Thunder + fiber-optic cabling used for seismic imaging

雷声 + 光纤电缆：用于地震成像的新技术

Most of what we know about the Earth’s interior comes from observing seismic waves. These travel at somewhat different speeds depending on the details of the rock they’re moving through—whether it’s solid or semi-molten, how much water is present, whether it’s fractured or solid material, and so on. Get enough data from enough seismic events, and you can start piecing together a picture of what’s present at different depths below the surface. 我们对地球内部的大部分了解都来自于对地震波的观测。地震波在穿过岩石时，会根据岩石的具体性质（如固体还是半熔融状态、含水量多少、是破碎还是完整等）以不同的速度传播。通过从足够多的地震事件中获取数据，我们就可以开始拼凑出地表以下不同深度的地质结构图。

In many cases, we can get this data from naturally occurring events like earthquakes. In others, we intentionally create waves using things like explosives, providing the opportunity to do imaging in specific areas without needing to wait for an earthquake. Now, a team of scientists at Penn State suggests there’s a potential option that sits between waiting for an earthquake and triggering your own seismic event: thunderstorms. 在许多情况下，我们可以从地震等自然事件中获取这些数据。在其他情况下，我们则会利用炸药等手段人为制造地震波，从而在无需等待地震的情况下对特定区域进行成像。现在，宾夕法尼亚州立大学的一个科学家团队提出了一种介于“等待地震”和“人为制造地震”之间的新选择：雷暴。

Some of the energy carried by thunder enters the Earth’s upper crust, triggering what are termed “thunderquakes.” But, for various physical reasons, the seismic signals are extremely complex, making it difficult to extract clear signals from them. The Penn State team says it has finally constructed a model that can help make sense of this complexity and used it to reconstruct the terrain under the local campus. 雷声携带的部分能量会进入地球上地壳，引发所谓的“雷震”（thunderquakes）。然而，由于各种物理原因，这些地震信号极其复杂，难以从中提取出清晰的信号。宾夕法尼亚州立大学的团队表示，他们终于构建了一个模型，能够帮助解析这种复杂性，并利用它重建了当地校园地下的地形。

Managing complexity

处理复杂性

Why are thunderquakes so hideously complex? It starts with the phenomenon that creates thunder in the first place. Lightning creates thunder by forming superheated bubbles of plasma along its path, creating a structure that has been compared to a string of beads. Each of those beads has the potential to generate an acoustic shock wave, leading to a chain of expanding shock waves that trace the lightning’s path through the area, which is anything but a straight line. 为什么“雷震”如此复杂？这要从产生雷声的现象说起。闪电通过在其路径上形成过热的等离子体气泡来产生雷声，形成了一种常被比作“珠串”的结构。每一个“珠子”都有可能产生声冲击波，从而引发一连串的扩张冲击波，这些冲击波沿着闪电穿过区域的路径传播，而这条路径绝非直线。

These waves also have the potential to interfere with each other as they expand. And, while these shock waves first hit the Earth at a single point, they rapidly expand from there, albeit with decreasing power. Things don’t get less complex once the Earth gets involved. The acoustic shock waves may strike soft soil, hard rock, various forms of human infrastructure, and so on, each of which will affect how energy gets transmitted. 这些波在扩张时还可能相互干扰。虽然这些冲击波最初是在某一点撞击地球，但随后会迅速向外扩散，尽管能量会逐渐减弱。一旦进入地表，情况就变得更加复杂。声冲击波可能会撞击松软的土壤、坚硬的岩石或各种人类基础设施，每一项都会影响能量的传输方式。

Some of the energy gets converted into what are called Rayleigh waves, where the energy is transmitted as a wave that moves along the Earth’s surface. The rest go deeper, forming waves that may move through some combination of loose material or the underlying bedrock. To extract information about the Earth’s structure, you have to understand what the seismic waves from a thunderclap would normally look like. Which, to an extent, requires modeling all of the above processes. 部分能量会转化为所谓的“瑞利波”（Rayleigh waves），即能量以沿地表移动的波的形式传播。其余能量则深入地下，形成可能穿过松散物质或底层基岩的波。为了提取有关地球结构的信息，必须了解雷声产生的地震波通常是什么样子的。这在一定程度上要求对上述所有过程进行建模。

Since each thunderquake is going to be unique due to the different locations and conditions, this model is going to be, at best, an approximation. The fear that any approximation wouldn’t be good enough to generate usable data probably kept people from trying to analyze thunderquakes sooner. 由于地点和条件不同，每一次“雷震”都是独一无二的，因此该模型充其量只能是一种近似值。人们担心任何近似值都无法生成可用的数据，这可能就是为什么人们没有更早尝试分析“雷震”的原因。

To get their approximation, the team started with a software package called SPECFEM3D Cartesian, which is dedicated to 3D reconstructions of seismic waves. Already, that choice necessitates a few compromises. For example, the software treats the atmosphere as a 3.6 km-thick homogeneous layer, even though the atmosphere near a thunderstorm is anything but. The model also updates events at a frequency that’s slower than the waves moving through the Earth-air interface. So, to compensate for that, the researchers simply stretched the top 20 meters of Earth out to cover 200 meters. 为了获得近似值，该团队使用了一款名为 SPECFEM3D Cartesian 的软件包，该软件专门用于地震波的 3D 重建。这一选择本身就需要做出一些妥协。例如，该软件将大气层视为 3.6 公里厚的均匀层，尽管雷暴附近的大气层绝非如此。此外，该模型更新事件的频率比波穿过地气界面的速度要慢。因此，为了弥补这一点，研究人员简单地将地表顶部 20 米的区域“拉伸”到了 200 米。

These and other factors mean that there were plenty of reasons to think that the model wouldn’t be sufficient to handle real-world data. So, the people who developed it tested it against the real world, using thunderstorms that passed by their campus. 这些因素意味着，有充分的理由认为该模型不足以处理真实世界的数据。因此，开发人员利用经过校园的雷暴，对模型进行了现实世界的测试。

Passing the test

通过测试

One of the nicer discoveries in seismology has been the realization that the same fiber-optic cables that rush cat pics to your LAN can act as seismometers. And, conveniently, the Penn State campus has a 4 kilometer fiber line that has been set aside for seismic sensing running under the campus. And said campus happens to be located in a part of the US where summer thunderstorms are a regular occurrence. 地震学中一个令人欣喜的发现是：那些将猫咪图片传送到你局域网的光纤电缆，竟然可以充当地震仪。巧合的是，宾夕法尼亚州立大学校园地下有一条 4 公里长的光纤线路，专门用于地震传感。而且，该校园恰好位于美国夏季雷暴频发的地区。

Two years of data netted them 458 well-resolved thunderquakes, each of which was confirmed using records from the US’s National Lightning Detection Network (something I had not realized existed). These quakes were characterized by multiple signals arriving from different altitudes, as you’d expect from a chain of beads reaching from clouds to the Earth’s surface. 两年的数据让他们获得了 458 次解析度良好的“雷震”记录，每一次都通过美国国家闪电探测网络（我之前都不知道它的存在）的记录得到了证实。这些地震的特征是来自不同高度的多个信号，正如你所预期的那样，这是从云层延伸到地表的“珠串”结构所产生的。

Once the signals arrived at the Earth’s surface, things happened quickly: “The impingement of each bubble onto the ground or environment generates a high-energy impulsive wavelet followed by a decaying wave train dominated by surface-wave content lasting one to two seconds.” From there, the signal spread out and started to interact with the features of the Earth under the campus. 一旦信号到达地表，过程就会迅速发生：“每个气泡对地面或环境的撞击都会产生一个高能脉冲小波，随后是一个以面波为主的衰减波列，持续一到两秒。”此后，信号向外扩散，并开始与校园地下的地质特征相互作用。

Using this data, the team identified four “weak zones,” where seismic signals slow down as they interact with less rigid materials. These can include sediments, fractured rock, or areas with high water content. The Penn State campus happens to sit on a karst formation, where water has slowly altered limestone bedrock, potentially creating a variety of weak spots. 利用这些数据，研究团队识别出了四个“弱区”，在这些区域，地震信号因与硬度较低的物质相互作用而减慢。这些物质可能包括沉积物、破碎岩石或高含水量的区域。宾夕法尼亚州立大学校园恰好位于喀斯特地貌上，水流缓慢改变了石灰岩基岩，可能形成了各种薄弱点。

In these cases, the team was able to confirm that these four sites actually have something unusual going on there. This was done using a mixture of radar that measured surface deformation, engineering surveys, boreholes made at the sites, and independent seismic data. All of which gives the researchers confidence that, despite all the approximations it required, their model is performing reconstructions that are sufficiently accurate to obtain informative seismic data. 在这些案例中，研究团队证实这四个地点确实存在异常情况。他们通过结合测量地表变形的雷达、工程勘测、现场钻孔以及独立的地震数据进行了验证。所有这些都让研究人员确信，尽管模型需要进行各种近似处理，但其重建结果足够准确，能够获取有价值的地震数据。