D (3:08)

Something you Should Know Fascinating intel, the.

B (3:11)

World'S top experts and practical advice you can use in your life today. Something you Should Know with Mike Carruthers hi, welcome to Something you should Know. Quick question for you. When was the last time you looked at your phone, checked your phone for something? I'll bet it was minutes, maybe even seconds ago. The smartphone is a wonderful device. It saves us so much time or does. Also seems to occupy a lot of our time and attention, making it perhaps as big a time waster as it is a time saver. Here are some of the latest statistics regarding cell phone use today. Americans check their phones. How many times would you guess the typical American checks their phone per day? 144times 89% of Americans say they check their phone within the first 10 minutes of waking up. 75% of Americans feel uneasy leaving their phone at home. 75% of people check their phone within five minutes of receiving a notification. 75 75% of people use their phone on the toilet. 69% of us have texted someone in the same room. 57% of people consider themselves addicted to their phones. 55% of people it's more than one out of two say they've never gone longer than 24 hours without their cell phone. And 47% of people say they feel a sense of panic or anxiety when their cell phone battery goes below 20%. 46% of people look at their phone while on a date and 27% of people look or use their phone while driving. And that is something you should know.

A (5:09)

It's Marie Antoinette Month on the Vulgar History Podcast. Every week in September, we will be talking about the notorious French queen. Why is she still talked about today?

C (5:18)

Did she really say let them eat cake?

A (5:20)

Spoiler she did not. Why do people still think she deserved.

C (5:23)

To have her head cut off?

A (5:25)

We're going to be taking a deep dive into Marie Antoinette's life and world to try to answer the question, how do you solve a problem like Marie Antoinette? Listen to Vulgar History Wherever you get.

C (5:34)

Podcasts.

B (5:39)

If you were to search for books or webinars on the topic of decision making, you'd find a lot of them. If you were to search the website for this podcast, you'll find we've discussed the topic of decision making five or six times in the last three or so years. It's as if we need a lot of help making decisions and that we're somehow not particularly good at it. And that's why we need all these books and webinars and podcasts and maybe for those big important decisions like who to marry, which house to buy, what job to take, maybe a little help can be beneficial. But actually, when you think about all the decisions you make every day, and you make a lot of them, you do just fine. And in fact, most of them don't really matter all that much. To understand what I mean and why this is important to you, I want you to meet Annie Duke. She's a speaker and consultant on the topic of decision making. She's a former professional poker player and she is an advocate in the world of decision making. She is an advocate for people giving themselves permission to quit things more often. She's the author of a book called how to Simple Tools for Making Better Choices. Hi, Annie. Welcome to something you should know.

C (6:57)

Well, thank you for having me, Mike.

B (6:59)

So, as I said, you could get the sense from all the books about the topic that we're not very good at decision making, that we're terrible at it. Are we terrible at it?

C (7:09)

Look, if we were really terrible at making decisions, our species wouldn't exist. The issue that we have is that we have all these ways that we make decisions that work. Most of the time, they're pretty good. The problem is that there's a whole set of circumstances under which they don't work, which would be true of kind of any rule of thumb. So there are certain heuristics that we use in order to make decisions. There are biases that we have in the decisions that we make that cause us to make poor decisions under certain and predictable circumstances.

B (7:49)

So I remember hearing once, and I always thought this was interesting, that in many cases it isn't so much what you decide as your commitment to your decision, that whatever you decide, if you commit to it, rather than second guess it after the fact, that. That you'll be a lot happier and content.

C (8:09)

Yeah. So it's an interesting trade off. And B, I think it depends a little bit about what arena we're talking about. I think in general, for things like marriage, which is supposed to be a lifelong commitment, getting married and then immediately starting to second guess that would be bad for your happiness. I think that's absolutely true. So you definitely don't want to second guess things too much. I think that in general, like, you know, if you go to college and you're constantly second guessing your choice of college. For example, you're going to be less happy if you take a job and you're constantly second guessing the job that you take. You're going to be less happy. That being said, there's a flip side to that, which is that we don't want the second guessing to go to zero. And the reason that we don't want that to go to zero is that we when we choose to do something. So let's say we choose to take a job, right? Remember I said every decision is a forecast. We're choosing to take the job under conditions where we don't have a lot of information. We've done some interviews, we've researched the position and the company, talked to a few people who are there, gotten some vibes, and we decide to take the job. Right. But what do we really know about what it's going to be like when we're actually working there? We don't know a whole lot. So one of the things that we want to think about when we're entering into something is that that decision should not be treated as last and final. It should be the thing that I'm doing now, but I need to think about what are the signals that would tell me that this was a choice that I would prefer to change. Right. So in other words, we don't want to live a life where the first job we take is the last job that we ever do unless we happen to get fired from the job. We need to realize that we do have the option to quit, to change and go do other jobs. So you need to get a balance between committing to the thing you're doing, but also paying attention to the signals that that job might not be for you.

B (10:14)

It seems an important element in decision making that maybe doesn't get talked a lot about is timing. That you have to make a decision about something, but you also have a time limit because if the time expires, the decision doesn't matter. Some people take a long time to make decisions, other people make them quickly. What do you think in general?

C (10:36)

I think that people decide too slow. But stepping back from that, every decision is not created equal. And we need to understand what are the types of decisions that we should be taking our time on and what are the types of decisions that we can go pretty fast on. And if we can understand that, we can actually get to a better balance. So the types of decisions that we can go really fast on are ones where it's okay to make a mistake. And why are those two things connected? Well, because the faster that you make a decision, the more likely you're going to introduce error into the decision. So when you're making decision, that isn't going to matter much to your happiness in the long run. That's when you should go fast. So an example would be, and this is something that people often take a lot of time on is ordering off a menu. So, Mike, have you ever maybe you're somebody like this, or do you know people like this where you go to a restaurant and they're looking at the menu and it just takes them forever to decide what to eat?

B (11:37)

Drives me crazy.

C (11:39)

Right? Like, it's particularly bad if you're, you know, at like the Cheesecake Factory, which I think has like a 20 page menu or something.

B (11:46)

Exactly right.

C (11:47)

But even if you're, you're at a place with a relatively small menu, people tend to really, really struggle with that decision. And I think that part of the reason that people struggle with that decision is that pretty quickly after you order, you're going to get whatever it is you ordered, and it's either going to be good or bad. And when it's bad, you're going to feel like you made a mistake. So what they're trying to do is to get to the right choice to avoid that feeling of, I made a mistake because I don't like my food. But of course, we have to remember every decision being a forecast, that first of all, there's no way for you to know whether your dish is going to be great or bad in advance of getting it. So you're just having, you're making your best guess. And if it turns out the chicken is dry, it doesn't mean you made a mistake. But more importantly, the reason why we shouldn't take a lot of time on that decision is because it doesn't really matter, not in the long run. So, like, Mike, I mean, I can ask you this. Like, let's say that we go to lunch and you order something and it turns out that you don't like your lunch very much. If I catch you a year later, after we've had that meal, and I say to you, you know, hey, just catching up with you after a year. The last time I saw you was at that lunch a year ago, and you didn't really like it very much, how much did that meal affect your happiness over the course of this last year? None. Now, what if I see you a month later and I say, hey, it's been a month since we had that lunch. Like, how much did that lunch affect your happiness over the last month?

B (13:21)

Yeah, not much.

C (13:22)

No, not much. And even if I see you a week later, you've had 21 meals since then. In other words, it's a decision that makes no difference. Right. Like, we feel it really keenly in the moment, but it's actually very low impact. So what we want to think about when we're deciding, like when should we take our time versus when should we go fast? Is not this fear of getting a bad outcome and feeling like you made a mistake. It's, is it something that's going to matter? Because if it's not going to matter, it doesn't really matter if I got a bad meal. So we should be thinking about impact. So that's sort of piece number one, is that most of the decisions that we make are actually pretty low impact. They don't. They're not really going to have high effect on, like, our overall happiness over the course of our lives. They're pretty low impact. So just go fast on those things. And the things that are high impact, like, you know, the way the, the. The thing that I like to think about. Are you dating or are you marrying? Right. If you have a bad date, it's not a big deal. If you have a bad marriage, it is, right? Are you hiring an intern? Are you hiring a cfo? If you hire an intern who doesn't work out very well, so what if you hire a CFO that doesn't work out very well, that's a really big deal, right? So, like, whenever you're in this sort of dating category or the intern category, just go fast. It doesn't really matter. But when you're in that CFO or marriage category, those are rarer decisions. That's when you should actually slow down.

B (14:50)

We're talking about decisions we make and why we spend a lot of time on making decisions that don't really matter much. My guest is Annie Duke. She's author of the book how to Simple Tools for Making Better Choices. Does it ever feel like you're a marketing professional just speaking into the void? Well, with LinkedIn ads, you can know you're reaching the right decision makers. You can even target buyers by job title industry, company seniority skills. Wait, did I say job title yet? Get started today and see how you can avoid the void and reach the right buyers with LinkedIn ads. We'll even give you a $100 credit on your next campaign. Get started at LinkedIn.com results, terms and conditions apply.

C (15:35)

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B (15:37)

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C (15:56)

Strayer University is certified to operate in.

B (15:58)

Virginia by Chev and has many campuses including at 2121 15th Street north in Arlington, Virginia. So Annie, I find often in making decisions where you speculate like if I did this, then this could happen or that could happen, that none of those could happens, ever happen, that it's always something else. And it, it may be good, maybe bad, but you spend a lot of time imagining the possibilities and it seems like almost never do those possibilities materialize.

C (16:31)

Yeah. So first of all, one of the problems that we have as decision makers and it kind of goes back to that idea, you know, when I said the thing that's really hard for people when they're ordering from a menu is that they're afraid that the meal is going to be bad. One of the biases that we have is called loss aversion. And what that means is that when you're imagining the possibilities that are going to occur in the future, you tend to be more focused on the bad things that can happen than the good things. And when you get more focused on the bad things that happen, you can see how that would cause paralysis. Right. Like this very slow decision making because you're so concerned about quote unquote getting the decision. Right. So, so that's one piece of that imagining of the future. Look, here is the fact is that when we're making decisions at the moment that we make decisions, the decision we know very little in comparison to all there is to be known. That's just the state of being human. And there's going to be an influence of luck on the outcome. So even in the situation where we know everything we need to know, like we have a coin and we've weighed it and we know that it's going to land heads 50% of the time and tails 50% of the time on a single flip, we still don't know what's going to land. Right. Because that, that's just under the influence of luck. But because we know very little in comparison to all there is to be known, we actually don't even know if the coin is two sided. Right. We don't know if it's a fair coin. Maybe, maybe it's not a fair coin. Maybe it's got three sides or four sides. Right. Like, we're sort of guessing at those kinds of things. So you're right. When we're imagining the different outcomes that could occur, generally depending on how much luck is involved, depending on whatever sort of our informational state is, there's going to be a range of possible outcomes that could occur and each of those outcomes is going to have some probability associated with it. But we're only ever going to observe one of those outcomes, which means that most of the outcomes that we're imagining aren't going to happen. And that's going to be more true the farther out into the future that you go. So if I'm trying to predict something that's going to happen in the next minute, I'm probably going to be pretty good at that. If I'm trying to predict something that's going to happen in a year or two years, most of the things that I'm guessing at aren't going to occur because there's such a big range of things that could occur as you get farther out into the future. But what's really important, though, is that doesn't mean that you shouldn't try to predict because you should. You should try to predict because you still have to make a decision that's your best guess. The important thing is I make a decision that's my best guess about all the things that might happen, say in a year. But then as I accumulate more information, then I will change my guess because eventually that thing that I was thinking about that might occur in a year is only going to be a week away. Right. Like, you know, as I get out, you know, 51 weeks into the future, it will only be a week away, at which point I should be updating what my prediction was. But that's just, you know, the state of being human. But it doesn't mean that you shouldn't be trying to forecast what those outcomes are because it's still going to make you a better decision maker.

B (19:53)

But it seems that also that your temperament has something to do with what those outcomes are. That if you're a pessimist, you're going to be looking at the, you know, the worst case scenario. If you're an optimist, you're going to be that everything works out. It doesn't really matter.

C (20:09)

Oh, absolutely. So, you know, with loss aversion, people tend to focus on the downside. They tend to focus on, like those bad outcomes that might occur. Obviously there's also the other problem, which is people tend to be overconfident and overly optimistic. So we, we will often estimate our chances of success as much higher. We know that that's a problem as well. So overconfidence is just a really huge problem. Both of the problems, if we're sort of in the pessimistic side where we're really just think, you know, we're really just focused on the downside outcomes that could occur, or we're, you know, overly optimistic or overconfident, or where we're really overestimating the chances that good things can happen, it's going to mess our forecasts up. So whichever bias you're subject to, you actually want to get a better view of what the world might hold for you. And one of the best ways to do that is to get somebody else's opinion. So we're subject to these biases where we might overestimate the chances of good stuff happening, or we might be particularly risk averse and afraid of the bad things that are happening. But those are, those are biases that we have for ourselves and our own decisions. So one of the best things that you can do is go find yourself a mentor or someone to help you out and sort of explain what the decision is that you're facing and ask them what they think the possible outcomes are and what options they think that you should be considering because they'll generally see the world more clearly than you see yourself. There's just all sorts of evidence that shows when you look at people giving other people advice, the quality of the advice that they give to other people is much higher than the sort of what we consider the quality of the advice that you give to yourself. So we should be seeking out people to give us advice to help with the advice that we're giving ourselves.

B (22:04)

Well, I mean, that is so apparent when you look at somebody who's struggling with a decision, struggling with a problem, and to you the answer's so clear. But when you have something similar, that same kind of problem, you struggle as much as they did because it's you, it's your, it's you on the line.

C (22:25)

Yeah. And there's recent research that actually shows that when people are struggling with a really hard decision, if you have them go give advice to somebody else who's struggling with the same decision, it helps them with their own decision. There's something about, as you just said, like giving advice to somebody else, it's not your struggle anymore, and that allows you to see it so much more clearly.

B (22:48)

You know, I can think of decisions I've made and I'm sure other people have this experience that you, at the time you're making the decision, you think like, this is it, like there's no going back. But so many of the decisions that we make, we can undo them later if they didn't turn out right. Right.

C (23:08)

You know, once we start something, we think that stopping it is like a failure. It's a sign of being weak willed. Like, we all know that grit is a sign of character and we should stick it out and show our mettle. Right. We should be courageous and keep going. But there's so much science that shows that we don't quit things soon enough. And I think that one of the ways that I can get at that, Mike, is like, think about some big decisions that you've made where you did finally quit something. As you think about that set of decisions, would you say that for the most part after you finally quit, you think, oh, I should have done that a lot earlier or for the most part, do you think, woo, I did that too soon?

B (23:57)

Oh, I would say, you know, wish I'd done that earlier.

C (24:00)

Right. And I think that that's true for most people is that we feel like, oh, I wish I had done that earlier. And I think the problem is that kind of to the point of what we were talking about before, about wanting to get to that certainty before you're willing to make a decision, is that once we start things, we don't want to quit unless we're certain that we have to. Because it does feel like such a failure to us to actually walk away from something that we don't want to walk away from it unless we know that we didn't have any other choice. But if we didn't have any other choice, that's way past the point that you should have walked away. So I think that people need to get better at saying, like, look, when I make a decision to start something, I'm giving it my best guess as to whether I'm going to like this job, for example. But then after I've started the job, there's all sorts of signals that could happen that would show me that this isn't the job for me. You know, my boss could be toxic or the hours might not be good, or people are emailing me constantly on Sunday and that's not really what I wanted in a job. And I didn't think that that was going to be the case. But now that I've discovered it, it's okay for me to leave.

B (25:09)

Well, as I listen to you talk, I can think of several decisions, many decisions that I've made in my life that seemed really so important at the time but have had no lasting effect on my life or my happiness or anything. And I think that's so important to keep in mind that so many of the decisions that we make that we agonize over just don't really matter that much. I've been speaking with Annie Duke. She is a speaker and consultant on the topic of decision making. She's a former professional poker player and author of the book how to Simple Tools for Making Better Choices and there's a link to her book at Amazon in the show notes. Thanks Annie. Appreciate you coming on.

C (25:53)

Thanks Mike. This has been super fun. Really happy that you had me on.

D (25:57)

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B (27:00)

One thing that affects you every day to some degree is the weather. It dictates what you do or don't do, what you wear or don't wear when you leave, when you come home. Weather has a huge impact and it frankly can be fascinating to watch it and witness it, both the beauty and the destruction it creates. To help you better understand how weather works and how science works with it is James Marshall Shepard. He is a professor of Geography and Atmospheric Sciences at the University of Georgia, past president of the American Meteorological Society, and host of the Weather Geeks podcast. Hey James, welcome to Something youg Should Know.

D (27:42)

Hi, thanks for having me.

B (27:44)

So let's start with how our knowledge of weather has changed in our ability to forecast it and really understand it. Is it getting a lot better? Is it pretty much the same as it's been for several Years or what?

D (27:57)

No, it's changed. It's light years ahead of where it was even 5, 10, 20 years ago. I mean we are about 90 to 95% accurate five days in on most weather forecasts. Most people jokingly say that we're wrong about weather forecasts a lot and we're not. That's a human perception issue because people tend to remember the occasional miss and, and, and forget the 95% of the days that were correct. So that's something we deal with in our profession quite a bit. But if you just look at things like how far out we can predict the path of a hurricane now, five to seven in cases of sand. Hurricane Sandy 9A one day, I'm sorry, a three day forecast for hurricane track today is about as good as, is about as good as a one day forecast was in the 70s. You rarely see airplane crashes anymore because of wind shear microbursts that we used to deal with in the 70s because we have terminal Doppler radar and very advanced weather radar systems. We've got advanced models and satellites. We're really in the golden age of weather forecasting in terms of our ability. I mean from where we were in the 70s and 80s. And I think we're about to take another step forward with the introduction of artificial intelligence and machine learning techniques in our weather forecasting as well.

B (29:15)

And when weather is forecasted, when, when meteorologists look at the weather and go, okay, so looking at this, we can tell that in three days from now it's going to be sunny and 75 degrees. What goes into that equation?

D (29:29)

Yeah, it's not what people think. I think people think we put our thumb in the air and wet, wet our, just look at how it's shifting from west to east. It's not done that way at all. And we use very complex geophysical fluid dynamics models, computer models solving very complex equations. The atmosphere after all is just the fluid. It's just like water in a pipe or a river. And so it's governed by complex equations. And so we can actually solve those equations on a set of grid points and very fast supercomputers to predict how that fluid changes. One day out, three days out, seven days out, ten days out. And from that information we take information from the observations from the weather balloons, from aircraft satellite, we initialize those computer models and it predicts a future state of the atmosphere in terms of its wind patterns, its moisture, and that's how weather forecasts are made. I often ask that in my public engagements as well. I asked people how weather forecast made. And generally people have. The two things that I notice is that people have no clue. They, they say everything. That's not what we do. And they also confuse things like percent chance of rain. They usually don't know what that means as well. So it's, it's really to most people a black box because these days they just either pull it up on their television or pull up an app. But there's a lot of physics and calculus that went into what they see on that little icon on their app.

B (30:53)

So explain some of those terms because we hear, you know, like, what's the difference between partly cloudy and partly sunny? And what is the chance of rain really mean? Explain some of those terms. Sure.

D (31:06)

Well, these are just sort of back end terms used for communication. I mean, partly cloudy and partly sunny are based on the percent cover of the sky that has cloud cover. You know, less than 10% is actually clear, greater than 90% is actually cloudy or mostly cloudy. And then in between those ranges of cloud cover you get partly cloudy and partly sunny.% chance of rain is a way that we try to characterize rainfall because you can't predict specifically where rain is going to fall as a very sort of statistically variant property. In other words, on a hot summer day here in Georgia, the hot temperature is probably similar in Atlanta as it is in Athens, Georgia, where the University of Georgia is. But rainfall can be a lot more sporadic and variable. And so the way we try to convey it is in probability. And so people will say, well, what does 40% chance of rain mean? The way I try to convey it is that really is the confidence that we have in our forecast that 40% of the forecast area for the National Weather Service that covers that region will receive rain. And so when someone says, well, it was supposed to rain today and there was only a 20% chance of rain, they got it wrong. That's just a baffling statement to me because there was a 20% chance of rain that was, there was some confidence that 20% of that area was going to receive rain. And you happen to be in that 20% of the area that day. We have to do the same thing with hurricanes. We often show the hurricane cone of uncertainty, that little cone or triangle that's approaching the coast. And that's because the models will give you a range of understanding. And so there's variability, so we can't tell you the exact line that that hurricane is going to take without some uncertainty around it. So that cone of uncertainty tells you that there's a 66% chance that that hurricane can be anywhere in that cone. It doesn't have to be right down the center as most people perceive that to be. So one of the merging areas within meteorology is social sciences of weather forecast. And it's how people consume this information because we've actually gotten pretty good with the actual weather forecast, the model forecast, the radars and satellites. But people still have trouble perceiving a lot of the information or they put their own interpretations on it.

B (33:23)

So time is a big factor, right, because you can predict tomorrow's weather pretty accurately.

D (33:27)

You can't predict, you can't predict the.

B (33:30)

Weather two weeks from now anywhere near as accurately as you can predict the weather for tomorrow.

D (33:36)

Well, that's out to about seven to 14 days. We have some degree of predictability and that's because the weather models start to sort of lose some of their sort of influence of the initial starting conditions of the model. So again, we run these computer models, we run them out one days out, 10 days out, even in some cases, 13, 14 days out. And the further away you get from the initial condition, some of the physics starts to break down some. So indeed, a 10 day forecast is not going to be as accurate as a two day forecast. But these days, out to seven to 10 days, we're pretty darn good. I mean, I would say we probably hit about 9 out of 10 times, even in some cases, cases out as far as seven to ten days.

B (34:23)

And when that one out of ten times you're wrong. What typically goes wrong?

D (34:30)

Well, a lot of things could go wrong. One, the model, I mean, we have to, we don't have. You think about your smartphone that you have in your pocket. The more megapixels the model the phone has, the better the picture will be on the phone. Well, the same thing with our computer models. The more grid points on that computer model, the more accurate we can predict things like a rainstorm or a wind gust. But our models or computers sometimes aren't fast enough for us to get down at that level of fidelity to maybe resolve some of the weather processes that are actually happening. So it's usually either related to a model not having enough resolution or in some cases in those computer models, we have to do something called parameterization. That's a big fancy word. It just means we can't really see the cloud. So we just assume a cloud is there if the relative humidity that's spit out of the model is above a certain level. That's just one example of a parameterization. Or you could have bad data going in. You don't have enough initial data going in that resolves what was happening in the system. We understand the reasons that there are misses. The other big reason is that the atmosphere is very non linear. In other words, A doesn't necessarily need to B or C or D in the way our minds think. Our brains think very linearly, but our atmosphere doesn't. You may have heard of something called chaos theory, this idea that a butterfly flaps its wings in the Amazon and it can change a hurricane thousands of miles away. That is to some degree a part of the non linearity of chaos theory in our atmosphere. And we, our models just don't always get that right. But I want to sort of end this part of the discussion by noting even with all of that, our weather models are very good within zero to 10 days. Just don't fall for the tendency that we human beings tend to do, which is if our picnic got rained out by a bad forecast, that one bad forecast is concluded to mean that all forecasts are bad. In fact, most of them are good. You just remember the one that impacted you.

B (36:34)

So talk about extreme weather because we hear stories, we see stories on the news of, you know, forest fires and big snowstorms and things. But statistically, overall, because I was just reading an article about in the Washington Post about temperatures in the 1930s which are hotter than they are today. So it seems like it could.

D (36:54)

Yeah, that article is being misused. I'd be happy to speak on it because we are definitely warmer today than the 1930s. People bring up the 1930s in a dust bowl as an isolated example. But I just wrote an article in Forbes about this. In fact, we just lived through the warmest July on record. That means since we've been taking records, of course there have been hotter times in the Earth's history. So it's a very complicated discussion, but it often gets oversimplified and then people mischaracterize, sort of the understanding of how climate is really affecting us.

B (37:27)

Has the weather around the world ever been, you know, different in the sense that, you know, we have a climate in North America, you know, the west is hot and New England is, you know, wet and green. It is. Has it stayed pretty steady or not?

D (37:44)

No, I mean, our climate is changing and we know that as a fact. Now again, as a climate scientist, it's bizarre. But I do get people that come up to me and say, well, climate change is natural. You've always had hurricanes. And I said, I promise you, I didn't Miss that. In my graduate courses, of course, there's naturally varying climate in the same way that grass grows naturally. But when we fertilize our lawns, it grows different, differently. So we've had a naturally varying climate system for millennial millions of years, but in the last, say, 150 years since the Industrial Revolution, we've got a human steroid on top of that naturally varying climate system. And so I, I co authored a study for the National Academies of sciences back in 2016, where we looked at something called attribution. What does that mean? It's the part of science, climate science, that tries to understand how we can pinpoint the DNA of climate in today's weather. So to answer your question, we know for a fact the data shows this, multiple studies, that the heat waves are more intense and frequent than baseline heat waves of the past. The intense rainstorms rain with greater intensity. And that's basic physics because as the atmosphere warms, it can hold about 6 to 7% more water vapor for every 1 degree. So that's just a basic physics principle rooted in something called the Clausius Clapeyron relationship. Again, a big fancy equation that basically says the hotter it is, the more water vapor the atmosphere has available to it. And we can experience, we know that from our own experience, it's hotter and more muggy and humid in the summer than it is in winter in most places. So as our climate system is warming, there's more water vapor available to these rainstorms. The ocean temperatures right now, as we speak are just unbelievably hot. I mean, running well above baseline temperatures we've seen. So when hurricanes move over that hot water and form, we are seeing a generation of what we call rapidly intensifying hurricanes, and they just kind of explode. You go to bed to a Category 2 hurricane, and you wake up 24 hours later and it's Cat 4, the basics of weather.

B (39:46)

Like, you know, like, I guess I've never really understood, like, what's the difference between hail and sleet and snow? I mean, what are the differences?

D (39:56)

Yeah, well, they're very different. And again, it's one of those things. As a meteorologist, I have fun with people all the time because I've written articles in Forbes on misperceptions about weather, and I usually include that one. So, for example, hail is. Doesn't happen in winter for the most part. Hail is typically associated with big thunderstorms that you get in the spring and the summertime. So you get these big sort of ice balls that sort of Traverse up in these large thunderstorms and they take on more water and freezes, and you get these hailstones. So fundamentally, hail is associated with thunderstorms. And so thunderstorms typically happen most in the spring and summer. Sleet is more akin to snow and in perhaps some cases, rain. So essentially, all rain starts as snow and clouds. In the United States, that's, again, that's something that's a little counterintuitive to people. But even on a hot summer day, 85 degrees up in the cloud, it's very cold, it's well below freezing. And the processes that cause rain starts to snow. So that snow falls out of the cloud. If it's below freezing, as it falls to the ground, it remains, it's snow. But on a hot summer day, as it falls out of the cloud, it melts, and you just see it on your picnic table as rain. Now, there are certain situations in the winter where it can start out as snow. It may melt some on the way down because it encountered a warm layer and then a cold layer beneath that. And so it refreezes. And so you get these little ice pellets, and that's what we see as sleet. So whether we get snow, rain, or sleet depends on what the temperature is like at the top of the cloud, in the base of the clouds and all the way down to the ground. There's. There's some cases, some what we see here in Georgia in the wintertime, it can be rain that falls to the ground, but then right at the ground, the temperature is below freezing, and so then it freezes. And we call that black ice or freezing rain. So, yeah, there are all kinds of things. One that will probably shock and pun intended many of your listeners is there's no such thing as heat lightning. I hear people all the time say, oh, my grandma told me that that's heat lightning. The heat of the day is causing the air to flash. There's no such thing as heat lightning. It's just when people see thunderstorms that are well off into the distance, but it's too far away to hear the thunder because, of course, light travels much faster than sound.

B (42:18)

So can you explain? I've often wondered about this. If you look at, like a. The Earth from a satellite, you see the clouds and they move, you know, from west to east and they go around the earth. So why isn't the weather more homogenous all around the world? Why is the UK so wet? Why is the southwest of the US So dry? If the clouds are just Circling around the Earth. Why doesn't everybody more or less get the same thing?

D (42:47)

That's a great question. It really takes about a semester of dynamic meteorology to really answer it. But again, these cloud, clouds are moving around the planet because of a series of waves. If you were could really look at the motion of the atmosphere. It's moving in these large wave patterns, and these wave patterns in these troughs and ridges in these mountains and valleys in those wave patterns. The valleys, if you will, tend to be associated with rainier conditions. The ridges or peaks in those wave patterns tend to be where we see hot, dry conditions. So, for example, much of the United States, south and Southwest is in a regional bad heat wave this summer. It's because we're stuck under one of those ridges of high pressure. So the location of those ridges and valleys in the jet stream pattern is one reason there's variability depending on where mountain ranges or warm ocean currents are that moderates and changes weather patterns as well. So you've got these, what we call large scale features like jet stream patterns and waves, ridges and highs and lows. But then weather is also governed by sort of more regional or local scale effects. So for example, any listeners that live near a beach or a coastline know that on certain days every day it rains at about 3 or 4 o'. Clock. That's because of the sea breeze front, though. The land heats up faster than the water, and so the air over the land rises and you get cloud formation. And so there's a circulation called the sea breeze. You can have very similar type of circulations near valleys and mountains, mountains or near large bodies of water like lakes. And so it's a combination of these large scale patterns, proximity, the geographic features such as mountains, rivers or oceans, all of those things plus the rotation of the Earth and some other things that are really take more than a podcast to get into what determine our weather. So, for example, this is an El Nino year. El Nino means the waters in the eastern Pacific Ocean are warm, warmer than normal. And so when you have the warm condition in the Pacific Ocean, that's called El Nino. Colder than normal waters in the Pacific, eastern Pacific, are called La Nina. In either of those cases, that warm hot water changes jet stream patterns or those wave patterns that I talked about earlier. And so you get shifts in the weather patterns around the world. So that's, that's what we call a teleconnection. So what's happening in Athens, Georgia, or New York or California, where you are, is very much related to the water temperatures in the eastern Pacific Ocean, in that case.

B (45:20)

What's one more thing like you mentioned, you know, heat lightning is not a thing. What's one more thing that people get wrong or don't understand about the weather like that?

D (45:28)

Yeah, that's really. Well, the main ones I've mentioned. I think people have a perception of forecasts are wrong more often than they are. I think there are some other little things that I've noticed. People. People sort of don't think that it gets cold in deserts, and it does get. Can get very cold in deserts, particularly at night. That's something that I've noticed. An area of work that I've done in my own scholarly research at the University of Georgia is on ways that things like cities can affect the weather. In downtown areas of cities, it's much warmer than the surrounding rural communities because of all the asphalt and lack of trees in downtown cities cause it to be warmer. And that's called the urban heat island. And we've even found that that can cause cities in some cases to modify or produce their own rainstorms. So there are so many fascinating aspects of weather. That's one of the reasons. To get back to the question you asked earlier. You know, I got into it, you know, just because there's so much weather. Unlike physics or chemistry, meteorology is a fairly young science, and so there's still so much about it that we're learning every day.

B (46:33)

Well, great. I appreciate you sharing all this because as I said, you know, weather is something that affects all of us every day, and it's great to get an understanding of how some of it works. I've been talking with James Marshall Shepard. He is a professor of geography and atmospheric sciences at the University of Georgia, and he is also host of the Weather Geeks podcast. And I've got a link to that podcast in the show notes. Thank you, James. If you've ever been prescribed an antibiotic by a doctor, one of the warnings that typically comes with it is to not drink alcohol while you're taking the antibiotic. The assumption many people make from that is that somehow the alcohol will reduce the effectiveness of the antibiotic. That's apparently not true. However, alcohol can increase the potential side effects of antibiotics. Those could range from stomach upset, dizziness, drowsiness, to more severe reactions like headache, vomiting, and rapid heart rate. Drinking alcohol can also reduce your energy levels and delay your recovery from your illness. So the warning not to drink alcohol while you're taking an antibiotic is probably good advice, and that is something you should know. I'VE noticed we have a lot of new listeners. We can tell from looking at the analytics that we have a lot of new listeners. And many of those new listeners come as the result of people like you telling their friends to give this podcast a listen. So please keep it up. It's a great way to support this podcast. I'm Micah Ruthers. Thanks for listening today to something you should know. New season, new chaos in college football. Big stage, big opportunity this Labor Day weekend. The wildness lives on ABC, ESPN and the all new ESPN app. What a way to start. Featuring top 10 teams like Clemson, Notre Dame, Alabama and LSU. And Bill Belichick's debut at North Carolina. It's so special, these teams collide. Don't miss a lineup filled with electric matchups. Welcome back to College Football Kickoff Week presented by Modelo Labor Day Weekend on ESPN and abc. Also available to stream on the all new ESPN app.

C (48:41)

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