Winter Weather Predictions
FLORA LICHTMAN, HOST:
This is SCIENCE FRIDAY. I'm Flora Lichtman. We had a very mild winter last year, at least here on the East Coast. And so people are understandably wondering whether that means we're going to get punished this year. If you're a "Farmers' Almanac" reader, you'll know that the prediction doesn't look good for the East Coast based on what they say is a secret formula involving sun spots, lunar cycles, the position of the planets. The almanac even gives specific date ranges for particularly bad weather - FYI: Feb. 12 through 15. Is that science, or more like astrology?
Well, here's the interesting part. The scientific heavyweights like the National Oceanic and Atmospheric Administration didn't fare any better than the almanac last year, which makes you wonder: Is seasonal prediction even possible? Here to talk about it is Jason Samenow. He's a chief meteorologist for the Capital Weather Gang at The Washington Post. He joins us from NPR in Washington. Welcome to SCIENCE FRIDAY.
JASON SAMENOW: Thank you for having me on.
LICHTMAN: So what are the predictions look like this year, and then should we pay attention to them?
SAMENOW: There is a ton of uncertainty about what this winter's going to bring across much of the country. And that has to do with the fact that El Nino - which is the episodic warming of the equatorial Pacific, which was predicted to develop by now - really hasn't behaved as expected. So when we have an El Nino, we typically see warm and dry conditions across the Northern Tier and wet and cold conditions across the Southern Tier. But it has pretty much baffled forecasters in that it hasn't developed as models have predicted.
And so, for large parts of the country, the winter outlook is a major wildcard, especially in the East, and the central parts of the country. So NOAA yesterday released its winter outlook and had large chances of either being warm or cold or wet or dry over expansive parts of the U.S.
LICHTMAN: Hmm. And last year was kind of a puzzling year, too, right?
SAMENOW: That's right. Last year, we had the opposite phase of El Nino called La Nina, but it was it on its way out. And rather than having cold, stormy conditions in the Northern Tier, as well as into the Northeast, it was exceptionally warm. And that had to do with a feature called the Arctic oscillation, which was mainly locked in its positive phase, meaning the jet stream - which is a river of air at high altitudes, which tends to serve as a storm track - was well to the north for much of the season. So places like Boston, New York City, Minneapolis, Chicago were all very warm and, for the most part, dry.
LICHTMAN: Was the jet stream actually screening out the cold air? Do I have that right?
SAMENOW: Pretty much. The jet stream is typically the dividing line between the warm tropical air to the south and the cold, Arctic air to the north. And for the most part, it had retreated to close to the Canadian border for large parts of the winter.
LICHTMAN: Hmm. What about the "Farmers' Almanac"? I have to admit that I like picking it up and looking at it, and I sort of - I'm hesitant to even ask. Is there any science backing it up?
SAMENOW: Well, I think the "Farmers' Almanac," they do look at some of the same things that NOAA look at, that AccuWeather looks at, as well as the Capital Weather Gang, when developing their outlooks. At the same time, they're using some more suspect features like sun spots and planetary alignments and things like that, which have never been proven to have any real predictive skill in terms of forecasting the weather in the long range.
And the other thing that Farmers' Almanac tries to do and for which there's no predictive value whatsoever is to predict storms more than a week ahead of time. You can typically get a general sense of what a season might look at - look like, whether it's going to be warmer than normal, colder than normal. But trying to pin down when a particular storm is going to hit a particular area, there is no scientific validity to doing that.
LICHTMAN: Why does it - why are we able to - forecast many years into the future the temperature on the planet with what we're told is pretty good certainty, but we can't forecast the sort of nearer-term seasonal weather?
SAMENOW: Right. So when you're looking at long-range predictions of temperatures, we're looking at changes and things like the atmospheric concentration of greenhouse gases, which acts on a average level rather than at geographically specific areas. So, for example, we can say because greenhouse gases are predicted to increase over time, that that is likely to exert a warming effect over the coming decades. But we can't say, for example, which regions are going to warm more than others. We can't say with a lot of confidence what areas are going to become wetter and drier because we just don't have that type of computing power. We - and there's a lot of chaos in the atmosphere. And so we can look at the larger scale features and smooth them out. But the random noise, that's really hard to predict.
LICHTMAN: So is it not just there's more variables, but also that we don't understand how the influence each other well?
SAMENOW: I think it's both of those things. You're trying to look at a whole number of variables, different atmospheric patterns like the Arctic oscillation, like El Nino and La Nina, which we really can't predict beyond a season or two. And then you're also trying to pinpoint how storm tracks are going to change. And it becomes an enormous jigsaw puzzle. And while our computers are getting better and they're able to assimilate more and more data, the longer you go into the future, the more the errors in the models tend to increase. And so as a result of that, forecasts of detailed weather features get more and more unpredictable as you go deeper into time.
LICHTMAN: I wonder also if it's maybe the hardest time to even try to take this on, because even if you have really great historical data and understood how things worked in the past, there - that - because of climate change, that may not translate to the future.
SAMENOW: That's exactly right. We're pretty much moving into unchartered territory when we're looking at the changes which are happening with the atmosphere and the atmosphere's concentration and greenhouse gas levels higher than they've been in over 800,000 years. And so we're really conducting an experiment on the atmosphere, and there are a lot of unknowns. And there are a lot of things we have to learn and better understand moving on into the future.
LICHTMAN: Arctic sea ice melted to its lowest level on record, I think, this year. Does that play a role in seasonal weather?
SAMENOW: That is a very fascinating and interesting question. And there are some cutting-edge research which would suggest it does, as a matter of fact. When the Arctic sea ice retreats, what it's effectively doing is it is slowing down the upper-level winds at the high latitudes, according to some of the latest research. And when those upper-level winds, when they slow down, they tend to meander more and become more wavy. And that tends to result in what we call atmospheric blocking, which is basically a traffic jam in the atmosphere where the jet stream can dip farther south in some areas and then retreat farther north in other areas.
And what that tends to result in is more extreme weather. In other words, where the jet stream dips further to the south, it gets colder and it stays colder for long periods of time, whereas, on the other hand, where the jet stream retreats to the north, it gets warmer and stays warmer for longer periods of time. And then in the transition zone, it's more stormy. So this change in the atmospheric circulation that is likely resulting from the decline in Arctic sea ice may well be having profound influences on winter weather, winter - and on weather year-round.
LICHTMAN: Does that - is that factored into your model?
SAMENOW: Well, it's really...
LICHTMAN: The prediction?
SAMENOW: It's really not well-integrated into the models at this point. In fact, NOAA, in its winter outlook released yesterday, really didn't factor in the Arctic sea ice trends. And it's because it's really a cutting-edge experimental area of research. And there are just a few very recent papers on the issue, and it's not well-established. And it's maybe just one piece of a very large, complex puzzle. So there are scientists who are skeptical that the Arctic sea ice retreat is making the jet stream more wavy and extreme. But there is some preliminary data and some preliminary research would suggest that.
LICHTMAN: And what about these animal indicators, like the sandhill crane, for example?
SAMENOW: Right. So there are a number of animal indicators that people look at when trying to predict winter weather, and those mostly fall in the category of folklore. In other words, there aren't any studies which demonstrate any true relationship between animal behavior or, for example, acorn/squirrel behavior prior to winter and how harsh a winter it's going to be. One of the favorites is the wooly caterpillar. And there are those who say the brown segment in the middle of that caterpillar, if it's wide, it's going to be warm. If it's narrow, it's going to be cold. And that's a long-standing folklore, but there's really no established scientific literature which validates those sorts of predictions.
LICHTMAN: Myth busted here on SCIENCE FRIDAY. Thanks for joining us today, Jason Samenow.
SAMENOW: You bet. It was a pleasure. Thank you.
LICHTMAN: Jason Samenow is the chief meteorologist for the Capital Weather Gang at The Washington Post.
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