So, the other day, the Celsius/Fahrenheit debate reemerged on my Twitter timeline, hitting all the usual beats. As someone who has been firmly team Celsius all these years (yes, I’m Canadian), I sometimes wonder: is Fahrenheit actually better?
I think the problem is that I’m really bad at guessing the weather. This is the hottest day, I am so, so sweaty, and I am absolutely convinced that it is 40 degrees. It’s 26. There’s a fundamental disconnect in my brain between this number and this feeling, which means that when I get dressed in the morning, I often pick the wrong clothes. Obviously, if it’s extreme temperatures, I can usually figure it out. But those in-between temperatures, like 12 degrees Celsius, what does that mean?
The Celsius Conundrum
My hypothesis is that Celsius does a bad job at communicating temperature intuitively. Now, the Fahrenheit squad claims to have solved this problem. I think it has something to do with brine. But to figure this out, I need to learn how temperature was invented.
Back in 300 BCE, people believed that hot and cold were two distinct metrics. Temperature as we know it didn’t exist. If something felt warm, it was warm. If it felt cold, it was cold. But we know that sensations can be inconsistent. After a cold winter, 10 degrees may feel warm, but in the middle of summer, you might need a sweater. Two people in a room can feel totally different depending on their build, metabolism, or even menstrual cycle.
The Birth of Temperature Scales
It was only in the early 1600s that scientists began to use math and machines to separate sensation from science. The quest to capture temperature as we know it had finally begun. Early thermometers were poorly designed and inconsistently calibrated, leading to two big problems: you couldn’t rely on the same thermometer to give you the same reading for the same temperature, and it was difficult to compare with others who were using different thermometers.
Daniel Gabriel Fahrenheit tackled consistency by using mercury, leading to more stable results compared to other options. However, he used a scale with calibration points that were difficult to recreate, leaving comparability unsolved. Luckily, around the same time, other scientists were emphasizing reproducible calibration points, including Anders Celsius, who suggested the phase transitions of water. This only made sense because of the discovery that water purity impacted freezing points. Maybe it was the convenience this discovery brought, or some other reason, but the French chose to adopt Celsius into their metric system, which carried it across the globe, except for a few places.
Fahrenheit vs. Celsius: The Ultimate Showdown
So, what’s the best temperature scale? Unsurprisingly, it depends. Fahrenheit is probably the most intuitive when it comes to the weather because most of us are already familiar with a zero to 100 scale. Pretend that zero degrees Fahrenheit is like one of the coldest days you’ve experienced, and 100 degrees Fahrenheit is one of the hottest days you’ve experienced. You get this logical bridge between a number and how you might actually feel.
Celsius is probably the best for communication because almost everyone uses it. If you’re traveling and talking about the weather, chances are you’ll be better understood if you say 18 degrees Celsius over 65 degrees Fahrenheit.
Beyond the Numbers
If we’re looking for the best measure to tell us how we’ll feel, should we use Fahrenheit or Celsius? Trick question: none of the above, because temperature as a concept was created explicitly to remove sensation from the equation. This is why your weather app might look like this or this, or something else.
They may vary in levels of detail, but they all carry key metrics beyond just temperature that can impact how you feel outdoors. The most important ones I’ve found are temperature, wind, precipitation, humidity, and solar intensity.
Temperature offers a magnitude that we can treat as a starting point. Wind and precipitation can make us feel colder than the temperature suggests by carrying away the heat generated by our body. Humidity can make us feel warmer by making it more difficult to evaporate our sweat. Finally, the sun is hot, so being in the sun makes us feel hot.
Figuring Out the Weather
I get all of that in concept. The problem is that I still don’t know how to use it. At a dead end, I decided it was time to talk to other people to see how they solved this problem. But I quickly realized it wasn’t a problem anyone else had.
“You just look at the big number. You see this big number? If it’s sunny and cold, I’m still happy-ish. But if it’s warm and wet, then that’s a totally different story,” one friend told me.
“Will I die from hypothermia? No. Will I die from heat stroke? No. We’re fine,” another friend added.
“I don’t even think people who live here in the US who grew up with Fahrenheit particularly like Fahrenheit. It’s just what we all learned,” said a third.
“Soon as it got up to 100 and I experienced it, I was like, oh yeah, okay, 100’s really hot,” someone else mentioned.
The Real Issue
So, the problem isn’t Celsius, it’s me and the fact that I don’t have enough experience going outside. So here’s the plan: go outside, record the weather, track how comfortable I feel, and use that data to figure out whether I should wear pants or shorts. You know, this stuff everyone else learned when they were 12.
But first, I need to build a weather station. Dr. Samantha Ballard, a meteorologist, ocean physicist, and data scientist, says, “We really need as much data as possible. So they’re using everything. I like to break them up into temporal measurements and spatial because temporal is a point like a buoy or a weather station. You’re collecting data at one place over time. And with the satellites, we can collect over time, but it’s over a series of distances.”
Building My Own Weather Station
These observations are used to inform weather models, which are basically formulas based on physics related to things we care about over time. By combining observations with model output, we can do things like approximate weather conditions in a location without a measurement device and forecast weather conditions into the future. But it still has its limits. “The model will output one measurement for that entire grid space. You know, hundreds of kilometers squared or at best, you know, tens of kilometers. We don’t have the computer power right now to output this higher resolution.”
But if the goal is to calibrate myself to the weather, I should probably know the weather exactly where I am. So my idea is to build a weather station to bring around with me. I just don’t know how to do that. Circuits and wires have always freaked me out. Like, I don’t know how this Raspberry Pi that I finessed with Twitter is a computer. Everything on it is so little and it seems fake. This can apparently sense temperature, humidity, and barometric pressure, but I could eat this. It looks crunchy. This is an IR sensor. I’m not fully confident what an IR is. I know it’s infrared, but like, what is that? And this is a light meter. I don’t know how we measure light. This just seems like stuff that isn’t for me.
The Role Model Dilemma
Growing up, I was a young Filipino woman in the mid-2000s, force-fed women in STEM role models, posters, and videos. The idea was that if I saw a poster of an engineer who looked like me, I’d know that I could also be an engineer. But I always found that idea kind of silly because I wasn’t the person speaking at some sort of empowering seminar. I wasn’t the person on the poster. It felt like they had it all figured out where I didn’t even know where to start. So I just didn’t.
But last year, 3M emailed us and was like, “We want to pay you guys to talk about the difference between role models and champions.” I read the article and asked them to clarify some things because the whole thing made me revisit this existential crisis that I thought I resolved a while ago. It’s why I didn’t ever seriously pursue a career in science, technology, or engineering despite being the kind of person who’s clearly interested in it. Look at the videos I’ve made: lots of STEM.
I always thought it was a me problem, like why I need to calibrate myself to the weather. I figured I was just too stupid or too scared to figure it out. But this article made me consider being kinder to my past self. Maybe the reason I didn’t do all of that stuff was that I didn’t have a champion. A role model shows you where you can go, but a champion actively helps you get there. It sounds small, but the difference in effort and therefore impact is massive. It goes beyond telling people to believe in themselves. Instead, it’s informing them of what they should do and expect, and where to find support. For somebody like me whose parents were immigrants and didn’t go to school in Canada, 15 years ago something or somebody being a champion for me, that would’ve been life-changing.
Weather Station Adventures
Okay, I’m gonna plug this back in and see if it senses stuff. Power. It’s telling me the temperature. It is still possible to get to where you want to go without a champion. I ended up here with you making stuff: terrible music-generating machines, cat-loving AI, and sketchy little weather stations, all in our little corner of the internet where it feels kind of safe to mess up and learn together.
For example, I can’t wait for one of you in the comments to tell me that the idea of calibrating myself using a local weather station is moot since the margin of error on this $3 thermometer and the margin of error on this $12 sensor that I got off the internet is probably going to make all the data I’m collecting meaningless. But at least it gives me a starting point, even if it ends up being garbage.
But this is pretty cool. So, I have the tools. Now, it’s time to start collecting data and learning from experience. Let’s see if I can finally figure out the weather and dress appropriately for once.
Conclusion: The Weather is Personal
In the end, whether you prefer Celsius or Fahrenheit, the real challenge is making sense of the weather in a way that works for you. For me, it’s about going outside more, observing, and learning. It’s about turning data into personal insight and maybe building a little weather station along the way. So, here’s to better weather forecasting, one step at a time.
And, as always, if you’ve got any tips, tricks, or stories about your weather adventures, drop them in the comments. Let’s learn from each other and make this whole weather thing a bit less mysterious!