23 November 2016
No writer credit found
The 2011 Tohoku-Oki earthquake generated tsunamis that devastated large swathes of Japan, including the Fukushima Nuclear Power Plant. A new earthquake detection technique might help give residents a few minutes’ extra warning. XINHUA / Gamma-Rapho / Getty Images
As deep rock shuffles around, an area’s gravitational pull changes too. Detecting these blips could provide precious minutes when it comes to tsunami warnings.
Earthquakes can shuffle around huge chunks of the deep Earth. But picking up these signs by measuring the associated transient gravity change might help provide early warnings, new research shows.
Jean-Paul Montagner from the Paris Institute of Earth Physics in France and colleagues examined data collected during the devastating 2011 Tohoku-Oki earthquake off the coast of Japan, and detected a distinct gravity signal that arose before the arrival of the seismic waves. They published their work in Nature Communications.
And while the technology to employ their system is not yet set up, they say the technique may herald new developments in early warning systems for earthquake hazards such as tsunamis.
Earthquakes are notoriously hard to predict. When a fault line ruptures, seismic waves travel through and around the Earth and these are usually the first sign that at earthquake has hit.
And even though these waves travel quickly – the fastest, P-wave or primary waves, can barrel through the Earth at 13 kilometres per second – they still mean precious seconds or minutes before the waves arrive at a seismic station.
Montagner and his crew thought there could be a way to detect an earthquake before the waves appeared.
Seismologists have known for more than a decade that there are static gravity changes following a rupture. This happens because as a fault line moves around, mass is redistributed below the surface. This means some areas suddenly become less dense while others pack on mass – and so their gravitational pull changes too.
Such changes are measured with gravimeters. The problem is there’s background noise when it comes to gravity changes – the dynamic Earth constantly shifts and wriggles. Could the sudden gravity signal associated with an earthquake be teased out from the underlying noise?
To find out, the researchers needed to examine a large earthquake that happened close enough to a sensitive gravimeter, so small changes in the gravity field could be picked up, but far enough away so the P-waves didn’t immediately reach seismic sensors.
They found an ideal example in the 11 March Tohoku-Oki earthquake that led to the Fukushima Nuclear Power Plant disaster.
Some 500 kilometres from the earthquake’s epicentre was a gravimeter at the Kamioka Observatory. The observatory was surrounded by five seismic stations. P-waves from the earthquake took around 65 seconds to reach the stations.
Montagner and his colleagues first “calibrated” their statistical technique with 60 days of background gravity measurements – from 1 March 2011 to 5.46am on 11 March (21 seconds before the earthquake rumbled), then from 12 March to 30 April.
They compared this background with measurements taken during the earthquake and shortly thereafter, and found a distinct blip at the time of the earthquake. It was small, but strong enough to be distinguished from the background with 99% confidence.
So can this prediction technique be implemented today? Unfortunately not – it would require building a substantial network of exceptionally sensitive gravimeters which don’t yet exist. But, the researchers write, they could have the potential to let seismologists estimate earthquake magnitude quickly – a process that currently takes up to several minutes.
See the full article here .
You, too, can help with earthquake knowledge and research.
The Quake-Catcher Network is a collaborative initiative for developing the world’s largest, low-cost strong-motion seismic network by utilizing sensors in and attached to internet-connected computers. With your help, the Quake-Catcher Network can provide better understanding of earthquakes, give early warning to schools, emergency response systems, and others. The Quake-Catcher Network also provides educational software designed to help teach about earthquakes and earthquake hazards.
After almost eight years at Stanford, and a year at CalTech, the QCN project is moving to the University of Southern California Dept. of Earth Sciences. QCN will be sponsored by the Incorporated Research Institutions for Seismology (IRIS) and the Southern California Earthquake Center (SCEC).
The Quake-Catcher Network is a distributed computing network that links volunteer hosted computers into a real-time motion sensing network. QCN is one of many scientific computing projects that runs on the world-renowned distributed computing platform Berkeley Open Infrastructure for Network Computing (BOINC).
The volunteer computers monitor vibrational sensors called MEMS accelerometers, and digitally transmit “triggers” to QCN’s servers whenever strong new motions are observed. QCN’s servers sift through these signals, and determine which ones represent earthquakes, and which ones represent cultural noise (like doors slamming, or trucks driving by).
There are two categories of sensors used by QCN: 1) internal mobile device sensors, and 2) external USB sensors.
Mobile Devices: MEMS sensors are often included in laptops, games, cell phones, and other electronic devices for hardware protection, navigation, and game control. When these devices are still and connected to QCN, QCN software monitors the internal accelerometer for strong new shaking. Unfortunately, these devices are rarely secured to the floor, so they may bounce around when a large earthquake occurs. While this is less than ideal for characterizing the regional ground shaking, many such sensors can still provide useful information about earthquake locations and magnitudes.
USB Sensors: MEMS sensors can be mounted to the floor and connected to a desktop computer via a USB cable. These sensors have several advantages over mobile device sensors. 1) By mounting them to the floor, they measure more reliable shaking than mobile devices. 2) These sensors typically have lower noise and better resolution of 3D motion. 3) Desktops are often left on and do not move. 4) The USB sensor is physically removed from the game, phone, or laptop, so human interaction with the device doesn’t reduce the sensors’ performance. 5) USB sensors can be aligned to North, so we know what direction the horizontal “X” and “Y” axes correspond to.
If you are a science teacher at a K-12 school, please apply for a free USB sensor and accompanying QCN software. QCN has been able to purchase sensors to donate to schools in need. If you are interested in donating to the program or requesting a sensor, click here.
BOINC is a leader in the field(s) of Distributed Computing, Grid Computing and Citizen Cyberscience.BOINC is more properly the Berkeley Open Infrastructure for Network Computing, developed at UC Berkeley.
Earthquake safety is a responsibility shared by billions worldwide. The Quake-Catcher Network (QCN) provides software so that individuals can join together to improve earthquake monitoring, earthquake awareness, and the science of earthquakes. The Quake-Catcher Network (QCN) links existing networked laptops and desktops in hopes to form the worlds largest strong-motion seismic network.
Below, the QCN Quake Catcher Network map
Please help promote STEM in your local schools.
Stem Education Coalition