Science Friday - Starliner Leaves Astronauts Stuck | Could We Get Weather Forecasts Years In Advance?

Episode Date: August 9, 2024

The Boeing capsule is having issues with its thrusters and cannot bring astronauts back to Earth. Also, move over, Farmer’s Almanac. A more accurate long-term weather forecast could be on the horizon.Boeing’s Starliner Leaves Astronauts Stuck On The Space StationIn another blow to Boeing’s Starliner program, which is meant to ferry astronauts and supplies to the International Space Station, NASA announced Wednesday that the troubled spacecraft would not be able to take astronauts Suni Williams and Butch Wilmore back to Earth due to issues with its thrusters.The two astronauts arrived at the International Space Station in June for a mission that was supposed to last eight days. But with the current problems, the pair might be stuck on the space station, where Starliner remains docked, until early next year. NASA is considering bringing them back in an upcoming SpaceX Dragon mission.Ira Flatow is joined by Umair Irfan, senior correspondent at Vox, who breaks down this and other top science stories this week, including how the Olympic Games are adjusting to abnormally high temperatures in France, why the EPA banned a widely used weedkiller, and what the moon’s atmosphere is made of.Could We Get Weather Forecasts Years—Or A Decade—In Advance?Access to weather forecasts has been made easier than ever with the advent of smartphones. Most of the time, we can get accurate information about weather for the next few hours up through the next few days. But a week or two out, those predictions get less reliable.In the near future, it may be possible to get accurate weather forecasts weeks, months, or even a decade ahead of schedule. While this sounds like science fiction, researchers at the National Center for Atmospheric Research (NCAR) are working on this very challenge.Earth system predictions, as the field is called, combines a variety of factors including atmospheric conditions, ocean currents, and even what’s happening in the soil to form predictions. These forecasts are in high demand as the climate changes, particularly as farmers need more information about incoming heat and precipitation. There’s even the possibility that Earth systems predictions could help regions prepare for dangerous natural hazards well ahead of time.At Science Friday Live in Boulder, Colorado, Ira sat down with two NCAR scientists, Dr. Yaga Richter and Dr. Jerry Meehl about their work in this field.Transcripts for each segment will be available after the show airs on sciencefriday.com. Subscribe to this podcast. Plus, to stay updated on all things science, sign up for Science Friday's newsletters.

How do scientists forecast the weather? Take atmospheric land and sea ice to the observed state, start the model, and integrate it forward in time for 10 years, and try to predict the time evolution of regional climate as it's happening. It's Friday, August 9th, and you're listening to Science Friday. I'm sci-fi producer D. Peter Schmidt. I'm going to make a prediction, and it's that most of us probably check the weather this week, especially with all the heat and storms happening this summer. And most of the time, we can get pretty accurate forecasts for the next few hours or a couple days.

But what about weeks, months, or even a decade ahead of time? It seems like science fiction, but we'll hear from two researchers who are working on exactly that. They joined us at a live show we hosted in Boulder, Colorado last week. But before we get to that, here's Ira Flato with the top stories in science this week. Back in June, you might remember that Boeing Starliner capsule that successfully flew astronaut Sonny Williams and Butch Wilmore to the International Space Station on its maiden voyage. Remember that flight, of course, was not without its drama with problems arising with its thrusters. The mission was supposed to be an eight-day tour, but now it's August, and Williams and Wilmore are still on the space station.

Turns out that Starliner had more issues than Boeing thought, and NASA is now trying to figure out how to get those astronauts safely back to Earth. But it could take a while. Here's how NASA's Ken Bauersox explained to. this week. We know that at some point we need to bring Butch and Sonny home. While they're up there, we have extra crews, we have extra hands. They can do a lot more work, but they're also using up more supplies. So we have to maintain that balance. And at some point, we need to bring those folks home and get back to a normal crew size on the ISS. I'm sure they do. Umar-er-erfan is here with that story and other top stories of the week. He's senior correspondent at Vox. Welcome back to Science

Friday. Hey, Ira. So just for folks who don't know the beginnings of that story, what's the drama here? Well, these astronauts, you mentioned, Butch and Sunni, were supposed to only stay at the ISS for about eight days. They arrived in June and were just supposed to hang out there because they were testing the first crude mission with Boeing's new Starliner spacecraft. And this was initially just supposed to be a test run. But as you noted, on the way to the station, they had some drama. There were some damage to thrusters or thrusters that malfunction and some helium leaks. And so once they arrived at the space station, they spent a lot of time trying to diagnose the problem. The concern is that while NASA engineers and Boeing engineers say that the spacecraft is safe to return to Earth, they worry that a lot of the equipment that they're trying to analyze might be damaged on the return flight and they won't have this chance to sort of analyze the problem. And so the concern right now is that they want to be able to figure out what went wrong to help protect future missions.

Is there a backup spacecraft that they might use? Well, the International Space Station, they have lifeboats, and NASA does object to the term stuck or stranded. They always are keen to point out that they do have a way to get home, but they also don't want to use up those lifeboats unnecessarily. And so right now, what they're doing is scheduling another mission using the SpaceX Dragon capsule to arrive at the ISS, and then arranging for those two astronauts to return home on that mission. I'm sure that politically speaking with Boeing, that would be a black guy for them, right? Right. Yeah, Boeing is, you know, part of this new generation of spaceflight with NASA, where they're trying to find private contractors to help ferry astronauts back and forth on these space missions.

So SpaceX has been able to deliver astronauts successfully, but NASA also wants to have another company involved as well as a competitor, but also to have a backup plan. And so that's part of why they're so vested in the success of this Boeing mission as well, even though they have a private contractor that already has been able to do this mission. And so it's a true test of this sort of change in ideology or sort of this change in an approach to how we're doing science and space missions. And how long might they be up there if they have to have this backup plan? Well, if they're going to return home with the SpaceX mission, that flight is not scheduled to return until first. February. So they may be up there for a few more months. Now, NASA says that they are resupplying the space station with food and equipment. So they're not going to run out of provisions. But as they said that, you know, this is a crew that's initially supposed to be seven people. And right now there's nine people on the space. And so it's a little bit crowded up there. All right. Let's move from drama in space to drama at the Olympics. As I've been watching the Olympics, I've noticed how hot they keep saying it is there. I mean, that tennis.

match look grueling. And you have reported about how organizers are dealing with this. Please tell us about that. Right. You may recall the Tokyo Olympics back in 2021. Those were considered to be some of the hottest Olympics ever held on record. And organizers were paying close attention to the lessons that they learned there and were trying to make sure that they applied them to the Paris Games because they were concerned that it was also going to be extremely hot in Paris. Now, the organizers got a little lucky that the major heat wave in Europe and July sort of settled down a little bit before the games began, but it has been intensely hot. So one of the key things that organizers are trying, tried to emphasize with athletes was the role of acclimatization, basically getting athletes used

to heat before they arrive at the game. They put together a protocol for how to start introducing heat into your training regimen, and that includes practicing more outside. Or if you live in a cool weather climate to do things like wear extra clothes. wear extra layers and try to work indoors in a high humidity, high heat environment. And then they've also developed emergency techniques to help athletes who suffer from heat exhaustion, heat stroke, in particular the use of ice water baths that they're going to be using to treat anybody who does have heat stroke. So far, they haven't had to use that, but now they have this sort of emergency mechanism to help ensure that, you know, nobody gets seriously ill or

harmed by the heat. Speaking of heat, I mean, the next summary games are happening in L.A. in 2028, we can expect it to be pretty hot there too, right? Yeah, exactly. And so organizers are now contending with the fact that perhaps it's going to be really difficult to host the Olympics in any one city in particular because the conditions just won't be right. And so during the Tokyo Olympics, for instance, they held the marathon in Sapporo, Japan, which is about 600 miles north of Tokyo.

During the Paris Olympics, they're scheduling the marathon to begin at 8 a.m. on August 10. And so we're seeing a lot more of like the sort of rescheduling to the earlier and later times of day for these high endurance events. And increasingly for future Olympics, they're going to be taking more of these precautions and having to sort of expand the scope of where they can hold the games in order to keep people comfortable and safe and at their peak of performance. Right. Continuing with our human health theme this morning, it looks like the West Nile virus is gaining ground in the U.S. this week. What's happening? Right. Health officials have now reported cases in Massachusetts, in Wisconsin, and several deaths now, including a death this week in Dallas, Texas. West Nile virus is a virus that sort of springs up every now and then every few years. It tends to be concentrated towards the southern part of the U.S. But increasingly, we're seeing that the vectors, the mosquitoes that spread this disease are moving further and further north every year. While we don't see big outbreaks every year, the conditions get more and more ripe. Think of kind of like the conditions for a forest fire, the temperature and the conditions for breeding the mosquitoes become ripe, and then what it just needs is a spark.

And so we've seen this year, for instance, already big cases of dengue, which is also a mosquito-borne disease. And then last year we saw, you know, malaria being spread domestically in the U.S. for the first time in decades. And this is all part of a trend of, you know, people moving back and forth from areas where these diseases are endemic, but also the fact that we have such ripe conditions for mosquitoes to grow and spread, that it causes these diseases to, you know, gain ground and take root here in the U.S. over time. Let's move on to the Environmental Protection Agency this week, putting out an emergency order to ban a weed killer. Why did that happen? Right. This is sort of a rare move by the environmental

protection agency. They don't typically put out emergency orders, but they did for the this chemical known as DCPA or Dacthall. It's used to treat vegetables like broccoli. It's fairly common, but it can also cause birth defects and impaired development in children. It's made by a company called the Amvac Chemical Corporation. But the strange thing with this weed killer is that it's actually been banned in Europe since 2009. There's actually been a long history of reports of health effects from this particular pesticide. And the EPA says that it was actually waiting for the company to submit its own data about the health risks. And then after getting frustrated with the company for a period of time, decided to put out this emergency order and is now engaging in the

process of banning this permanently. So the Supreme Court ended the Chevron deference a couple of months ago, which could weaken orders like these from the EPA, right? How could orders like this be affected in the future? Right. So the Supreme Court decision on the Chevron doctrine basically undermines the deference that Congress tends to give to federal agencies to make rulings on specific chemicals like this. And so while the EPA could potentially still issue these kinds of emergency stop orders, it opens the door to litigation from the companies to try to push back or block these kinds of regulations or creates opportunities for them to weaken the EPA's ability to regulate these chemicals. And that is, you know, a major concern now after that decision, that a lot of the

regulations the EPA is imposing may not be guaranteed. Finally, some good news. Omer, let's get to that. There's no research out this week, and scientists have figured out a technique to regrow cartilage. Wow, we arthritics could certainly use that. How are they doing this? Right.

Well, that they've developed is this, what they call it, this bioactive gel that contains natural substances and polysaccharides, as well as synthetic structures. and what they do is that they are injected into the joint and they induce the cells in the cartilage to grow and provide them with scaffolding that helps provide the structure. See, the challenge with cartilage is that it typically isn't vascularized. It doesn't have blood vessels in it,

and so it's hard to get nutrients to the tissue. And the other challenge is that cartilage is structural. It has to hold up your knees, your elbows, and it's hard to, you know, just simply grow cells and have them be able to withstand that. And so what they've developed is a technique that doesn't use cells, but rather it uses, induces the cells already in the joints to grow and to rebuild itself.

They've tested this successfully in sheep, and they want to move this into human trials as soon as possible. And to wrap up, scientists are learning some new things about what the moon's atmosphere is made of. And yes, it does have an atmosphere. What did they find, Umair? Well, the Apollo astronauts who went there and scientists who have been monitoring the moon have, you know, notice that there is something up there. But the moon's atmosphere is so thin that they actually put in a different category called an exosphere. Basically, that it's so thin that atoms in the moon's atmosphere don't collide very often. And so it doesn't give us a lot of signal as to what they're actually made out of. But researchers started looking at soil samples collected during the Apollo missions.

And they found that historically in the early days of the moon, this atmosphere was seated by massive meteorite strikes. And then it's been continuously replenished by micrometeoroids. It's basically tiny rocks that are kicking up dust constantly into the moon and vaporizing it on contact. And because the moon's atmosphere is so thin, those meteorites don't vaporize. And because the gravity of the moon is so low, that dust gets kicked up really high into the moon's atmosphere. And that helps keep a thin layer of this sort of moon dust that sticks around the planetoid or the moon. Always interesting to have you on the show, Amar. Thank you for taking time to be with us today.

Well, my pleasure to be here, Ira. Omerer Fon, senior correspondent at Fox, based in Washington, D.C. This is Science Friday. I'm Ira Flato, live from the Chautauqua Auditorium in Boulder, Colorado. I have a prediction, something that every one of you did before coming here tonight. I know I did. And that was to check what the weather was going to be, right? My guess is that everyone here checked the weather.

And now most of the time, we can get pretty, accurate information about what the next few hours will look like, perhaps up through the next few days. But it's possible that in the near future, we'll be able to get accurate weather forecasts for maybe weeks or months. How about a decade ahead? Would that be cool? Seems like science fiction, I know, but my next guests are working on that very possibility.

Let me welcome both of them from the National Center for atmospheric research right here in Boulder. Welcome to Science Friday. Let me introduce both of you. Dr. Yaga Richter, lead of the Earth System predictability across timescales initiative. And Dr. Jerry Meal, senior scientist and head of the Climate Change Research section, welcome both of you to Science Friday. Thank you. Thank you. It's a pleasure to be here. Let me begin with you, Jerry. I know that Earth systems predictions is quite a mouthful, not only to say, but for a career field. What does this, what does it mean? in simple terms we can all understand.

Well, when you talk about Earth System prediction, you have to go back to the 1980s, really. And that's when we started using these, what we call Earth System models or climate models. And in the 80s, we had components of atmosphere, ocean, land, and sea ice. And these were basically computer programs that would communicate with each other.

And these computer programs are sets of equations, which for physics and thermodynamics and fluid dynamics. And for those of you who were forced to take calculus, the core equations in these these models are partial differential equations so you can numerically and mathematically integrate them forward in time. So that's how we make predictions with equations. And I still can't believe it works, but it does actually work. Unfortunately, I knew what you were saying.

You must have taken calculus. I did. I took calculus. And so you can actually make the mathematics string together equations to predict what's going to happen, you think. So when we first started using these Earth System models in the 80s, we were doing an experiment where we'd start the model out from some states, say pre-industrial state, 1850, for example. And then you'd integrate the model forward in time. And as various things happen, you'd add the ingredients as the model is going forward.

So if a big volcanic eruption went off, you'd put the effects of the eruption, the equation that'd handle that. Greenhouse gases were increasing. You put the increases of greenhouse gases in that equation as you're going forward in time. You can put in solar variability. That's another natural aspect of the climate system that affects the outcome. And you would go through the 20th century and you get to the end of the 20th century. and you get to the end of the 20th century and you'd see whether your model could predict

the average climate that we actually observe. And if you didn't, if it didn't look like planet earth, you go back to the drawing board. But usually these models actually, even the early ones, did a pretty good job in getting the features of the climate system. So you get to the present day and you say, well, what about the future? We don't know what's going to happen in the future. So we have to come up with scenarios of different possible outcomes

involving maybe future demographics or economic activity or energy sources, technologies, could come into play. And so there's a whole community of scientists that come up with these emission scenarios, we call them, and they give you emission pathways of future emissions of greenhouse gases. So you can run this same Earth system model into the future with the ingredients now being these future emission scenarios. So you get a range of possible outcomes.

And usually what we did, and we still do this, actually, we'd say climate change is the climate change you get at the end of the 21st century compared to pre-industrial, compared to the before the Industrial Revolution started. And so we were doing, we still do this. But around the turn of the century in the early 21st century, stakeholders were saying, you know, that's great. You guys are doing this end of the 21st century thing. But we really are interested in what's going to happen in the next few seasons,

the next couple years, the next 10 years. What can do about that? Well, that then started us on a whole new area of climate science. We started using Zer system models in a new way. And the way we are doing this now with these climate predictions is we start the model out at a specific point in time with some of state of the system like today, take atmospheric and sea ice to the observed state, start the model out, integrate it forward in time for 10 years, and try to predict the time evolution

of regional climate as it's happening. I want to get into that a little bit more later about exactly what you do, but I know that that, that, Yaga, you, you work on a different time scale, right, than what Jerry is does? What, what time scale are you working on? That's right. So I work on a subseasonal time scale, which is usually considered a couple of weeks to a few months. And it's a much, it's a harder time scale because they often call it the

predictability desert. So it's, why is that? Because it's really hard. We still don't understand the sources of predictability. So we know for the weather forecast, the primary source of predictability is the initial state of the atmosphere. And as Jerry explained for the longer forecast, there's greenhouse gases and changes in sea surface temperatures. So we're looking at things like interactions with the land, interactions of the oceans, the role of aerosols, the role of the upper layers of the atmosphere like the stratosphere. So how much predictability can we get from these sources? But this subseasonal time scale, it's a little bit of a mystery. So we're still trying to understand what are the key drivers in this space and makes it a very challenging problem.

And you're more reliable than Jerry is because Jerry gets wrong. No one's going to know it for decades. That's right. You're not right. We'll know it next week or in a couple of weeks, right? If a heat wave comes and you don't have snow skiing, yes, you're going to come after me. And Jerry, how satisfied would you be? What record of predictability would you think would be good at the beginning of this research? Well, the way we try to check out these models is we go back and we call them Heincast. You start the model out in 1967, run it for 10 years to 1977, and see if you could capture anything that actually happened during that time period. We can do that with climate information.

So you give probabilities of certain outcomes happening at certain times in the future. But, of course, we're trying to improve the models. We're trying to understand what is we're trying to predict. And since the first paper on this was just published in 2007, this is still really a new area of climate science. And the stakes are high, right? Because on the 10-year time scale, this is what we have to adapt to. And these Earth System model predictions are the only way we can get information on what we're going to have to adapt to. Well, let's talk about exactly what factors go into that prediction.

And I'll ask you, Yaga, what factors, oceans, atmosphere, What kinds of things do you plug in there? We apply calculus and lots of equations, and we need to use a supercomputer to solve the equations for temperature, wind, precipitation, et cetera. So you need all those factors, how the land works, the ocean, the atmosphere, the soil has parts to play here? Yep, and also the humans, right? Because humans are responsible for the emissions,

and they're also responsible for planting crops. So if you replace grass with urban and cities, that also has two-way feedbacks onto the system. So we try to capture as much of that, but the more complex you make the model, the longer it takes to run. So there is a little we have to play the game of resolution versus complexity.

And Jerry, who would benefit mostly from these long-term predictions? Well, when you think about these longer-term predictions, agriculture is always one that people say, and water resource managers, the Colorado River Basins, a big one now. They really would like information on what the climate is going to be.

like five to ten years from now. You can imagine infrastructure planners, people designing buildings, if the winds or temperature are going to change over the next three to five years, they need to know that. If you're going to deploy clean energy technologies, for example, if you want to put a wind farm out there somewhere with wind turbines and the wind patterns are going to change if they're not going to be the same. And five to ten years from now, you want to know that. So you want to have optimally able to cite them. Solar panel, same thing. It's going to get cloudier in a place or clearer in a place. In three to five years, you want to know that. I mean, there are things happening now.

We never thought might change the weather. The forest fire soot and the smoke and things like that. Do you have to add those now more into your models than you thought before? Yeah, so actually in our institute, John Fasulu, another researcher, did a study just very recently with the Australian bushfires. And he showed that they were affecting all the way to the tropical Pacific influencing Lanina, which is one phase of the ensue isolation. So these fires can, the smoke commissions can travel around the world and impact places that we never thought of. And what about the melting glaciers? Jerry, they're going to change possibly the currents that flow around the world.

Do you put those into the long-term predictions? So the biggest concerns, of course, the big ice sheets, the Greenland Ice Sheet and the Antarctic Ice Sheet, behaving in ways that humans have never observed because humans have never been around when the ice sheets were really melting like this. So people that study ice sheets are trying to figure out what this means for what they're seeing now. I think, yeah, when you go into this kind of uncharted territory, you have to really be trying to understand what processes are going to affect things and try to capture those in these prediction models. Plus, we're also going to see crops moving, right?

The crops are going to follow where the weather changes as the climate changes and diseases changing and vectors moving around. These are things I'll bet you never thought about when you got into this business. That's right, and people are going to react differently to the forecast, right? So as the climate changes, people are going to take different actions, and we need to account for that in our models as well. And how do you do that? So we work with different individuals from different sectors

who study human behavior, and we need to try to project the human behavior and then put those processes into the model. But that is very new, right? Those human interactions were not in our models up to a few years ago, and we're just at the beginning of putting those in there, especially at the urban scales, right? Oh, certainly.

at the scales of cities where people are replacing grass with buildings, et cetera, that has tremendous impact on the local weather. So we can model some of these things. But we have enough trouble trying to predict the physical system to predict how humans are going to react because then geopolitical systems come into play and it becomes a lot more complicated. If you had a blank check and you wanted to spend it on your research

to find out something you don't know and you could spend it anyway, how would you spend it? So we would need at least a billion dollars. A billion? That's not a lot. It's not a lot. Not in these days. But we would spin it, I think, in multiple ways. So first, we would hire more machine learning and artificial intelligence experts.

AI. AI, because AI is really grown in our system science in the last few years. So those scientists are helping us identify sources of predictability. Then we would need to buy a bigger supercomputer because if we go to higher resolution, we do believe we can resolve more of the relevant processes and produce a better forecast. And then we would need to have more observations, of the area, of the parts of the Earth system that we don't have. The deep ocean is not observed, so not very well.

So therefore, if you start your model with limited observations, your forecasts are also not very good. Jerry, you got that big check? What do you do with it? She has the last word on this because she was just at a workshop this last week where she was asked that question. Is that right? They stole my question?

She was actually told by a program manager to ask for a billion dollars. Okay, there you have it. Last word, I want to thank both of you for taking time to be with us today. Dr. Agha Richter, lead of the Earth System Predictability Across Times Cales Initiative, and Dr. Jerry Meal, senior scientist, head of the climate change research section. Thank you both for taking time to viewers. And that's all the time we have for it today. Lots of folks help make the show happen, including

Sandy Roberts, Beth Rami, John Dancosky, Daniel Johnson. Next time, we'll talk about why a record-setting $44 million sale of a Stegasaurus fossil is worrying paleontologists. But for now, I'm SciFri producer D. Peter Schmidt. See you then.