Weather Forecasting Is The Best It’s Ever Been. Will Climate Change Ruin It?

Weather Forecasting Is The Best It’s Ever Been. Will Climate Change Ruin It?

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Look closely at almost anything and you’ll find data—lots of it. But when you push past the calculations, what are all those numbers really saying about who we are and what we believe? CNN’s Harry Enten is on a mission to find out. This season on Margins of Error, Harry teases out big ideas like what accents say about where we live, how much money it takes to be happy, and whether the U.S. should finally switch to the metric system.

Forecasting the Future of Weather

Margins of Error Jun 21, 2022

31 minsLet’s face it: We cannot live without our weather forecasts. It’s the first thing we check most mornings — and when they’re wrong, we get pretty frustrated. But forecasting is actually the best it’s ever been! Harry learns the secrets to predicting the weather accurately and investigates how climate change could make those predictions a little cloudier.

Harry in Central Park


So here we are, right on the steps of Belvedere Castle in the center of Central Park, just off of West 81st Street. And I am looking for the Weather Observatory, which Google tells me is right near here, but I’ve never been here. So we’re going to try and figure out exactly where it is we’re going to walk up there.

Yes, that’s me in Central Park trying to find the Weather Observatory. You may not know this, I bet a lot of New Yorkers don’t, but they’ve been recording the weather here at the Observatory for over a century. In fact, it’s one of the longest active weather stations in the country. While, I’ve never been to the Weather Observatory in Central Park, well, I’m a huge weather nerd. Huge. I’ve always been this way. Growing up, I was obsessed with knowing when it was going to snow because what’s better than a snow day? But it quickly went beyond that. I joined online weather forums when I was in middle school. I went to Penn State weather camp when I was in high school. I even purposely chose a college in New Hampshire that averaged over 60 inches of snow per year. To me, forecasting the weather seemed like magic. So over the years, I’ve taught myself about weather models, probability of precipitation. Heck, I’ve done a lot of forecasting myself. Which brings us back to my quest to find the Weather Observatory in Central Park.

Harry in Central Park


This is kind of ridiculous, in the sense that it is, it’s just right here. It’s like no bigger than like a small room almost if it was like outside. And it’s just, all these weather instruments, as people walk by almost not even noticing it.

My trip to the observatory was cool, but like I said while I was there, it was so odd to see all these people walking by without even noticing it. And in many ways, I feel like that works as a kind of allegory for much of our relationship with weather forecasting. You see, over the years, as I’ve followed forecasts and messed with weather models myself, I’ve noticed that for something that affects literally every human being, every single day of their lives, people have a lot of misconceptions about weather forecasts or don’t really even know how they work, which is funny because people love the weather. In fact, a 2019 survey from the Pew Research Center found that of all the topics covered on local news, broadcast, weather, weather was the thing most people said was important to their daily lives, which makes sense, right? If a forecast says it’s going to rain later today, you’re probably going to take an umbrella with you. But that’s also why folks love to rag on forecasters when they get it wrong. Heck, part of the reason why I wanted to do an episode about the weather was a forecast that called for the, quote unquote storm of the century, only to whiff New York City almost entirely. So come hell or high water, by the end of today’s episode, I guarantee that you’ll understand how forecasting works, why it’s never been better, and how climate change may affect our ability to predict the weather. I’m calling for clear skies, a light breeze, and a whole bunch of information about the art of weather forecasting. I’m Harry Enten and this is Margins of Error.

So I think everyone has a weather story from when they were kids or when they first became interested in the weather. Most meteorologists that I know have one.

This is John Homenuk. He’s a meteorologist, storm chaser and founder of the forecasting blog New York Metro Weather, which he started back in 2008.

I remember very vividly, when I was seven or eight years old, being rushed to the basement by my parents because there was a thunderstorm or a possible tornado. And the memory that I have in my head is feeling really scared and helpless. That was a defining moment for me where I said, I want to learn about this so I don’t feel helpless, when it comes to forecasting it and figuring it out, because I did not like that feeling at all, and I still remember it like it was yesterday.

So here’s John now, supplying New York City with daily weather forecasts.

We’ve kind of built this community where people can learn and talk about the weather and there’s so many people that are interested in the weather. And that’s become a place where I can interact with people and kind of develop a relationship with them. And what I love about it is communicating it to people and giving people the opportunity to learn and understand it.

So I think it’s a natural segue to this question, which is explain to me how forecasting works.

Meteorology is extremely complex, as I’m sure you know, and when I describe to people what it is, it is very literally, our job is to predict the future. And so in order to do that, we need to start by understanding what’s happening right now. And so we will take a large amount of time in the morning to look at radar, satellite, all kinds of things that are available to us. Then we want to try to predict what’s going to happen in the near term, so the next couple of hours. And we look at how things are trending, current observation wise, short term weather models start to come into play. As you start to get a little further out into the next day and the day beyond that, things start to get more complicated because weather models are, you know, attempting to simulate a fluid process, which is the atmosphere. And so we have to be very careful as you get further out from just a couple of hours, in which weather model are you using for guidance, you know what, how are you weighing that in your forecast? And you’re trying to put together a picture of what makes sense moving forward, not just a couple of hours, but now we’re several hours to the next day.

Like I said, complicated.

And so when I explain it this way to people, most people start to garner an appreciation for the fact that just even getting the forecast right the next day is, when you think about it, pretty crazy. I mean, we’re able to give an immense amount of detail as to what’s going to happen tomorrow based on what we’re looking at today and the technology that we have. So then when you start to stretch it out into the medium range, which I consider days like three to six from today, you start to get into a much more complicated conversation of how you’re using the weather models and understanding the weather patterns.

When listeners hear weather model, what does that mean exactly?

So a weather model is very literally a code that is written to try to simulate the atmospheric processes. So it takes the current conditions that are ongoing right now and then tries to roll it forward, simulating all of the processes that we know exist in the atmosphere.

Talk about the models themselves and sort of how you’re able to weight them in the forecast and and just sort of figure out where the heck things are going.

Yeah, so, so weather models, there are a bunch of them. I mean, there’s, there’s the main ones which are is the GFS global forecast system that’s kind of known as the American model. There’s a European model, there’s a Canadian model, there’s a U.K. weather model. And even beyond those, what we consider global models. So those are models that are forecasting the weather across the entire globe. There are models that are more specific and inherently they’re going to be wrong. They’re going to be incorrect. And as meteorologists, our job is to understand what this what story they’re trying to tell us and how to use each of them individually to kind of put the pieces of that puzzle together.

And I can say this from experience. Taking what the models are telling you and using them to make your own forecasts, well, that’s where forecasting becomes an art.

The problem, I think for meteorologists and the challenge is, understanding how these weather models work. So each of these models almost has a personality of its own. They have biases. They tend to handle different types of weather systems in certain ways. And, you know, for example, the GFS usually is way too progressive with coastal storms. It likes to slide them out to sea too fast. That’s been a bias in the model for a decade now. As a meteorologist, we have to factor all this in to our forecast.

I think that makes sense. Let me ask you this question. Why and how have our forecasts gotten so good?

Well, that’s a multifaceted answer. The best way I could answer that, I would say, is I think people have taken the time and invested a lot of time into understanding the atmosphere and, you know, weather models are one thing, right? There’s there’s amazing minds working on producing these weather models, which are incredible, right? They’ve gotten so detailed. I keep mentioning we can predict individual thunderstorms, things like that. Incredible technology boom has helped us a ton. We have a lot of fire power behind these weather models. But I always go back to the fact that people have taken the time to understand how to use these models as guidance, properly. And so our forecasts have gotten good because we’ve gotten better at communicating it to people, communicating to the public, which has led to these forecasts just being more reliable overall.

If forecasting has improved so much, why are we still getting forecasts wrong? Sometimes?

Yeah, I mean, I think it’s a very fair question to ask. These things are complex and the weather prediction has improved so much everywhere. But we’re still learning the bigger ones. The big, the big storms are still very complex and very difficult to figure out where it’s just, you know, the joke sometimes in the thunderstorm community is a farmer can sneeze in Oklahoma and change the whole setup. And it’s kind of like when you’re watching a storm coming up the coast, that could potentially be huge or could not be, it’s just a tiny little thing makes a difference. And so the big thing in meteorology is we try to do meteorology, not modelology. We don’t want to just look at the weather models and use them only because that’s how you get yourself into a bad place. And so with the big storms, you almost have to sit down. I remember during January 2016, I sat down and made a list of reasons why the storm would miss New York to the south from a meteorology perspective. And I had just as many reasons that it would hit as reasons that it wouldn’t. And so it’s those storms that are right on the periphery that I think, you know, it’s it’s going to be a while before we can confidently say, oh, this one’s definitely going to hit New York. It’s just it’s just too com

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