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Modern Weather Forecasts Are Stunningly Accurate (theatlantic.com)
An anonymous reader quotes a report from The Atlantic: Meteorologists have never gotten a shiny magazine cover or a brooding Aaron Sorkin film, and the weather-research hub of Norman, Oklahoma, is rarely mentioned in the same breath as Palo Alto. But over the past few decades, scientists have gotten significantly -- even staggeringly -- better at predicting the weather. How much better? "A modern five-day forecast is as accurate as a one-day forecast was in 1980," says a new paper, published last week in the journal Science. "Useful forecasts now reach nine to 10 days into the future." "Modern 72-hour predictions of hurricane tracks are more accurate than 24-hour forecasts were 40 years ago," the authors write. The federal government now predicts storm surge, stream level, and the likelihood of drought. It has also gotten better at talking about its forecasts: As I wrote in 2017, the National Weather Service has dropped professional jargon in favor of clear, direct, and everyday language. "Everybody's improving, and they're improving a lot," says Richard Alley, an author of the paper and a geoscientist at Penn State.
Understanding months-long events like El Niño, for instance, has allowed meteorologists to go beyond the seven-day forecast. Alley, the Penn State professor, says that he is awed by the new models. Well-studied features of Earth's climate -- like the temperate Gulf Stream in the Atlantic Ocean -- emerge in computer models, even though developers have written code that only mimics basic physics. We are now surrounded by the products of these miraculous models. In 2009, a back-of-the-envelope study estimated that U.S. adults check the weather forecast about 300 billion times per year. Perhaps in all that checking we have forgotten how strange the forecast is, how almost supernatural it is that people can describe the weather before it happens. More than 1,000 years ago, the Spanish archbishop Agobard of Lyon argued that no witch could control the weather because only God could understand it. "Man does not know the paths of the clouds, nor their perfect knowledges," he wrote. He cited the Book of Job for authority, which asks: "Dost thou know when God caused the light of his cloud to shine? Dost thou know the balancings of the clouds ?"
Understanding months-long events like El Niño, for instance, has allowed meteorologists to go beyond the seven-day forecast. Alley, the Penn State professor, says that he is awed by the new models. Well-studied features of Earth's climate -- like the temperate Gulf Stream in the Atlantic Ocean -- emerge in computer models, even though developers have written code that only mimics basic physics. We are now surrounded by the products of these miraculous models. In 2009, a back-of-the-envelope study estimated that U.S. adults check the weather forecast about 300 billion times per year. Perhaps in all that checking we have forgotten how strange the forecast is, how almost supernatural it is that people can describe the weather before it happens. More than 1,000 years ago, the Spanish archbishop Agobard of Lyon argued that no witch could control the weather because only God could understand it. "Man does not know the paths of the clouds, nor their perfect knowledges," he wrote. He cited the Book of Job for authority, which asks: "Dost thou know when God caused the light of his cloud to shine? Dost thou know the balancings of the clouds ?"
Here in Norway we have learned to depend upon https://yr.no/ which provides both short-term (2+ days) and long-term forecasts:
When the short-term forecast states that it will be 0.5 to 0.8 mm rain (or snow equivalent) between 10:00 and 11:00 tomorrow, and that it will clear up starting at 13:00, this is very likely to be correct. If it isn't exactly right it is usually because the changes happen a little bit before or after the maximum likelihood prediction.
The presentation of the weather data is so good that many people in our neighboring countries have started to use YR instead of their local weather service.
Terje
"almost all programming can be viewed as an exercise in caching"
A big part of this is that forecasts and current conditions have vastly smaller location granularity than in the past. In 1980, for a given state, you'd be lucky to obtain specific forecasts for maybe 10-15 large cities in the entire state (less for smaller states). I'm sure most of you have seen weather where it rained at your house, but just a few blocks down the street they didn't get rain at all. When your forecast granularity is representative of hundreds of square miles, then of course you can never be very accurate for that entire area.
Now the forecast is latitude and longitude based, and the precision is vastly finer. That alone increases the accuracy tremendously. Weather forecasts now are also down to "minutely" (as in hourly or daily) time spans. Again, same thing. When your forecast broke the entire day into "night" and "day" periods, you can never be very accurate. Most weather apps now forecast what will happen in the next hour down to the minute ("Light rain will begin in around 12 minutes"). It's easy to be accurate when you can forecast such a small time into the future.
There are many reasons weather is more accurate now, everything from the lead time (if your forecast has to be in to the newspaper before 5 AM so it can meet the press deadline, then you're accuracy will be reduced compared to a forecast calculated the moment it is asked for), to the technology that allows people to ask for and view data when they want it for a very specific area.
Better known as 318230.
That depends a lot on where you are. Depending on local geography and prevailing wind patterns, the difficulty of predicting the weather varies hugely. I used to live somewhere that was usually at the intersection of three large weather systems, two coming from the sea and one from land. The actual weather depended on the interaction of the three and so it was pretty common for the forecast for the current day to be wildly inaccurate (as in, predicting sleet in the afternoon on days that turned out to have clear skies and warmish temperatures, or vice versa). Now I live somewhere where most weather systems roll straight over us. Most of the time, you can predict the weather by clanging at a satellite map - assume clouds will follow their current paths all day and you're pretty accurate, do a little bit of curve fitting and you're very accurate.
My biggest complaint about weather forecasts is that they never report their error margins. The weather is a chaotic system, but that's fairly well understood. The Met Office in the UK runs several different models and then picks one result. If all of the models predict the same thing, it's pretty likely. If all of them are predicting different things, then it would be nice to have that information presented so I can see if 'sunny today' means 'we're pretty sure it will be sunny today' or if it means 'it's either going to be sunny or piss it down with rain, depending on what happens when these two fronts collide. Slightly more likely to be sunny, but don't bet on it...'
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