How We Got Here - Ep 7

Rachel: Hi everyone. I'm Dr. Rachel Lupien

Steph: and I’m Dr. Stephanie Spera.

Rachel: Our climate is in crisis and we all want to help, but we might not know how

Steph: we're talking to people who have figured out how to use their talents to combat climate change and the hopes that their journey might inspire your own.

Rachel: This is how we got here: because the earth needs professional help.

INTRO

How We Got Here - Ep 7

Steph: Hey, Rachel.

Rachel: Hey Steph. Hello. You know, I'm good.

Steph: . It's Tuesday. We're in it.

Rachel: It's Tuesday. I think. I am taking the day off tomorrow. Um, I am, I'm traveling

up to Providence, Rhode Island to go take some engagement photos with my fiance.

Steph: I'm so jealous because I love Providence. I love your fiance. I love a photography shoot or we can stop talking about Providence anywhere. I can take a joke about The Hot Club and how that's where all of my engagement photos would be taken.

Rachel: Shout out to Hot Club but I don't think I have time to go get a drink in a plastic cup.

Steph: That's okay. Well, Rachel, let's start the week. Like we usually do catching up. What is something good that happened this week?

Rachel: Yeah. Yeah. I had a pretty good week. I was invited to go give a virtual talk because of COVID, but I talk with a university and it went really well.

It was really a fun group to chat. They're more on the human evolution side of things. So I sort of had to tailor my talk to that. And it was great hung out with some paleo anthropologists and really the highlight was a someone real famous at the end of the talk, asked me a question and it was a great question.

And I, it was also a very long question, which, you know, I actually had to take notes during the question that's how long it was, but it was, it was delightful. And, and, um, I answered it. And then she said, "That was a very good answer."

Steph: That's such a good post-talk feeling. Also, just anyone getting questions, like if you get questions, that means people. I mean, seriously, it means people are paying attention

Rachel: It was just great. How about you?

Steph: Um, oh boy, I ha I've had a rough week, which you can get into in a second. Uh, but yesterday I, I didn't have to teach when my son was in daycare. I bought a step aerobics thingy. What are they called? I don't even know during COVID. Oh yeah. I bought a step.

Rachel: Trying to get fit.

Steph: Just trying to stay healthy.

Rachel: Keep it tight.

Steph: Just keep it a little bit less loose. But I love, I mean, I love step aerobics so much. I haven't done it for so long. So yesterday I just took 30 minutes, and YouTube, I was like, 'beginner stepaerobics' and ' Jenny Ford, I'm tired of you.' JennyFord is a big deal in the step aerobics world. I found hip hop step aerobics, and I would say it is non traditional. If you are embedded in the step aerobics world. It used to be it's a little different, but it was so good. . It was still like normal step routine, but it was taught a little differently than I would say the traditional step is taught.

Rachel: No, our listeners, our listeners are tried and true traditionalist when it comes to staff, so right. Yeah.

Steph: Thank you for understanding my niche. I mean, it was such a silly thing to do for 30 minutes, but I, I mean, I was sweating at the end and sometime I just need 30 minutes to not, I love step.

Yeah, we, maybe we should flip these and talk about what was bad first, how it was something, but we let's start at a high and then just, we'll go back to a low and I'll introduce our guests, which is a high.

Rachel: And, and as a reminder, it's always good to talk about the bad things that happened. Cause especially with social media and science Twitter, we see a lot of people's, um, accomplishments, but it's good to remember that it's a mix throughout the, throughout the day, throughout the week,

throughout the year.

Steph: What's something low?

Rachel: A low, I guess, you know, I had a pretty good week. I didn't, there wasn't really anything in particular that happened, but it's just sort of like a lot of my papers right now are sort of at a standstill. So I felt like, um, I have this outline for a new paper and it's just so hard for me to get back into it. Um, although I will say I have a writing partner who may well on some day, um, she, she helps me a lot and we set some goals today and I did get, I did write a little bit, so that's a terrible bad example because I try to me in the end, it's possible to break through.

Steph: That's great also that you, that you have someone who's on the same page and it was like, we'll hold each other accountable. I think that is fantastic.

Rachel: Yeah. But yeah, it was generally just like, I don't know, in my position where I'm really just doing research. I haven't had students come in so far this week. Uh, my schedule has been actually very open, which is great, but it also, for me, and I think for other people, it makes it really hard to schedule to, to really structure my time. And the day kind of gets away from you. Then you get to the end of the day and you just feel kind of crappy. Yeah. Cause you don't do as much as you think

you could do.

Steph: Right. Because you're so used to being like, okay, I have two free hours when I sit down, I'm going to knock this out. And by free, I mean your work, but like not in meetings or teaching. You're like, what do I, what do I do with my hands?

Rachel: Yeah, but not so bad. But how about you?

Steph: I actually feel similar. I've just been like this week, the past week, honestly, the past year and a half has kicked my butt, but it's catching up to me this week. Yeah. So everyone's like, ha enjoy fall break. I'm like, I guess I'm going to work the whole time because yeah.

Well, let me rant for like 30 seconds then I'll stop. COVID sucks. Being pre-tenure sucks. Having a newborn sucks.

Rachel: Ohhhhhh

Steph: okay. COVID is hard. Pre-tenure having a newborn is hard. My son is the light of my life. Oh. Also sometimes he's really hard and I think his molars are coming in and like what a mess.

You just don't sleep. So it's all sort of coming together. Like on Sunday after Theodore went to bed, I just took 20 minutes to just sat and sat in the bedroom. I was like, okay. I just always feel like I'm that that cartoon, that this is fine with the fire in the back.

Rachel: Oh yeah. The little smiling dog.

Steph: I am that smiling dog. And then if you want to be existential, let's add the climate crisis on how our government is doing nothing right now.

Rachel: Right. You sort of start thinking bigger and bigger about all the problems and they're all confounding. Yeah. That's tough. That's a tough week. Okay. So let's get to it. I am so excited for you. To meet our guest.

 Dr. Marysa Lagueis a scientist using climate models to understand the interactions between the land surface and the atmosphere. She sent an incredible amount of work on the community earth system model or CSM, and has won numerous fellowships and awards, including most recently the James R Holton Award from the American Geophysical Union ever heard of it- AGU- which recognizes outstanding scientific accomplishments from researchers within three years of receiving their PhD. So early career researchers, Marysa is just the peppiest human you will ever meet. And we became fast friends at a short course we did together in Norway a few years ago, and she is the person that I would strategically sit next to in class so that I could lean over and whisper things like, "so wait, what is the jet stream?" And she would draw a quick little diagram for me, just like that. She is the best. So welcome to how we got here with Dr. Marysa Lague.

INTERVIEW

Rachel: Hey Marisa.

Marysa: Hi. Hello.

Steph: Welcome.

Rachel: Can you just like tell us what you do? What's your job title. What's on your business card.

Marysa: I don't have a business card

Rachel: - Your theoretical-

Marysa: My imaginary business card: my official title is a James S. McDonald foundation, postdoctoral fellow in dynamic and multi-scale systems, which is quite a mouthful. I'm a postdoc.

Steph: Could I also just interject and have you put your novelty checks by your poster AGU so people can collect them as you?

Marysa: Yes, it'll be the thing.

Rachel: Like the NASA calendar, the calendar.

Steph: So that is a very impressive title. I'm going to throw that out there. What do you actually do if I like bumped into you at a bar or I was the person behind you, like a drugstore at CVS? What do you, what does that mean? What are all those words mean?

Marysa: I study how changes in vegetation modify stuff happening in the atmosphere. So specifically, if you change plants on the land surface, you're changing a bunch of physical properties about the land, like how dark it is or how hard it is to evaporate water.

And that changes fluxes of water and energy that go between the land and the sky above it. And then that can modify things like cloud cover or how warm or cold it is or how much water vapor is in the atmosphere. And that can go on to modify surfaces. Both locally, like just feeding back, Hey, it's writing less or more or something. It can also modify the climate on very large scales by changing like atmospheric circulation or infection of like water and energy around the planet.

Rachel: And imagine it would also just change that vegetation again. Right. Just go back and then it affects the other thing.

Marysa: Yeah, definitely. There's there's giant feedback. They're like change plans, change atmospheric change, climate change, plants, change atmosphere, change climate.

Rachel: So that's what you study. That's that's great. We will get more into that. And I think the three of us have in common in that research sense. So on a day-to-day basis, you're a postdoc you're studying vegetation effects on, on climate and other things. What do you actually do? What is day-in-the-life workday Marysa?

Marysa: I open my computer, which is already open to my email because I never turned my computer off until at which point I restart my computer because it's all frozen. So I restart my computer and then I should probably just turn my computer off at night. I look at my email, it makes me stressed. So I hide it. I come and look at other things. I run a lot of climate models. Um, so I set them up in sort of fun, weird ways to answer questions. So I, you know, do whatever changes I'm making. I submit them to the queue. They immediately crash. I try and figure out what's wrong and why they didn't work the way I thought. And then figure that out and put the back. And then I got down a little, well, let's go back.

Steph: You submit them to the queue.

Rachel: What is cute? Is that a letter?

Marysa: No, it's the Q-U-E-U-E spelling.

Rachel: Sorry, let's go way back. Can you just explain simply what a climate model is? Oh man. To me, because I would really like to know.

Marysa: Okay. So a climate model is a numerical representation of the various components of the earth system. So we have basically mathematical ways of explaining different processes that happen, um, on the planet. So like on the land surface, you have energy going in in terms of sunlight and heat from the atmosphere. And then you have a land surface model that's going to do something with that energy. Like you might have a plant and it's going to grow and it's going to keep track of carbon. And it's going to send some of the energy back up to the atmosphere as heat or as water. Um, and you can represent all of that, just with some equations. Um, and similarly in the atmosphere and the ocean, you can represent the motions, like the fluid motions of what's going on, like where air is moving and where water is moving and what other processes are happening.

Like, oh, if there's lots and lots of water and lots of energy, maybe you should have connection and a cloud and you can represent, um, physical real-world processes with mathematical equations, a lot of mathematical equations.

Steph: So it's like you are taking giant supercomputers and mapping out how the world works, essentially.

Marysa: Exactly. Every area on earth all the time. Yeah. The models are huge. They're like millions of lines of code.

Rachel: That was going to be my next question. Like. How do I get into code?

Marysa: No, no, it's funny you say that. I don't think there's a single, like person in the world has read or understands the whole thing

Rachel: so you're contributing pieces of code, which are full of equations. You're contributing pieces to a much larger thing. .

Marysa: So then you have this giant bundle of code and because this code is so huge and because we're going to run it at every single point for days and days and years, and years and decades and decades.

And that's just going to be way too big for my laptop to handle. And so I said, we have these supercomputers. That are specifically built to run these giant complex chunks of code. Um, and these supercomputers, they don't have like a screen and a keyboard that I can just sit down at my laptop. Instead you interact with them via, um, just like short little lines of code. You're basically sending it instructions. So you're sending it like, Hey, go, please run my model.

Rachel: So that was another question is like, okay, so I do lab work, right? I'm a geochemist. So. I need money from the government to do my lab work. And I, you know, I pay for the beakers and the vials and the organic solvent that I use. And then I, you know, pay for the time on the instruments that I use. How, where does the money, like, I know you need funding, right? You need funding to do this work. How does that work? Can you just help? Yeah.

Marysa: Yeah. So these computers are really expensive and, you're like renting time, kind of so different, different systems are set up in different ways. There's a few climate computers that people use and they are, each computer is sort of sponsored by a large wealthy entity, such as the National Science Foundation. So the National Science Foundation pays for this computer to exist and it's maintenance and like software engineers to babysit it because it gets upset and people who know what they're doing need to take care of it.

So, so like the, the, you know, the Department of Energy and the Department of Defense and the National Science Foundation, they'll each, you know, be like maintain a supercomputer and then if you get grants funded by like theNational Science Foundation, then that just entitles you to be able to go and ask for like, Hey, I need some time on this computer to do my science.

Rachel: Thank you for clearing up these questions that I've literally always had.

Steph: She has, I've known her for a while and then we just don't answer her.

Rachel: I just, I just us data people just think that we know what models are, but we don't -

Marysa: model is such a like loosey goosey word. That's true model is like two lines on a piece of homework or 10 million lines of code on a fancy supercomputer that when this happened,

Steph: So when, so your day-to-day you're like coding, you're getting in line in the queue to run near code while you're waiting in that queue what else you doing? Are you coding the whole time?

Marysa: No, no. Most of my time is waiting for models to run as opposed to actually running. They're pretty slow. Yeah. So, so most of my time is actually spent doing like analysis of the output that these models make. So I, you know, run an experiment like, oh, what happens if we turned off evaporation on land, what would that do to the atmosphere?

 And that takes like a week and I get the answers back. And then I like spend some time being like, oh, what happened? Weird stuff happened. Okay. So these models, these fancy big complex computer or, uh, earth system models, they're written usually in Fortran. I actually code in Python. Um, so I read in output from these fancy climate models and I look at what happens.

Rachel: Um, and what is that output you're getting? Are they maps? Are they more lines of code? Are they. numbers.

Marysa: There's some files full of numbers, but the numbers look like maps.

Rachel: Steph is laughing at me. I'm just via podcast. You cannot see her face. She is laughing at me.

Steph: I mean, I look at some map numbers or number maps sometimes, so it just makes, I didn't, I like I'm closer to Marissa's world than yours.

Rachel: I have other strengths.

Steph: You do. I mean, I don't know how to interpret those squiggly lines you look at.

Marysahow would you say your work contributes to the combating the climate crisis?

Marysa: That one's hard because I think I do what I do because I think it's fun. So my motivation is maybe slightly backwards, but I do think it is potentially still relevant because all the people live on land and people do a lot of stuff to land. Like they manage it in various ways, like building cities on it or agriculture or forestry and managed forests or burning stuff down or. Altering the climate system in a way that it wants to burn itself down. So there are lots of very large scale changes that happen to the land surface. And what I do is basically study the, the way that those changes will then impact the rest of the climate system. So we are changing the land. And then what I do is figure out how those changes in the land will impact the atmosphere and modify whether in climate systems, on like local, where you changed the land surface to very global scale.

Steph: So you're like if we plant all of these trees in this place, which is not a thing we're doing in a lot of places, if we tear down all of these trees in this place, which is the thing we're doing in a lot of places, how is that modifying the landscape? And then if we continue to do that, how might that modify our atmosphere and the like locally, regionally, globally.

 I think you directly contribute to understanding the effects of climate change

Rachel: Okay, so let us start your journey. Let's go back in time to little law. Marysa what are you doing? Maybe in high school. What's your first job? What are you interested in? Did you think, did you know that a climate model was a thing? .

Marysa: We didn't really, we didn't like learn coding in high school so that wasn't really on my radar. Um, yeah. I kind of wish we did.

Rachel: So what were you interested in and what did you think you might want to do?

Marysa: So, so in high school I was, I was very interested in like the sciences. Um, I liked school. Uh, I also really liked music. I played the clarinet for 11 years. And I grew up in a pretty small town in rural BC.. In, in rural British Columbia, I grew up in a small town in rural British Columbia where it was like, if you were one of the, like, Um, nerdy kids and you liked school, you are going to go and become an engineer or a doctor and those were like the options, like for what the quote 'smart kids' weren't going to do.

 So, so I mean, I was, I, I don't know. I wasn't super excited about either of those things, but I figured maybe engineering would be okay. Cause it's like math and that's kind of fun. Um, so I actually did my first year of university at the community college right in town um, cause I didn't know what I wanted to do and that meant I got to take calculus course with 10 people instead of 500, it was super fun.

 After a year there, I transferred to the university of British Columbia, which is in Vancouver. Um, and again, I guess I was like loosely intending to go the engineering route because that seemed like I'd rather do that, then become a medical doctor.

Steph: What's really interesting is that when you don't have these models for other jobs, you're like the only two that these are my two options. But I think if a college is the thing you choose to do, you should try and take classes and things you've never heard of before.

Just because there are all these jobs that don't exist, that you have no idea about.

Marysa: So I went to UBC, um, Yeah. If I realized that all the things that I liked about the engineering program or the math classes, and I promptly finished all the math classes that were required. And that was it.

Steph: So you, were you a math major

Marysa: I ended up actually being a math major because that was. I really, that was what I really liked to do. Going in, I wouldn't have been like, oh, you can do a degree in math. That's the thing like, oh yeah, that is a thing, like a whole department for it. That's actually a thing. Um, yeah, so I did my undergraduate degree in mathematics. Super fun. Um, so a mix of, you know, like applied math that we use in climate science and very like theoretical, pure math, like number theory and abstract algebra, which are ridiculously fun. It's like solving puzzles.

Steph: Ooh Marysa you can tell you are in the right job because you just said those words in the sentence together. Very few people would do. So then when you, so you graduated with a math major, what did you do?

Marysa: I went pretty much straight into grad school. So while I was an undergrad doing math, I took a lot of classes from the earth and ocean science department at UBC for fun. It was like, oh, intro to climate or like natural disasters and all that stuff. And it was just like a nice break from, you know, abstract algebra and number theory was sure let's talk about rocks. So, so those were super fun and I really liked both of these aspects. So I ended up going to graduate school at, um, the University of Washington and their atmospheric science program, because studying climate and like plants and climate, let me mix sort of the like, oh, we're going to use math to study the earth and I liked the earth. I like going outside and like walking through the forest and going hiking. Like, this is cool, but now we're going to like physically explain why everything we're seeing is happening.

Steph: Yeah, it sounds like the perfect marriage of your interest, right?

So in grad school, what was, what did you, what was your main research topic in graduate school? Climate modeling

Marysa: Yeah, so I started off, um, it sort of a combined masters PhD program and in my master's I was looking at how increasing the area of forest cover in the mid-latitudes, um, modified global scale atmospheric circulation. Like you're, you're making the land surface darker and you're changing how much water goes into the atmosphere. And that changes how much energy is going into the atmosphere in the place where you put the trees.

Um, and if you do this on large enough scales, that starts to mess with like how much energy is in the Northern Hemisphere versus the Southern Hemisphere. And the atmosphere likes to move energy around, like so that it can get rid of it more easily as opposed to leaving it all piled up in one place. So if you pile a bunch of energy into one hemisphere, then you get these shifts.

So one of the things that happens that happened when I did these climate models, simulations is putting much of trees into the mid-latitudes was that we got these interesting cloud responses in the mid-latitudes and you're like, oh, put a bunch of trees in quite strange, but annoying to me that I didn't know why the clouds were changing because you were changing a bunch of things about the land at the same time, like how dark it is and how aerodynamically rough it is, which influences like turbulent mixing, which matters for clouds and how much water was going into the atmosphere.

So it's kind of like if you have more water going into the atmosphere then, and you can let the air saturate more quickly, so you might get a cloud, or if you just have more turbulence, you could lift parcels of air up to the point where they condense. So it's, it's super, not obvious why um, and that, that annoyed me.

 So what I wanted to do was say like, okay, how much of this cloud change was due to the change now? How much was due to the change in evaporation? How much was due to the change in like how aerodynamically rough it was. And it's really hard to answer questions like that with modern land service models, because they're so complicated.

So on the one hand. Amazingly fascinating complex, um, models that represent like nitrogen cycles and carbon cycles and how happy plants are and plants growing and having lots of leaves and dying and decaying and doing all this complicated, crazy stuff. But that also means it's really hard to go in there and say, like be darker, but everything else stay the same, um, everything's related because everything is connected. So you can't isolate those individual.

Rachel: Also, if you just want to change one little thing, it's like not really worth it to use such a complex model right.

Marysa: Yeah. I mean the model, the model is expensive. The math major and meat was very upset by this. So what I spent most of my PhD doing was actually writing an idealized land surface model that you could couple into these complicated or system models.

But instead of having the fancy land, you just had this really stupid land instead where land. This is its albedo, this is its roughness. This is how hard it is to evaporate. This is a little bucket that holds water and here's a silly little snow model that can like change the albedo.

But none of these are related to each other, which means you can have something that looks like a tree except has the LP to have a grass or, oh, right. But that let's do like test how the atmosphere's going to respond to these individual properties.

Steph: In undergrad, did you take formal coding classes or I think both Rachel and I are self-taught coders. But I was just wondering, because it sounds like your PhD became very coding heavy. If you're writing, creating your own land model, right. That's code sort of taught yourself. It was a lot more teaching yourself - you weren't a CS major.

Marysa: Yeah. I took one formal coding class in undergrad and it was using like a, a dummy teaching language. So not even any of the languages I actually code in. Um, so yeah, so, so in, in a lot of sense, I'm a self taught coder, um, especially writing that line model.

I'd never coded in Fortran before. So I just sort of looked at the Fortran from the rest of the model and figured, tried to figure out what was going on and. You know, eventually it worked, um, it's definitely not written as neatly or tidally or numerically stably as it could be. I'm actually getting some help right now from some actual software engineers to, um, fix it up a little . They're, they're finding all sorts of problems with it, which I greatly appreciate their help. So,

Steph: I mean, my sister is a formal software engineer. And sometimes I send her my code when I can't get something to work. Oh, well, she's like, why did you do any of this, this way? This takes so long.

I was like, I don't care. Help me with the one line I need exactly.

Rachel: I mean, it's really interesting, right? . You had no idea that was the future for yourself.

Marysa: I feel like, no, in hindsight, if I did, I probably would have taken a few coding classes.

Steph: , I mean, us self-taught coders are generally the messiest coders of all time. Like I'm embarrassed to put myself on github.

Rachel: Okay. Marysa I mean, I I'm really, what I'm hearing is that you love math,

What other skills do you use for your job? Like, not necessarily on day-to-day basis, but if you were to see a young Marysa and you were like, oh, you're so good at this thing. What are you really good? Besides math and coding or is it just math and coding?

Marysa: No, no, no, no, no, no, no. That makes me sound like a robot. I think it's like, um, I want to understand how this works and like somewhat obsessively. And that motivates me to like, run these weird experiments.

Steph: You, you are a very skilled problem solver.

 Are there skills that you don't use for your job? Like if someone is starting to think like, oh, Marysa her story resonates with me, but I'm not good at these things.

Marysa: I hate writing. I'm so bad at it. I don't, I don't even know what it is like. Puzzling through what's going on and making the figures and figuring out the story and throwing them into a PowerPoint and adding some like bullet points on like, what's cool about it. But then like having those figures and those bullet points and make me make them into paragraphs into like a formal academic formal academic manuscript citations, and like proper puppet sending sentences.

Rachel: I'm very similar. I was a math kid growing up. Like I loved math and science. And then I didn't realize being a scientist involves some writing

Steph: What's really interesting across that we're getting across all of our guests is that being able to communicate is so important and like the way and understanding the ways in which you're a successful communicator and ways in which you're a less successful communicator. And knowing that about yourself is also a really important thing to know and lean into or not lean into.

Rachel: Especially when we're talking about the climate crisis, we need to get the word out in any. In any sense in our, like the result of our climate models in the results of our paleoclimate studies, we just need to like communicate that.

Marysa: Yeah. And I don't necessarily know that scientific papers are the best way to do that because I also kind of reading scientific papers. I want like a 10 minute YouTube video of the pictures and some bullet points for every paper.

Steph: So much of the stuff that the, like the three of us work on stays in it within our community. And I think you're right, like, honestly, the YouTube animation of like a tree getting sad because it doesn't have a messing this up, the water it needs. I mean, that would be more effective, right? Like communicate, being able to communicate this stuff to children. I don't know. Yeah. Well, or me or you or me or my mom. Yeah.

Rachel: Um, so if there were no climate crisis, like, I guess also, if, if you hadn't been interested in those classes, maybe in college, like you have these skills, what would you be doing?

Marysa: A great question. And I don't know. I think I would be doing the exact same thing because I think it's fun. That's what I said. Yeah. The earth is cool. How does land modify stuff? We don't really know. Let's go find out. Cool.

Steph: It is funny, the amount of things that we do as a general, like global population that we don't understand the repercussions of it. And don't think until much later. Oh, did we do that?

Rachel: Well, thanks for being with us.

Steph: Do you have anything you want to plug like a, like a Twitter handle or a pet social media presence.

Rachel: Please tell me about your cat.

Marysa: Yeah, there's two cats. I got a second cat. So there's Alistair and he was a stray and he came from a shelter and he, uh, he had an interesting, the way I adopted him was potentially questionable. So I went to the shelter and he was super, super like calm and he just crawled into my lap . And I was like, oh, this sweet, poor cat. He's like disgusting and matted and greasy, like just curled up from my lap and pray so sweet to solve. So I adopted him. This is not the end of the story. I filled out all the paperwork and I adopted the cat and I like, I'm walking out the door with the cat and this carrier and they're like, oh, bye. He just got neutered yesterday. So his drugs might wear off.

So it turns out that when he was curled up purring in my lap, partially sedated and the drugs wore off and he is insane. Crazy. So after like six months to a year, we kind of, we finally came to terms with each other he calmed down, he like grew a new coat.

Rachel: but you also have a COVID cat.

I also have a COVID cat.

Marysa: I didn't tell you about my first job though. I don't know if you want to hear it. I was a 1890s interpreted Victorian heritage town, full costume,

yeah, learn how to cook on a wood stove or like, you know, go to the blacksmith's shop and make, yeah. We'd make butter. They would make nails. We had a steam train, like an actually functional steam train. They would lay railway track. Railway ties were really heavy.

Rachel: Marysa also, you're not my only friend who has had this job.

Marysa: I am not the only person at our 20% lab here who has had this job.

Rachel: One of my close friends was this, she worked at Sturbridge village in Massachusetts.

Steph: What was, so can you tell me what you were dressed like? ,

Marysa: 1890s. skirt. Post bustle. Oops. Bustle. So you went from like hoop skirts, just like floor length, um, skirts, slightly poofy sleeves. Um, did you have fun hat color? No. Peter pan collar others in hats, feathers and hats. Optional. Oh.

Steph: I love that you were in this other time and then you would grow up and study climate change and it's amazing.

Rachel: And you're like sitting in queues

Marysa: I feel like it just made me really good at making cookies because I didn't spend all summer making cookies just for tourists.