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A research team at Google has developed a deep neural network that can make fast, detailed rainfall forecasts.
The researchers say their results are a dramatic improvement over previous techniques in two key ways. One is speed. Google says that leading weather forecasting models today take one to three hours to run, making them useless if you want a weather forecast an hour in the future. By contrast, Google says its system can produce results in less than 10 minutes—including the time to collect data from sensors around the United States.
[...] A second advantage: higher spatial resolution. Google's system breaks the United States down into squares 1km on a side. Google notes that in conventional systems, by contrast, "computational demands limit the spatial resolution to about 5 kilometers."
[...] Google says that its forecasts are more accurate than conventional weather forecasts, at least for time periods under six hours.
[...] Interestingly, Google's model is "physics-free": it isn't based on any a priori knowledge of atmospheric physics. The software doesn't try to simulate atmospheric variables like pressure, temperature, or humidity. Instead, it treats precipitation maps as images and tries to predict the next few images in the series based on previous snapshots.
[...] Specifically, it uses a popular neural network architecture called a U-Net that was first developed for diagnosing medical images.
[...] To produce a weather forecast, the network takes an hour's worth of previous precipitation maps as inputs. Each map is a "channel" in the input image, just as a conventional image has red, blue, and green channels. The network then tries to output a series of precipitation maps reflecting the precipitation over the next hour.
Like any neural network, this one is trained with past real-world examples. Thousands of past real-world weather patterns are fed into the network, and the training software tweaks the network's many parameters to more closely approximate the correct results for each training example. After repeating this process millions of times, the network gets pretty good at approximating future precipitation patterns for data it hasn't seen before.
(Score: 1, Funny) by Anonymous Coward on Wednesday January 15 2020, @03:16PM
Even without looking outside, even if I was 30ft underground in a sealed shelter I could tell you what the local weather here is, was and will be, as the place is renowned for it to be 'always fucking raining...'
Then there's the cat method...
0 cats on lap, weather is fine
1 cat on lap, weather is on the turn
All cats draped over any available part of body (and the dog, who thinks she is a cat, trying her best to join them) batten down the hatches...
Wet cat(s) on lap, it's fucking raining...
We can normally tell if there's a really bad storm coming in from the Atlantic, the parks opposite the house suddenly get covered in gulls of every species, the actions of the birds in the gardens are usually a good indicator of longer term changes, as an example, when our resident robins (Erithacus rubecula, I'm this side of the pond..) come up to the window, or pester us when we're at the door, then we know there's a spell of bad weather coming...and that they're wanting food put out, the magpies do the same.