面部识别技术可以预测极端天气

科学家称，面部识别技术可以预测极端天气

Machine learning technology used in facial recognition could predict extreme weather events responsible for billions of dollars of damage every year, according to a new study published in the Monthly Weather Review.

根据发表在《天气评论》(weather Review)月刊上的一项新研究，用于面部识别的机器学习技术可以预测每年造成数十亿美元损失的极端天气事件。

Storms that produce hail can have large, damaging impacts on agriculture, property, and even wildlife. Just last week, as many as 13,000 shorebirds and waterfowl were killed in a severe hailstorm in eastern Montana. Such storm events cost as much as $22 billion every year in damages to people and property, according to CBS News. More than 4,600 major hailstorms occurred in 2018, according to NOAA’s Severe Storms database, with the majority of damages being reported in the central part of the country.

产生冰雹的风暴可能对农业、财产甚至野生动物造成巨大的破坏性影响。就在上周，在蒙大拿州东部一场严重的冰雹中，多达13000只滨鸟和水禽死亡。据哥伦比亚广播公司新闻报道，这类风暴事件每年造成的人身和财产损失高达220亿美元。根据国家海洋和大气管理局的严重风暴数据库显示，2018年发生了4600多场大冰雹，大部分损失报告在美国中部地区。

But the size and severity of hailstorms are often difficult to predict. That’s where artificial intelligence technology by the National Center for Atmospheric Research (NCAR) comes into play. Rather than zooming in on the features of a face, scientists have trained a deep learning model called “convolution neural network” to pinpoint specific storm features in order to determine whether hail will be formed and, if so, how large the hailstones will be.

但冰雹的大小和严重程度往往难以预测。这就是国家大气研究中心(NCAR)的人工智能技术发挥作用的地方。科学家们训练了一种叫做“卷积神经网络”的深度学习模型，来精确定位特定的风暴特征，以确定冰雹是否会形成，如果会形成，那么冰雹会有多大。

"We know that the structure of a storm affects whether the storm can produce hail," said NCAR scientist David John Gagne in a statement. "A supercell is more likely to produce hail than a squall line, for example. But most hail forecasting methods just look at a small slice of the storm and can't distinguish the broader form and structure."

NCAR科学家大卫·约翰·加涅在一份声明中说：“我们知道，风暴的结构会影响风暴是否会产生冰雹。”例如，超级单体比暴风线更容易产生冰雹。但是，大多数冰雹预报方法只关注风暴的一小部分，无法区分更广泛的形式和结构。”

A perfect recipe of meteorological ingredients allows for a storm to produce hailstones, but even when conditions are ripe, the size and severity of hailstones will vary depending on the path and conditions within the storm, which is collectively known as the “storm structure”.

气象成分的完美配方才可以促进风暴产生冰雹，但即使条件成熟，冰雹的大小和严重程度也会因风暴的路径和条件而变化，这就是所谓的“风暴结构”。

"The shape of the storm is really important," Gagne said. "In the past, we have tended to focus on single points in a storm or vertical profiles, but the horizontal structure is also really important."

“风暴的形状非常重要，”加涅说。“过去，我们倾向于关注风暴的单点或垂直剖面，但其实水平结构也非常重要。”

NCAR scientists presented the machine learning software with images of simulated storms paired with data about temperature, pressure, and wind speed and direction, along with simulations of hail based on those factors. The program then figured out which features correlated with whether or not it hails and how big the hailstones are.

NCAR的科学家向机器学习软件展示了模拟风暴的图像，以及温度、压力、风速和风向的数据，以及基于这些因素的冰雹模拟。然后，该程序自动计算出哪些特征与冰雹发生、以及冰雹大小相关。

Generally speaking, the model confirmed storm features that the team had previously linked to hailstones. However, it’s important to note a number of limitations, including the fact that simulated storms vary dramatically from actual storms. Regardless, the team says their research could eventually transition into operational use to potentially replace the complex mathematical predictions currently used.

总的来说，该模型证实了该团队此前与冰雹有关的风暴特征。然而，需要注意的是一些限制，包括模拟风暴与实际风暴之间的巨大差异。无论如何，研究小组表示，他们的研究最终可能会转化为可操作性的应用，有可能取代目前使用的复杂数学预测。