answer later on. Let's see if you guys wanna give us an answer. Three weeks, three days, five days. Nobody's saying two months, nobody's saying a full year, probably because you know that, right? Yeah, I can tell you, I won't be able to tell you if we're gonna have a white Christmas this year or the next year because simply we're aren't that good at forecasting the weather for that far out. And there is a very, very sciencey answer there about 10 days for skillful prediction. Yes, but actually we can do a little bit better than that with the next generation of weather simulation models. And I'm gonna ask Katie now to play a movie which is from one of these super detailed weather models that we will be using in the future for weather forecasting. So if you look at this video now and you see, well, that looks like our earth, there is the US and North America there and you see all the clouds swirling about that's from a satellite, right? That's the, maybe it's current weather, it's sunny over Colorado there in the movie. Well, it turns out this is actually from a simulation. A simulation with one of those incredibly detailed next generation weather models. And Katie can, yeah, thanks for playing that. And so that's what I've been using here at NCAR to look into how far out we can actually forecast the weather in an optimal way. So this is a little bit of a thought experience. So the atmosphere is very, very complex. So we take planes and balloons to measure it, but we can only measure little, little bits of the whole atmosphere. So in order to measure everything, which we can't, we have to create our own weather in the computer. And that's where we use these super detailed models. And so my goal was to figure out how far out can we predict the weather? And in that, to do that, it gets a little bit complicated. Now we have to do a thought experiment first. Let's say we, okay, no, not with thought experiment, but what's what we call an idealized experiment. I will share with you now another graphic. So bear with me. And this is now the experiment that I did. Okay, I hope you can see my screen now. There should, you should be able to see a globe and left to the globe, it says fake reality. I just assume you guys can see that now. All right, so I'm gonna explain to you now. This is the super cool experiment that I ran with these incredibly detailed weather simulation models. So as I said, we cannot measure the atmosphere as well as we can do in the computer model because it sits in the computer. We have all the data there. So I ran a simulation. I created the weather for 20 days over the whole globe. And I'm gonna call that fake reality. That, now we think that is reality, but it's not. It's just a simulation. It's like in the matrix. That weather only exists in the computer, but let's pretend it's the real weather out there. And I took a point in the Amazon brain force. There's a city called Manaus in Brazil. And I told the computer, tell me what the wind speed is in Brazil, in the rainforest when we start the simulation. And the answer is here, 10.567 miles per hour. Remember the computer knows everything. It's a simulation. We can ask, we can see what the weather is at any point in the world, anytime. And this is what it was in Manaus in Brazil when we started the simulation. Okay, so the weather evolved over 20 days. And after that simulation finished, I ran another simulation. But now I pretend that, now here comes the thought experiment in the Amazon rainforest in Brazil, there's a little butterfly. And that butterfly probably flaps its wings. And as it flaps its wings, it makes the wind a little bit faster. So now we just assume in Brazil, in the rainforest, the wind speed is not 10.576 miles per hour, but 10.568 miles per hour. So a thousands of a mile per hour faster than that's something I cannot even measure with this instrument that I showed you before. And then we start the simulation again. And that is the only change. We only change the wind speed in the Amazon rainforest by a thousands of a mile. And we run the simulation again for 20 days and we see how the weather evolves. And you would probably think, well it will evolve more or less exactly the same because these two simulations are the same everywhere except for this teeny tiny change in the wind speed somewhere in Brazil where a butterfly flap its wings. But it turns out because the atmosphere is chaotic. So it's essentially unpredictable after some time that the weather situation all over the globe will be different between those two runs, the fake reality and the butterfly twin. And I'm gonna ask Katie now to show us a movie where we look at the temperature in Boulder you will see a line or two lines. So what the lines are showing is the temperature in Boulder in blue for the fake reality simulation and in red for the one where we had a little butterfly in the Amazon rainforest. Katie, it's predictability movie one. So first they are close together but then after a while, you see the number of days there on the bottom those red and blue lines are different. And that is because the atmosphere is chaotic. So that little butterfly changed the whole weather all over the globe. Not so much in the first six days, there the weather in Boulder is more or less the same that yellow there, that kind of tells you how different the weather is. And maybe Katie can run it again. So again in blue and red, that's the two simulations with the weather in Boulder and we see now 14 days. Oh, the blue line is cold and the red line is further up. So it's much warmer. And that is only because a little butterfly flap it's wings in the Amazon rainforest. So in one simulation, we get a snowstorm in Colorado and the other one we get fine weather. And that is the essence of chaos. So it means the tiny, tiny change in the beginning of an event will have huge outcomes later on. And that is the reason why we cannot make perfect weather forecasts because we cannot simulate all these little butterflies. And it's not only butterflies, it's birds too. Since we don't know when they flap their little wings we will never know if we get a snowstorm in Colorado or sunny weather two weeks or three weeks from now. And the last thing I wanna show is on average how far out we can predict the weather. Now I asked Katie to play the predictability movie number two. And what you see there is a line that starts out high. High means it's accurate, weather forecast is accurate. And then it drops down. And when it hits that red line there on the bottom that means the weather forecast lost all of its accuracy it's completely unpredictable. And if you look at the numbers there on the bottom it starts out at number zero. Oh, the weather is very accurate. Well, we know what the weather is right now we just need to look out of the window, it's sunny. And two days, four days from now the purple line is still on top there. So it's still pretty accurate that you can trust the forecast, but after eight or 10 days that purple line drops down it loses accuracy because of all the butterflies and birds that flap their wings and make tiny little changes to the winds all over the globes. And because the chaos this is like an avalanche that starts out very little but goes bigger as we go out in the forecast the accuracy is completely gone by about 16 to 18 days there. So bottom line is you cannot get accurate weather predictions more than 16 to seven days in advance but that is more than we have now. So now one of the you guys gave me the answers three days, five days somebody was more optimistic three weeks and that's what we have now. So we can make forecast out to 10 days that we can really trust. For example, I can tell you that this weekend is gonna be beautiful but we will have another rain and snow storm coming early next week. But beyond 16 to 18 days we won't have any we say scale any accuracy in the weather forecast because of all the little butterflies in Brazil and everywhere in the world that we can't measure of we don't know when they flap their little wings and change the weather on a tiny, tiny microscopic scale but because the atmosphere is a chaotic system it's unpredictable beyond let's say two to three weeks. That's in theory, we can still improve our models we can still make them more detailed we can still get better observations from satellites and aircraft. And before I close now and open this up for questions I want you to reflect on what I said about the weather maybe it also applies to yourself think about it you can predict where you will be tomorrow in a few days next month, maybe next year you have graduated or in a couple of years you have graduated and you go to college but beyond that it's hard to predict what your life will look like. So there's a similarity between the weather and your life and it's really interesting. So I often think about that when I study the weather it's as unpredictable as my own life because I told you I wanted to be a helicopter pilot that didn't work out well now I study storms and the science of weather prediction. Yeah, so that's all I wanted to tell you I hope you found it interesting if you love the weather like me the next couple of days are gonna be a little boring but Monday we'll get another storm. Oh man, I don't know what that means for my gardening plans this weekend Falco students, we can but the plants gotta make it through that snow storm. All right, students we're gonna turn it over to questions feel free to type any questions you have for Falco in the chat. Also if you would like to unmute and ask your question go ahead and just type in I have a question and we'll call on you to ask your question. While we're waiting for those questions to come in I have a question for you Falco do you feel like you have any sort of super power or special skill that makes you really good at your job or you find is really useful in your job doesn't have to be a science skill but just something that you find really useful as your superpower. Yeah, curiosity, I'm extremely curious I wanna know everything and that's kind of my superpower that, cause my work can sometimes be a little boring I always sit in my chair most of the time and stare at the computer screen but I'm curious I wanna know about things I wanna know how everything works and that makes my life really cool so because as a scientist I can actually figure out how things work but other superpowers than that not really I have a 14 months old baby and sometimes it just cries and I don't know why I wish I had the superpower to make him stop crying but I don't. Yeah, but that's a whole nother thing to figure out I think right there we have a question in the chat from Matt Beckett asking if future technology improves and allows us to get the initial conditions of the atmosphere right with accurate real-time data for instance, temperature, pressure, wind, et cetera at every point across the globe how far into the future do you think we'll be able to skillfully predict weather due to the chaotic nature of weather that is sensitive, dependent to initial conditions? Not more than three weeks that's about the upper limit so it always depends on the current situation of the weather all over the globe so sometimes the weather is more predictable so we can maybe forecast the weather out to three weeks sometimes it's less sometimes it's just 10 days or two weeks but three weeks seems to be an upper limit even with let's assume perfect initial conditions we know everything except the butterflies but even if we knew the butterflies it wouldn't be more than three weeks. Awesome, great question and I see Marley has a question would like to unmute and ask her question. So if a butterfly can change the weather if you're outside reading a book and you turn the page could that also change the weather? Yes, exactly so if you go out read a book change the page of the book you make a little wind there and that little whirl of wind that will move and spread through the atmosphere and change the whole weather pattern so you could actually cause a tornado in Texas by reading a book. Yeah, that's really cool if you think about it all these little tiny impacts that we do to the atmosphere will change the weather in some ways that we don't know. Cool question, I never thought about it but yes you change the weather as well it's not only butterflies and birds, it's us too. So everybody can take your hands and wave your hands around right now and we can adjust the weather a little bit and add some chaos into the system. Wonderful, let's see if anyone else has any questions please feel free to type those in the chat or let us know I have a question. I was curious Falco, are there certain times of year that it's harder to predict the weather? I feel like here in Colorado, April especially seems to be a tricky month that the weather changes a lot. Is there a reason for that? That is true, so in general it is easier to forecast the weather when it's less dynamic. So when there are extended periods of sunshine and we have that here in the summer, right? So the sun shines, we have storms developing over the mountains and usually they die out over the mountains. That's very different from let's say April now where we have a fight between the winter that doesn't wanna go away, it still hangs out in the mountains and summer is already arriving, we get warm air from the south and that creates a dynamic atmosphere and the more dynamic this, the more the little butterflies or you turning the book matter in destroying the predictability. Wonderful, we got another question from Marley, follow up. Could you also change the weather inside a building or does it have to be outside? That's a very interesting question and I think you have to be outside because when you're inside the building and let's see, I blow the air stops at the wall. The weather outside doesn't feel that I blew in the building. So that little world that I created or by waving my hand, that just stays in the building. So you have to be outside. You have to be in contact with the actual weather, with the atmosphere outside. Wonderful, that is a great question and great thing that we can all be thinking about next time we're outside. Kalko, you shared some photos of you in a tropical storm before. What's for some of those students who maybe haven't been in a big storm or hurricane or tropical storm, what's that like to be inside one of those storms? Well, I love it. I think it's really cool because the wind blows so hard, it really hurts the eyes. It's tough to open your eyes when the wind is blowing that hard and there's rain. So about other people don't like it so much because, yeah, you get wet and you cannot be outside. It's a little dangerous, stuff flies around. So I showed you the pictures. That was a tropical storm. So that's just a storm, a hurricane. I wouldn't go outside because it gets really dangerous. The wind is so strong that it can tear off stuff from the houses that flies around. So generally, people don't like those storms, hurricanes and tropical storms. It's just us weather. Us weather, yes, that like the weather, that like the storm. I've never been in a real hurricane even though I lived in Miami for 10 years, but that was the hurricane drought we call it. No hurricanes hit Miami during that time. So I still want to experience one, but most people don't want to. All right, and we have another question from Marley. No need to apologize by asking questions. What about my dog's tail? Does that change the weather too? Yes, yes. So Ed, pretty much everything that can move the air, your dog's tail, maybe your dog's tail caused a rainstorm in Africa and Tui. So you go out today with your dog and it runs around and wags its tail and that little whirl of air that grows upscale, growth gets bigger and bigger, but you won't see it, you won't feel it. It just changes the course of the weather pattern and maybe that your dog maybe made it rain in a place that doesn't get much rain. So yeah, also the dog's heavy breathing too. Yeah. Breathing, breaking your dog's barbs, it also exhales air. Okay, let's take one more question. Are there any improvements like observation, data collection, computer speeds, math, physics that will make initial condition input into weather models and resulting weather predictions more accurate such that we may be able to extend that upper three-weight limit. Can we ever get past three weeks, Falco? So as we understand the science, the answer is actually no. Think about the speed of light, right? So the speed of light is a barrier and nothing can travel faster than the speed of light. It's just something that nature sets. And this three-week limit is also something that is set by nature herself. That is not something that's because of our technology and that can be lengthened by improving the technology. So the experiment that I showed you, the assumption in that experiment is that our weather model perfectly describes the atmosphere. It's called a perfect model assumption. So that's why I create this fake reality. I'm just saying like, okay, the weather model is perfect and creates the weather perfectly. And then I go in and change just one tiny little bit and run it again. So we say the initial condition is almost perfect there. It's not something, it's futuristic, but even with this futuristic assumption that we can have a perfect weather model and a almost perfect initial condition, it's still three weeks. So you would have to make the assumption that you can measure the atmosphere perfectly to go beyond three weeks, but that is impossible because we never, even with the best technology, we can never measure the wind speeds to an accuracy of, let's say a billionth of a mile per hour or a billionth of a degree. So yeah, it's a boundary that nature sets that three week limit. So no computer, no observation technology, as far as we understand the science, there could be, maybe artificial intelligence comes up with something that we can't grasp and that could change that three week limit, but as far as we know, we can never forecast the weather more than three weeks out in advance. And I should say here that we're talking about weather, so a storm that hits at any particular time or place, that's different from climate. We can predict the climate out hundreds of years because there we talk about long-term averages. That's different from weather conditions. Awesome, well, thank you so much, Falco. Thank you so much students for all your questions. I think that is all the time we have today. I wanna invite all of you to join us in a couple of weeks for our final meet the experts of this school year. We're gonna be on Thursday, May 13th at 11 a.m. mountain time. We're gonna do Meet the Experts 3D Printed Science Labs and the Internet of Things with scientist Agbali Amiko from the Computational and Information Systems Lab at NCAR. So if you wanna learn how to make your own weather station and gather your own weather data and connect that in and maybe help go into some of these models that are predicting our weather and forecasting our weather, we would love to see you on that program. You can register for that today. Also, I would love to throw it to Tim to tell us a little bit more about the survey opportunity that we have. Thank you, Katie. Yes, some of you probably know that we're part of a collective network to understand students' experiences in online programs. Well, we wanna know what you learned and thought about this program today. So if you're a student in fifth grade or older, please copy and paste this link onto your computer. And when you leave our meeting, go there and answer some questions that will help you reflect on your learning experience and give us feedback on our program, if possible. We know everybody else's scheduled to have to keep, but we would love to have everyone who participated today in the program to answer these questions. So we'll just thank you for your help straight away. And I was just fascinated, Falco. This has been amazing. Thank you. Yeah, thank you so much, Falco. Thank you students and everybody who joined us today. We'll hope to see you next time. Bye, everybody.