In two papers published this month in the journal Nature, researchers describe two new methods of creating highly accurate and fast weather predictions up to six days in advance.
There’s an old joke: The weatherman is the only job you can be wrong 50 percent of the time and still keep your job. Meteorology has since improved a lot since that old chestnut was funny, but it still highlights a very real truth about weather prediction: It’s hard as hell.
That’s why scientists have begun turning to artificial intelligence to assist in weather forecasting. In two papers published July 5 in the journalresearchers describe two new methods of creating highly accurate and fast weather predictions up to six days in advance. The approaches could speed up extreme weather forecasting by orders of magnitudes.
On top of that, the paper’s authors also said that the model was often more accurate than traditional weather prediction systems. In fact, it was even able to track the path of a tropical cyclone—even though it hadn’t been trained on that type of data in the first placeThis phenomenon is known as emergent behavior: when a technology or system performs an action that wasn’t intentionally programmed into it.
It’s exciting—but, if the past few months are any indication, it will no doubt bring thoughts of “The robots are stealing my local news station weather person’s job!” or even “The robots are going to try and use deadly weather to kill us all!” In reality, models like both NowcastNet and Pangu-Weather will become more like an additional tool that meteorologists can use than replacing their roles entirely.
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