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Is it an earthquake, a nuclear test or a hurricane? How seismometers help us understand the world we live in

Is it an earthquake, a nuclear test or a hurricane? How seismometers help us understand the world we live in

Although traditionally used to study earthquakes, like today’s M 8.1 in Mexico,  seismometers have now become so sophisticated they are able to detect the slightest ground movements; whether they come from deep within the bowels of the planet or are triggered by events at the surface. But how, exactly, do earthquake scientists decipher the signals picked up by seismometers across the world? And more importantly, how do they know whether they are caused by an earthquake, nuclear test or a hurricane?  

To find out we asked Neil Wilkins (a PhD student at the University of Bristol) and Stephen Hicks (a seismologist at the University of Southampton) to share some insights with our readers.


Seismometers are highly sensitive and they are able to detect a magnitude 5 earthquake occurring on the other side of the planet. Also, most seismic monitoring stations have sensors located within a couple of meters of the ground surface, so they can be fairly susceptible to vibrations at the surface. Seismologists can “spy” on any noise source, from cows moving in a nearby field to passing trucks and trains.

A nuclear test

On Sunday the 3rd of September, North Korea issued a statement announcing it had successfully tested an underground hydrogen bomb. The blast was confirmed by seismometers across the globe. The U.S.  Geological Survey registered a 6.3 magnitude tremor, located at the Punggye-ri underground test site, in the northwest of the country. South Korea’s Meteorological Administration’s earthquake and volcano center also detected what is thought to be North Korea’s strongest test to date.

However they occur, explosions produce ground vibrations capable of being detected by seismic sensors. Mining and quarry blasts appear frequently at nearby seismic monitoring stations. In the case of nuclear explosions, the vibrations can be so large that the seismic waves they produce can be picked up all over the world, as in the case of this latest test.

It was realised quite early in the development of nuclear weapons that seismology could be used to detect such tests. In fact, the need to have reliable seismic data for monitoring underground nuclear explosions led in part to the development of the Worldwide Standardized Seismograph Network in the 1960s, the first of its kind.

Today, more than 150 seismic stations are operating as part of the International Monitoring System (IMS) to detect nuclear tests in breach of the Comprehensive Test-Ban Treaty (CTBT), which opened for signatures in 1996. The IMS also incorporates other technologies, including infrasound, hydroacoustics and radionuclide monitoring.

The key to determining whether a seismic signal is from an explosion or an earthquake lies in the nature of the waves that are present. There are three kinds of seismic wave seismologists can detect. The fastest, called Primary (P) waves, cause ground vibrations in the same direction that they travel, similar to sound waves in the air. Secondary (S) waves cause shaking in a perpendicular direction. Both P and S waves travel deep through the Earth and are known collectively as body waves. In contrast, the third type of seismic waves are known as surface waves, because they are trapped close to the surface of the Earth. In an earthquake, it is normally surface waves that cause the most ground shaking.

In an explosion, most of the seismic energy is released outwards as the explosive material rapidly expands. This means that the largest signal in the seismogram comes as P waves. Explosions therefore have a distinctive shape in the seismic data when compared with an earthquake, where we expect S and surface waves to have higher amplitude.

Forensic seismologists can therefore make measurements of the seismic data to determine whether there was an explosion. An extra indication that a nuclear test occurred can also be revealed by measuring the depth of the source of the waves, as it would not be possible to place a nuclear device deeper than around 10 km below the surface.

Yet while seismic data can tell us that there has been an explosion, there is nothing that can directly identify that explosion as being nuclear. Instead, the IMS relies on the detection of radioactive gases that can leak from the test site for final confirmation of what kind of bomb was used.

The figure shows (at the bottom) the seismic recording of the latest test in North Korea made at NORSAR’s station in Hedmark, Norway. The five upper traces show recordings at the same station for the five preceding tests, conducted by North Korea in 2006, 2009, 2013 and 2016 (two explosions in 2016). The 2017 test, is as can be seen from this figure, clearly the strongest so far. Credit: NORSAR.

When North Korea conducted a nuclear test in 2013, radioactive xenon was detected 55 days later, but this is not always possible. Any detection of such gases depends on whether or not a leak occurs in the first place, and how the gases are transported in the atmosphere.

Additionally, the seismic data cannot indicate the size of the nuclear device or whether it could be attached to a ballistic missile, as the North Korean government claims.

What seismology can give us is an idea of the size of the explosion by measuring the seismic magnitude. This is not straightforward, and depends on knowledge of exactly how deep the bomb was buried and the nature of the rock lying over the test site. However, by comparing the magnitude of this latest test with those from the previous five tests conducted in North Korea, we can see that this is a much larger explosion.

The Norwegian seismic observatory NORSAR has estimated a blast equivalent to 120 kilotons of TNT, six times larger than the atomic bomb dropped on Nagasaki in 1945, and consistent with the expected yield range of a hydrogen bomb.

Hurriquakes?

Nuclear tests are not the only hazard keeping our minds busy in the past few weeks. In the Atlantic, Hurricanes Harvey, Irma and Katia have wreaked havoc in the southern U.S.A, Mexico and the Caribbean.

Hurricanes in the Atlantic can occur at any time between June and November. According to hurricane experts, we are at the peak of the season. It is not uncommon for storms to form in rapid succession between August, September and October.

The National Hurricane Centre (NHC) is the de facto regional authority for producing hurricane forecasts and issuing alerts in the Atlantic and eastern Pacific. For their forecasts, meteorologists use a combination of on the ground weather sensors (e.g. wind, pressure, Doppler radar) and satellite data.

As hurricane Irma tore its way across the Atlantic, gaining strength and approaching the Caribbean island of Guadeloupe, local seismometers detected its signature, sending the global press into a frenzy. It may come as a slight surprise to some people that storms and hurricanes also show on seismometers.

However, a seismometer detecting an approaching hurricane is not actually that astonishing. There is no evidence to suggest that hurricanes directly cause earthquakes, so what signals can we detect from a hurricane? Rather than “signals”, seismologists tend to refer to this kind of seismic energy as “noise” as it thwarts our ability to see what we’re normally looking out for – earthquakes.

The seismic noise from a storm doesn’t look like distinct “pings” that we would see with an earthquake. What we see are fairly low-pitched “hums” that gradually get louder in the days and hours preceding the arrival of a storm. As the storm gets closer to the sensor, these hums turn into slightly higher-pitched “rustling”. This seismic energy then wanes as the hurricane drifts away. We saw this effect clearly for Hurricane Irma with recordings from a seismometer on the island of Guadeloupe.

What causes these hums and rustles? If you look at the frequency content of seismic data from any monitoring station around the globe, noise levels light up at frequencies of ~0.2 Hz (5 s period). We call these hums “microseism”. Microseism is caused by persistent seismic waves unrelated to earthquakes, and it occurs over huge areas of the planet.  One of the strongest sources of microseism is caused by ocean waves and swell. During a hurricane, swell increases and ocean waves become more energetic, eventually crashing into coastlines, transferring seismic energy into the ground. This effect is more obvious on islands as they are surrounded by water.

As the hurricane gets closer to the island, wind speeds dramatically increase and may dwarf the noise level of the longer period microseism. Wind rattles trees, telegraph poles, and the surface itself, transferring seismic energy into the ground and moving the sensitive mass inside the seismometer. This effect causes higher-pitched “rustles” as the centre of the storm approaches. Gusts of wind can also generate pressure changes inside the seismometer installation and within the seismometer itself, generating longer period fluctuations.

During Hurricane Irma, a seismic monitoring station located in the Dutch territory of St. Maarten clearly recorded the approach of the storm, leading to an intense crescendo as the eyewall crossed the area. As the centre of the eye passed over, the seismometer seems to have recorded a slightly lower noise level. This observation could be due to the calmer conditions and lower pressure within the eye. The station went down shortly after, probably from a power outage or loss in telemetry which provides the data in real-time.

Seismometers measuring storms is not a new observation. Recently, Hurricane Harvey shook up seismometers located in southern Texas. Even in the UK, the approach of winter storms across the Atlantic causes much higher levels of microseism.

It would be difficult to use seismometer recordings to help forecast a hurricane – the recordings really depend on how close the sensor is to the coast and how exposed the site is to wind. In the event of outside surface wind and pressure sensors being damaged by the storm, protected seismometers below the ground could possibly prove useful in delineating the rough location of the hurricane eye, assuming they maintain power and keep sending real-time data.

At least several seismic monitoring stations in the northern Antilles region were put out of action by the effects of the Hurricane. Given the total devastation on some islands, it is likely that it will take at least several months to bring these stations back online. The Lesser Antilles are a very tectonically active and complex part of Earth; bringing these sensors back into operation will be crucial to earthquake and volcano hazard monitoring in the region.

By Neil Wilkins (PhD student at the University of Bristol) and Steven Hicks (a seismologist at the University of Southampton)

References and further reading

GeoSciences Column: Can seismic signals help understand landslides and rockfalls?

NORSAR Press Release: Large nuclear test in North Korea on 3 September 2017

The Comprehensive Nuclear-Test-Ban Organization Press Release: CTBTO Executive Secretary Lassina Zerbo on the unusual seismic event detected in the Democratic People’s Republic of Korea

First Harvey, Then Irma and Jose. Why? It’s the Season (The New York Times)

NOAA  National Hurricane Center

IRIS education and outreach series: How does a seismometer work?

GeoTalk: A smart way to map earthquake impact

GeoTalk: A smart way to map earthquake impact

Last week at the 2016 General Assembly Sara, one of the EGU’s press assistants, had the opportunity to speak to Koen Van Noten about his research into how crowdsourcing can be used to find out more about where earthquakes have the biggest impact at the surface.

Firstly, can you tell me a little about yourself?

I did a PhD in structural geology at KULeuven and, after I finished, I started to work at the Royal Observatory of Belgium. What I do now is try to understand when people feel an earthquake, why they can feel it, how far away from the source they can feel it, if local geology affects the way people feel it and what the dynamics behind it all are.

How do you gather this information?

People can go online and fill in a ‘Did You Feel It?’ questionnaire about their experience. In the US it’s well organised because the USGS manages this system in whole of the US. In Europe we have so many institutions, so many countries, so many languages that almost every nation has its own questionnaire and sometimes there are many inquiries in only one country. This is good locally because information about a local earthquake is provided in the language of that country, but if you have a larger one that crosses all the borders of different countries then you have a problem. Earthquakes don’t stop at political borders; you have to somehow merge all the enquiries. That’s what I’m trying to do now.

European institutes that provide an online "Did You Feel the Earthquake?" inquiry. (Credit: Koen Van Noten)

European institutes that provide an online “Did You Feel the Earthquake?” inquiry. (Credit: Koen Van Noten)

There are lots of these databases around the world, how do you combine them to create something meaningful?

You first have to ask the different institutions if you can use their datasets, that’s crucial – am I allowed to work on it? And then find a method to merge all this information so that you can do science with it.

You have institutions that capture global data and also local networks. They have slightly different questions but the science behind them is very similar. The questions are quite specific, for instance “were you in a moving vehicle?” If you answer yes then of course the intensity of the earthquake has to be larger than one felt by somebody who was just standing outside doing nothing and barely felt the earthquake. You can work out that the first guy was really close to the epicentre and the other guy was probably very far, or that the earthquake wasn’t very big.

Usually intensities are shown in community maps. To merge all answers of all institutes, I avoid the inhomogeneous community maps. Instead I use 100 km2 grid cell maps and assign an intensity to every grid cell.. This makes the felt effect easy to read and allows you to plot data without giving away personal details of any people that responded. Institutes do not always provide a detailed location, but in a grid cell the precise location doesn’t matter. It’s a solution to the problem of merging databases within Europe and also globally.

Underlying geology can have a huge impact on how an earthquake is felt.  Credit: Koen Van Noten.

Underlying geology can have a huge impact on how an earthquake is felt. 2011 Goch ML 4.3 earthquake.  Credit: Koen Van Noten.

What information can you gain from using these devices?

If you make this graph for a few earthquakes, you can map the decay in shaking intensity in a certain region. I’m trying to understand how the local geology affects these kinds of maps. Somebody living on thick pile of sands, several kilometres above the hypocentre, won’t feel it because the sands will attenuate the earthquake. They are safe from it. However, if they’re directly on the bedrock, but further from the epicentre, they may still feel it because the seismic waves propagate fast through bedrock and aren’t attenuated.

What’s more, you can compare recent earthquakes with ones that happened 200 years ago at the same place. Historical seismologists map earthquake effects that happened years ago from a time when no instrumentation existed, purely based on old personal reports and journal papers. Of course the amount of data points isn’t as dense as now, but even that works.

Can questionnaires be used as a substitute for more advanced methods in areas that are poorly monitored?

Every person is a seismometer. In poorly instrumented regions it’s the perfect way to map an earthquake. The only thing it depends on is population density. For Europe it’s fine, you have a lot of cities, but you can have problems in places that aren’t so densely populated.

Can you use your method to disseminate information as well as gather it, say for education?

The more answers you get, the better the map will be. Intensity maps are easier to understand by communities and the media because they show the distribution of how people felt it, rather than a seismogram, which can be difficult to interpret.

What advice would you give to another researcher wanting to use crowd-sourced information in their research?

First get the word out. Because it’s crowd-sourced, they need to be warned that it does exist. Test your system before you go online, make sure you know what’s out there first and collaborate. Collaborating across borders is the most important thing to do.

Interview by Sara Mynott, EGU Press Assistant and PhD student at Plymouth University.

Koen presented his work at the EGU General Assembly in Vienna. Find out more about it here.

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