面部識別技術可以預測極端天氣

科學家稱，面部識別技術可以預測極端天氣

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.

根據發(fā)表在《天氣評論》(weather Review)月刊上的一項新研究，用于面部識別的機器學習技術可以預測每年造成數十億美元損失的極端天氣事件。

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.

產生冰雹的風暴可能對農業(yè)、財產甚至野生動物造成巨大的破壞性影響。就在上周，在蒙大拿州東部一場嚴重的冰雹中，多達13000只濱鳥和水禽死亡。據哥倫比亞廣播公司新聞報道，這類風暴事件每年造成的人身和財產損失高達220億美元。根據國家海洋和大氣管理局的嚴重風暴數據庫顯示，2018年發(fā)生了4600多場大冰雹，大部分損失報告在美國中部地區(qū)。

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.

但冰雹的大小和嚴重程度往往難以預測。這就是國家大氣研究中心(NCAR)的人工智能技術發(fā)揮作用的地方?？茖W家們訓練了一種叫做“卷積神經網絡”的深度學習模型，來精確定位特定的風暴特征，以確定冰雹是否會形成，如果會形成，那么冰雹會有多大。

"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科學家大衛(wèi)·約翰·加涅在一份聲明中說：“我們知道，風暴的結構會影響風暴是否會產生冰雹。”例如，超級單體比暴風線更容易產生冰雹。但是，大多數冰雹預報方法只關注風暴的一小部分，無法區(qū)分更廣泛的形式和結構。”

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”.

氣象成分的完美配方才可以促進風暴產生冰雹，但即使條件成熟，冰雹的大小和嚴重程度也會因風暴的路徑和條件而變化，這就是所謂的“風暴結構”。

"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."

“風暴的形狀非常重要，”加涅說。“過去，我們傾向于關注風暴的單點或垂直剖面，但其實水平結構也非常重要。”

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的科學家向機器學習軟件展示了模擬風暴的圖像，以及溫度、壓力、風速和風向的數據，以及基于這些因素的冰雹模擬。然后，該程序自動計算出哪些特征與冰雹發(fā)生、以及冰雹大小相關。

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.

總的來說，該模型證實了該團隊此前與冰雹有關的風暴特征。然而，需要注意的是一些限制，包括模擬風暴與實際風暴之間的巨大差異。無論如何，研究小組表示，他們的研究最終可能會轉化為可操作性的應用，有可能取代目前使用的復雜數學預測。