發現強烈地震初期產生的重力訊號可以用來定出其規模
在地震發生之後地球重力場幾乎立刻就會受到擾動，這種現象被儀器記錄到的時間會早於地震學家經常分析的地震波。在2017年12月1日發表在《科學》(Science)的研究中，由CNRS、IPGP和巴黎第七大學的研究人員組成的團隊成功觀測到這種跟重力有關的微弱訊號，並且解釋它們的來源。由於此訊號易受地震規模的影響，因此在快速辨識大地震是否發生時，它們或許能起到相當重要的作用。
想要更加瞭解地震的地震學家跟為了偵測重力波而發展精確重力觀測技術的物理學家合作之下促成了這項研究。地震會劇烈改變地球應力的平衡狀態而產生地震波，造成的後果可能相當具有破壞力。不過同樣的波動也會擾亂地球的重力場而放出不同的訊號。對於想要快速定量震動幅度的研究人員來說，這種訊號令他們相當有興趣，因為它們不像震波的行進速度僅有時速3至10公里，而是以光速來行進。因此距離震央1000公里遠的地震儀測站，或許有機會能在地震波到達兩分鐘之前就先偵測到此種訊號。
在2016年的一篇研究中初次呈現此種訊號，而此篇研究接續下去做出了更加詳細的探討。首先，在距2011年日本地震(規模9.1)震央周圍500至3000公里的範圍內，科學家確實從十個左右的地震儀紀錄中觀察到這類訊號。研究人員從此觀察結果接續證明訊號是源自於兩種效應。第一種效應是地震儀所在地點的重力變化會改變儀器質量的平衡分布。第二個效應則是以間接方式影響：由於地球任何一處的重力變化也會擾動原有的應力平衡，因此會產生新的地震波而被地震儀接收到。
研究人員探討上述兩種效應而證明跟重力有關的此類訊號相當容易受到地震規模影響，因此在強烈地震發生時有望利用它們來快速定量地震規模。研究人員未來面臨的挑戰是要想辦法將此種訊號運用在規模小於8至8.5的地震，因為在低於這個規模時，訊號相對於地球自然產生的地震波噪訊相比過於微弱，而要將兩者分離需要相當複雜的過程。所以研究人員已經開始著眼於數種技術，其中有些靈感源自於用來偵測重力波的儀器，計畫更進一步地對這些十分珍稀的訊號進行測量。
New early gravity signals to
quantify the magnitude of strong earthquakes
After an
earthquake, there is a disturbance in the field of gravity almost
instantaneously. This could be recorded before the seismic waves that
seismologists usually analyze. In a study published in Science on
December 1, 2017, a team formed of researchers from CNRS, IPGP, the Université
Paris Diderot and Caltech has managed to observe these weak signals related to
gravity and to understand where they come from. Because they are sensitive to
the magnitude of earthquakes, these signals may play an important role in the
early identification of the occurrence of a major earthquake.
This work came
out of the interaction between seismologists who wanted to better understand
earthquakes and physicists who were developing fine gravity measurements with a
view to detecting gravitational waves. Earthquakes change the equilibrium of
forces on Earth brutally and emit seismic waves whose consequences may be
devastating. But these same waves also disturb Earth's field of gravity, which
emits a different signal. This is particularly interesting with a view to fast
quantification of tremors because it moves at the speed of light, unlike tremor
waves, which propagate at speeds between 3 and 10 km/s. So seismometers at a
station located 1000 km from the epicenter may potentially detect this signal
more than two minutes before the seismic waves arrive.
The work
presented here, which follows on a 2016 study which demonstrated this signal
for the first time, greatly increases its understanding. First, the scientists
did indeed observe these signals on the data from about ten seismometers
located between 500 and 3000 km from the epicenter of the 2011 Japanese
earthquake (magnitude 9.1). From their observations, the researchers then
demonstrated that these signals were due to two effects. The first is the
gravity change that occurs at the location of the seismometer, which changes
the equilibrium position of the instrument's mass. The second effect, which is
indirect, is due to the gravity change everywhere on Earth, which disturbs the
equilibrium of the forces and produces new seismic waves that will reach the
seismometer.
Taking account
of these two effects, the researchers have shown that this gravity-related
signal is very sensitive to the earthquake's magnitude, which makes it a good
candidate for rapidly quantifying the magnitude of strong earthquakes. The
future challenge is to manage to exploit this signal for magnitudes below about
8 to 8.5, because below this threshold, the signal is too weak relative to the
seismic noise emitted naturally by Earth, and dissociating it from this noise
is complicated. So several technologies, including some inspired from instruments
developed to detect gravitational waves, are being envisaged to take a new step
forward in detection of these precious signals.
原始論文：Martin Vallée,
Jean Paul Ampuero, Kévin Juhel, Pascal Bernard, Jean-Paul Montagner, Matteo
Barsuglia. Observations and modeling of the elastogravity signals
preceding direct seismic waves. Science, 2017; DOI: 10.1126/science.aao0746
引用自：CNRS. "New early gravity signals to
quantify the magnitude of strong earthquakes." ScienceDaily. ScienceDaily,
30 November 2017.
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