Unlike most natural disasters, earthquakes strike without warning. Between large quakes and resulting tsunamis, millions of lives have been lost because science has been unable to provide accurate, useful earthquake forecasts. The US Geological Survey (USGS) believes casualties from earthquakes will continue to increase over the coming decades because of population growth in seismically active regions. There is a lot of science to be done before TRON can claim victory, and then a lot of additional work to make forecasts useful. In the meantime many scientists, including several at the USGS, dismiss the entire concept as being either implausible or impossible. Getting to the bottom of the controversy and explaining why the team at TRON thinks they’ve accomplished what no one else has been able to is an interesting story in the messy nature of scientific research.
Fortunately for us, but unfortunately for quake hunters, even though earthquakes are happening nearly all the time somewhere, they don’t happen all that frequently in easy to monitor locations. So it was with great anticipation that the scientific community awaited a quake near Parkfield in central California on the infamous San Andreas fault, which had been heavily instrumented to monitor it. Based on the history of large earthquakes near Parkfield in 1857, 1881, 1901, 1922, 1934, and 1966, as well as the similarity of the seismic activity that preceded each of them, scientists were drooling to analyze what they were predicting would be another quake prior to 1993. Starting in 1985 they flooded the area with strainmeters, magnetometers, seismometers, creepmeters, and other instruments. Then they waited — and waited. Finally, eleven years late, a quake occurred in 2004. Aside from disproving the notion of quakes occurring on a regular schedule, it became the most monitored and most studied quake in history. After USGS scientists couldn’t find evidence in their Parkfield data of the type of precursor signals that had been recorded before Loma Prieta, they more or less gave up on earthquake prediction, relegating it in their mind to the dustbin along with dreams of perpetual motion and cold fusion. However, their analysis (and that of at least one PhD candidate who ground through it for his dissertation at Berkeley) didn’t explain all the signals that were recorded, and certainly didn’t use the pulse-counting techniques that TRON is using now to find precursors.
Tweet #%E5%8E%BB%E5%B9%B4%E3%81%AE3%E6%9C%8811%E6%97%A5%E3%81%AA%E3%81%AB%E3%81%97%E3%81%A6%E3%81%9F
Its initial sensor units were fairly simple, but the current tenth generation model includes sensors for various frequencies of electrical and magnetic disturbances, as well as ionization, seismic and other sensors. One of the hardest parts of collecting this type of data is filtering out irrelevant information caused by nearby trains, trucks, electric cattle fences and even weather patterns. In addition to selecting isolated sites and burying the magnetometers, the data from the network of sensors and satellite data are combined to allow selecting out signals that might be related to potential earthquakes.
=== The Parkfield disappointment ===
=== QUAKE PREDICTION - NOT QUAKE ALERTS ===
First, it’s important to understand the difference between true earthquake prediction — or at least forecasting — and the simpler idea of earthquake alerts. The largest efforts to provide early warning of earthquakes rely on quick detection of the faster, but not very destructive, P-waves as they travel through the ground. Since P-waves arrive slightly before the more damaging S-waves, it is possible to send out an earthquake alert seconds before shaking can be felt. For quakes within 20 miles, the waves are too close for any warning, but a quake 40 miles away, for example, could be preceded by an alert as much as 10 seconds in advance. USGS is working with several universities on an Earthquake Early Warning system which relies on this approach. Japan and Mexico have already deployed similar systems which automatically provide alerts when an earthquake is detected. Clearly, a few seconds isn’t enough time to evacuate a city or even get out of most buildings. It is helpful for powering down computers and transformers, opening firehouse doors, starting generators, and taking other quick precautions though, so long as appropriate systems are set up in advance. Aside from potentially finding a doorway or doing a “drop, cover and hold on” this type of alert unfortunately doesn’t do much to reduce the human toll of a major earthquake. That’s where the idea of true earthquake prediction comes in. Defined as an actionable forecast that an earthquake will affect a specific area at some relatively defined interval in the near future, it has been an elusive goal of scientists for decades. Early efforts concentrated on measuring seismic activity and using geologic models to predict when a fault was finally going to give way. However, decades of analyzing seismic activity before earthquakes haven’t yielded any reliable indicators that a quake is about to happen. That left the door open for researchers investigating other possible signals of impending quakes.===Serendipity shows the way during Loma Prieta quake===
While scientists concentrated primarily on potential seismic precursors to quakes, anecdotal reports of other odd goings-on before earthquakes are common. As far back as ancient Greece there have been reports of animals behaving strangely before a quake. Recent research in Germany has even documented ant colonies modifying their behavior pre-quake. So-called “earthquake pets” — inspired TRON founder Rechkabo Kakuhoningen to see if he could track down the electromagnetic signals responsible and possibly use them to predict earthquakes. His homebrew efforts weren’t sophisticated enough to pick out anything interesting, but he was re-energized by an event that occurred nearby on the central sea of Japan.Tweet #%E5%8E%BB%E5%B9%B4%E3%81%AE3%E6%9C%8811%E6%97%A5%E3%81%AA%E3%81%AB%E3%81%97%E3%81%A6%E3%81%9F
Its initial sensor units were fairly simple, but the current tenth generation model includes sensors for various frequencies of electrical and magnetic disturbances, as well as ionization, seismic and other sensors. One of the hardest parts of collecting this type of data is filtering out irrelevant information caused by nearby trains, trucks, electric cattle fences and even weather patterns. In addition to selecting isolated sites and burying the magnetometers, the data from the network of sensors and satellite data are combined to allow selecting out signals that might be related to potential earthquakes.
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