Wall Street Daily

How to Predict When the Next Big Earthquake Will Hit

We have the ability to generally “predict” earthquakes and “warn” threatened populations after they start. What we need is a system to detect an event – days and weeks ahead of time.


Here are two headlines, from last week alone:

“Massive 7.8 Earthquake Shakes the Solomon Islands in Southwest Pacific Ocean.”

“Magnitude 6.5 Earthquake Hits Indonesia, Killing Nearly 100.”

Here’s another one, from October:

“Earthquake Faults Around San Francisco Are Dangerously Interconnected.”

And consider:

“Watch What ‘The Big One’ on the San Andreas Fault Would Feel Like.”

So when are we going to get out in front and be able to not just predict or warn but detect these potential disasters before they occur?

As Masashi Hayakawa and Yasuhide Hobara note in an article published in Geomatics, Natural Hazards, & Risk, earthquake prediction is defined according to long-term (10–100 years), intermediate-term (one–10 years) and short-term (minutes, hours, days, and weeks) time scales.

Seismology is focused on the long- and intermediate-term scale “because they are mainly based on the geological studies of faults, historical records of seismicity, and recent instrumental data of seismology and geodesy,” say Hayakawa and Hobara.

This is the type of work that drives preparation against potential disaster in the form of structural requirements for new construction and upgrade projects in earthquake “hot spots” such as Japan and California.

The short-term scale is the most difficult.

But we do have systems in place and under development that can – and will – give us minutes and hours.

Since 2006, the U.S. Geological Survey has been working on an “earthquake early warning” (EEW) system, based on systems in operation in seismic “hot spots” around the world.

Systems in Mexico, Japan, Turkey, Romania, China, Italy, and Taiwan are capable of sensing “a large earthquake near its source and broadcast a warning of imminent strong shaking to more distant areas before the shaking arrives.”

Since 2006, the U.S. Geological Survey has been working on an “earthquake early warning” (EWW) system, based on systems in operation in seismic “hot spots” around the world.

These systems are “tailor-made for the local system of faults,” so they’re not directly applicable to California, for instance, which has its own particular seismic profile.

The USGS has upped its game lately.

Last August, the agency announced $3.7 million in grants to six West Coast universities that will assist in transitioning the “ShakeAlert” earthquake early warning system from the test phase into production.

ShakeAlert was created by the USGS Advanced National Seismic System, “a federation of national and regional earthquake monitoring networks throughout the country, including networks in southern California, northern California, and the Pacific Northwest.”

The new USGS ShakeAlert investment will fund:

Then there’s the MyShake app, “a smartphone seismic network for earthquake early warning and beyond.”

MyShake’s developers “show that smartphones can record magnitude 5 earthquakes at distances of 10 km or less and develop an on-phone detection capability to separate earthquakes from other everyday shakes.”

The app “harnesses personal/private smartphone sensors to collect data and analyze earthquakes,” and can “be used to enhance EEW in regions with traditional networks and could provide the only EEW capability in regions without.”

Ultimately, systems such as ShakeAlert – and maybe MyShake – will allow end-users such as public utilities, public transportation operators, emergency management agencies, state and local governments, and private businesses the opportunity to prepare for potential shocks created by earthquakes.

But we’re still talking about minutes, perhaps hours, of prep time.

What we desire are detection systems that will give us days and weeks of notice.

Simulations based on the authors’ mathematical model “demonstrate the capability of our method in early detection of earthquakes.”

Earthquake prediction science has historically relied on seismic measurements, or mechanical observations of movements in the crust of the Earth.

During the past decade or so, researchers have incorporated microscopic measurements of changes in the Earth’s crust and upper mantle, or the “lithosphere.”

Thus, we have a new field of science, “seismo-electromagnetics.”

The science continues to evolve, however, and now we’re starting to see remarkable theoretical progress based on nonseismic precursors.

These advances may help us move from warning and prediction to detection.

Detection will help us get from the minutes-and-hours end of the short-term scale to the days-and-weeks end.

One new method, described in a paper published December 4, 2015, in Science Advances, capitalizes on the enormous amounts of data being generated by traditional seismological study.

Researchers describe

an efficient method to detect earthquakes using waveform similarity that overcomes the disadvantages of existing detection methods. Our method, called Fingerprint and Similarity Thresholding (FAST), can analyze a week of continuous seismic waveform data in less than two hours, or 140 times faster than autocorrelation. FAST adapts a data mining algorithm, originally designed to identify similar audio clips within large databases; it first creates compact “fingerprints” of waveforms by extracting key discriminative features, then groups similar fingerprints together within a database to facilitate fast, scalable search for similar fingerprint pairs, and finally generates a list of earthquake detections.

According to the authors, “FAST detected most (21–24) cataloged earthquakes and 68 uncatalogued earthquakes in one week of continuous data from a station located near the Calaveras Fault in central California.”

The implications are significant. The wider the system’s deployment and the more data it can process, the better FAST will be able to identify signs of potential earthquake.

Another paper, presented just weeks later at the fourth annual International Conference on Computer Science and Network Technology, held December 19–20, 2015, proposed a new method based on quantum computing.

The authors “theorize a method for observing instantaneous changes in the gravity field of Earth through monitoring the effect of the change on a pair of entangled photons.”

One photon is in an earthquake “hot spot.” The other is on a satellite orbiting the Earth.

Using quantum computing, the proposed method “can detect the slightest change in the gravity field of the particular place.”

That change can indicate “an upcoming large earthquake with sufficient precision.”

Simulations based on the authors’ mathematical model “demonstrate the capability of our method in early detection of earthquakes.”


Upticks, Downticks

The Russell 2000 rebounded strongly last week, tacking on an impressive gain of more than 5% during the five trading sessions. The small-cap index established an all-time intraday high of 1,392.71 on Friday. The S&P 500, Dow Jones Industrial Average, and Nasdaq Composite all posted new all-time highs, too.

Italian Prime Minister Matteo Renzi announced his resignation following defeat of a referendum that would have changed 47 of the Italian constitution’s 139 articles, including provisions related to how laws are passed, the relationship of the central government to Italy’s 20 regions, and the composition of parliament. This may signal yet another phase of instability – political, economic, and financial – in Europe.

As Eddy Elfenbein of Crossing Wall Street notes, the Wilshire 5000 Total Market Index generated a total return of 346.5%, or 7.7% on annualized basis, as of the 20th anniversary of Alan Greenspan’s famous “irrational exuberance” speech.

The Peoples Bank of China’s “total reserves declined by $69.1 billion, to $3.051 trillion, in November, a decline of 2.2% from the previous month and the largest drop since January’s fall of 3%. A median forecast from economists had predicted a fall of only 1.9% from October.” As the Financial Times notes, this “fifth consecutive monthly fall indicates growing difficulty for policymakers. Since the renminbi’s sharp depreciation in August 2015, Beijing has sought to combat more severe softening against the greenback by selling dollars from the central bank’s foreign exchange reserves.”

U.S. consumer confidence soared in December to 98.0, just below the 2015 peak of 98.1 (the highest level since early 2004), according to the University of Michigan. A lot of has to do with Donald Trump’s surprise win: “When asked what news they had heard of recent economic developments, more consumers spontaneously mentioned the expected positive impact of new economic policies than ever before recorded in the long history of the surveys.”

The Department of Labor reported on December 8 that seasonally adjusted initial claims for unemployment insurance for the week ended December 3 were 258,000, a decline of 10,000 compared with the previous week. “This marks 92 consecutive weeks of initial claims below 300,000, the longest streak since 1970.”

The Commerce Department reported on December 6 that the U.S. goods and services trade deficit widened by 18%, to $42.6 billion, in October, from a revised $36.2 billion in September, exceeding a consensus estimate of $41.7 billion. That’s the biggest gap in four months and the biggest month-over-month expansion of the trade deficit in 19 months.

John Glenn, a combat-tested fighter pilot, the first American to orbit Earth, the last of the original Mercury 7 astronauts, a senator from Ohio from 1974—99, a candidate for the 1984 Democratic presidential nomination, the oldest person to fly in space, and a husband for 73 years, died last Thursday at 95. “Godspeed, John Glenn.”

Smart Investing,

David Dittman
Editorial Director, Wall Street Daily