The ‘pulse’ of a volcano can be used to help predict its next eruption


The 2018 eruption of Kilauea volcano was preceded by damage of the magma plumbing system at the summit.
Courtesy of Grace Tobin, 60 Minutes, Author provided

Rebecca Carey, University of Tasmania

Predicting when a volcano will next blow is tricky business, but lessons we learned from one of Hawaii’s recent eruptions may help.

Kīlauea, on the Big Island of Hawai’i, is probably the best understood volcano on Earth. That’s thanks to monitoring and gathered information that extends back to the formation of the Hawaiian Volcano Observatory in 1912.

The volcano is also subject to the world’s most technologically advanced geophysical monitoring network.




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From the skies, satellites collect data that show the changing topography of the volcano as magma moves throughout the internal magma plumbing system. Satellites also look at the composition of volcanic gases.

From the ground, volcanologists use a number of highly sensitive chemical and physical tools to further understand the structure of that magma plumbing system. This helps to study the movement of magma within the volcano.

Earthquakes and vibrations

A lynch pin of volcano monitoring is seismicity – how often, where and when earthquakes occur. Magma movement within the volcano triggers earthquakes, and putting together the data on their location (a technique known as triangulation) tracks the path of magma underground.

A schematic of the deep magma plumbind system of Kilauea volcano, Big Island, Hawaii. Magma is transported from deep within the Earth and arrives in a series of summit magma reservoirs.
USGS

A newer technique, seismic interferometry, uses vibrations of energy from ocean waves hitting the distant shorelines that then travel through the volcano.

Changes in the speed of these vibrations help us map the 3D footprint of the volcano’s magma plumbing system. We can then detect when, and in some cases how, the magma plumbing system is changing.

This monitoring provides the “pulse” of the volcano during times of inactivity – a baseline from which to detect change during volcanic unrest. This proved invaluable for early warning, and the prediction of where and when, of the eruption of Kīlauea on May 3, 2018.

The “pulse” of Kīlauea includes cycles of volcano inflation (bulging) and deflation (contraction) as magma moves into and out of the storage region at the summit of the volcano.

The speeds of vibrations travelling through the volcano are predictable during observations of inflation/deflation cycles. When the volcano bulges, the vibrations travel faster through the volcano as rock and magma is compressed. When the volcano contracts these speeds decrease.

We describe this relationship between the two sets of data – the bulging/contraction and the faster/slower speed of vibrations – as coupled.

Something changed

Compared to our baseline, we saw the coupled data shift 10 days before the Kīlauea eruption on May 3. That told scientists the magma plumbing system had changed in a significant way.

The volcano was bulging due to the buildup of pressure inside the magma chamber, but the seismic waves were slowing down quite dramatically, instead of speeding up.

Our interpretation of this data was that the summit magma chamber was not able to sustain the pressure from an increasing magma supply – the bulge was too big. Rock material started to break around the summit magma chamber.

Breakage of the rocks perhaps then led to changes of the summit magmatic system so that more magma could more easily arrive at the eruption site about 40km away.

As well as Kīlauea, such coupled data sets are regularly collected, investigated and interpreted in terms of magma transport at other volcanoes globally. Sites include Piton de la Fournaise on Reunion Island, and Etna volcano, Italy.

But our modelling was the first to demonstrate these changes in the coupled data relationship could occur due to weakening of the material inside the volcano before an eruption.

The damage model that we applied can now be used for other volcanoes in a state of unrest. This adds to the toolbox volcanologists need to predict the when and where of an impending eruption.

So much data, we need help

When volcanoes are in a heightened state of unrest, the volume of information available from digital data and ground observations is extreme. Scientists tend to rely on observational monitoring first, and other data when time and extra people are available.

But the total amount of incoming data (such as from satellites) is overwhelming, and scientists simply can’t keep up. Machine learning might be able to help us here.

Artificial intelligence is the new kid on the block for eruption prediction. Neural networks and other algorithms can use high volumes of complex data and “learn” to distinguish between different signals.




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Automated early alert systems of an impending eruption using sensor arrays exist for some volcanoes today, for example at Etna volcano, Italy. It’s likely that artificial intelligence will make these systems more sophisticated in the future.

Early detection sounds wonderful for authorities charged with public safety, but many volcanologists are wary.

If they lead to multiple false alarms then that could slash trust in scientists for both managers of volcanic crises and the public alike.The Conversation

Rebecca Carey, Senior Lecturer in Earth Sciences, University of Tasmania

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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To predict droughts, don’t look at the skies. Look in the soil… from space


Siyuan Tian, Australian National University and Albert Van Dijk, Australian National University

Another summer, another drought. Sydney’s water storages are running on empty, and desalinisation plants are being dusted off. Elsewhere, shrunken rivers, lakes and dams are swollen with rotting fish. Governments, irrigators and environmentalists blame each other for the drought, or just blame it on nature.

To be sure, Australia is large enough to usually leave some part of our country waiting for rain. So what exactly is a drought, and how do we know when we are in it?

This question matters, because declaring drought has practical implications. For example, it may entitle those affected to government assistance or insurance pay-outs.

But it is also a surprisingly difficult question. Droughts are not like other natural hazards. They are not a single extreme weather event, but the persistent lack of a quite common event: rain. What’s more, it’s not the lack of rain per se that ultimately affects us. The desert is a dry place but it cannot always be called in drought.

Ultimately, what matters are the impacts of drought: the damage to crops, pastures and environment; the uncontrollable fires that can take hold in dried-up forests and grasslands; the lack of water in dams and rivers that stops them from functioning. Each of these impacts is affected by more than just the amount of rain over an arbitrary number of months, and that makes defining drought difficult.




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Scientists and governments alike have been looking for ways to measure drought in a way that relates more closely to its impacts. Any farmer or gardener can tell you that you don’t need much rain, but you do need it at the right time. This is where the soil becomes really important, because it is where plants get their water.

Too much rain at once, and most of it is lost to runoff or disappears deep into the soil. That does not mean it is lost. Runoff helps fill our rivers and waterways. Water sinking deep into the soil can still be available to some plants. While our lawn withers, trees carry on as if there is nothing wrong. That’s because their roots dig further, reaching soil moisture that is buried deep.

A good start in defining and measuring drought would be to know how much soil moisture the vegetation can still get out of the soil. That is a very hard thing to do, because each crop, grass and tree has a different root system and grows in a different soil type, and the distribution of moisture below the surface is not easy to predict. Many dryland and irrigation farmers use soil sensors to measure how well their crops are doing, but this does not tell us much about the rest of the landscape, about the flammability of forests, or the condition of pastures.

Not knowing how drought conditions will develop, graziers face a difficult choice: sell their livestock or buy in feed?
Shutterstock

Soils and satellites

As it turns out, you need to move further away to get closer to this problem – into space, to be precise. In our new research, published in Nature Communications, we show just how much satellite instruments can tell us about drought.

The satellite instruments have prosaic names such as SMOS and GRACE, but the way they measure water is mind-boggling. For example, the SMOS satellite unfurled a huge radio antenna in space to measure very specific radio waves emitted by the ground, and from it scientists can determine how much moisture is available in the topsoil.

Even more amazingly, GRACE (now replaced by GRACE Follow-On) was a pair of laser-guided satellites in a continuous high-speed chase around the Earth. By measuring the distance between each other with barely imaginable accuracy, they could measure miniscule changes in the Earth’s gravitational field caused by local increases or decreases in the amount of water below the surface.

By combining these data with a computer model that simulates the water cycle and plant growth, we created a detailed picture of the distribution of water below the surface.

It is a great example showing that space science is not just about galaxies and astronauts, but offers real insights and solutions by looking down at Earth. It also shows why having a strong Australian Space Agency is so important.




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Taking it a step further, we discovered that the satellite measurements even allowed us to predict how much longer the vegetation in a given region could continue growing before the soils run dry. In this way, we can predict drought impacts before they happen, sometimes more than four months in advance.

Map showing how many months ahead, on average, drought impacts can be predicted with good accuracy.
author provided

This offers us a new way to look at drought prediction. Traditionally, we have looked up at the sky to predict droughts, but the weather has a short memory. Thanks to the influence of ocean currents, the Bureau of Meteorology can sometimes give us better-than-evens odds for the months ahead (for example, the next three months are not looking promising), but these predictions are often very uncertain.

Our results show there is at least as much value in knowing how much water is left for plants to use as there is in guessing how much rain is on the way. By combining the two information sources we should be able to improve our predictions still further.

Many practical decisions hinge on an accurate assessment of drought risk. How many firefighters should be on call? Should I sow a crop in this paddock? Should we prepare for water restrictions? Should we budget for drought assistance? In future years, satellites keeping an eye on Earth will help us make these decisions with much more confidence.The Conversation

Siyuan Tian, Postdoctoral fellow, Australian National University and Albert Van Dijk, Professor, Water and Landscape Dynamics, Fenner School of Environment & Society, Australian National University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

19th century weather data is helping climate scientists predict the future


Linden Ashcroft, Universitat Rovira i Virgili; Howard Bridgman, University of Newcastle, and Ken Thornton, University of Newcastle

The 19th-century English historian Lord Acton famously advised people to live in both the future and the past, and said “those who do not live in the past cannot live in the future”.

It may seem a stretch to apply this famous quotation to climate research, but we can’t possibly understand how the climate will change in the future without first understanding how it changed in the past.

Australia’s official climate record, kept by the Bureau of Meteorology, begins in 1910. But historical climate records kept before the development of national meteorological organisations are valuable tools for improving our understanding of what has happened in the past.

They also put the present into a long-term context, and improve climate models used to predict the future.

What can old numbers really tell us?

One thing historical records can help us understand is extreme weather events – the aspect of climate change that has people most concerned. How can we prepare cities and buildings for storms in the future without understanding what previous storms have done?

It is true that historical observations have reliability issues and are sometimes hard to compare to modern observations, which are recorded in a standard way. However, old weather records can still tell us a lot about year-to-year changes, and there are many ways to minimise reliability problems.

There are several climate and weather analysis products that recreate how the atmosphere behaved over time. In the Southern Hemisphere, these climate tools are generally uncertain until the mid-20th century, due to a lack of – you guessed it — long-term data.

Historical records can also help us hone climate models for predicting the future. Some of the atmospheric and oceanic features that dominate our climate have cycles that can last several decades. This means that modern climate data starting in the 20th century may only capture one or two cycles of a particular feature, making it hard to train climate models on the full range of our climate variability.

Historical weather records are also important for past climate analysis. Extracting the climate signal from tree rings, ice cores, or documentary data, requires instrumental climate records for comparison. The longer the climate records are, the better this comparison will be.

What exists for Australia?

In the past few years, concerted efforts at the Bureau of Meteorology and several universities have been able to recover and analyse a large amount of historical climate data for Australia. Most of these observations come from Australia’s southeast, as this is the region that was first colonised by Europeans.

There are now studies that explore temperature, rainfall and atmospheric pressure variability in southeastern Australia back to the 1860s. Several studies have even rescued data from 1788.

With these newly recovered observations, we have learned a lot about Australia’s climate in the 19th century, as well as the early years of English colonisation. But there is still a lot we don’t know.

In particular, the majority of our old weather data come from coastal locations, where the weather is more sensitive to local factors rather than large-scale features such as the El Niño–Southern Oscillation (ENSO).

A rare opportunity

In 2011, some weather diaries were donated to the University of Newcastle and University of New England. The diaries contain 45 years of daily handwritten weather observations of a Mr Algernon Belfield taken on his 8,000-hectare property, Eversleigh, near Armidale in northern New South Wales.

A H Belfield at Eversleigh
Belfield Family

A pastoralist, amateur meteorologist and astronomer, Belfield took these meticulous weather observations every morning at 9am from June 1877 until August 1922, a month before his death.

His observations continued through the period of the 1891 shearers’ strike, the Boer War, Australia’s Federation, the First World War and the Centennial and Federation droughts.

Belfield’s diaries also span the period that inspired Dorothea Mackellar’s famous ode to Australia, My Country.

The last few decades of the 19th century were indeed times of “droughts and flooding rains”, thanks to a string of La Niña and El Niño phases of ENSO.

Belfield weather diaries
Ken Thornton (Author)

Belfield’s steady hand captured the weather at Eversleigh during a time of dramatic variability before the impact of human-induced climate change, in a region where the climate is highly correlated with ENSO.

His detailed records, therefore, provide us with a unique opportunity to uncover more about this period in our climate history than ever before.

The handwritten records are scanned but need to be transcribed into a digitised format. We are looking for volunteers to help us with this important task of recovering our climate history. If you are interested, please contact us here, to help shed light on Australia’s past, present and future climate.

The Conversation

Linden Ashcroft, Senior Researcher, Universitat Rovira i Virgili; Howard Bridgman, Conjoint Professor, University of Newcastle, and Ken Thornton, Affiliate, Cultural Collections, University of Newcastle

This article was originally published on The Conversation. Read the original article.

Fires are increasing in warming world, but a new model could help us predict them


Ritaban Dutta, CSIRO

Over the past decade, the frequency of bushfires in Australia has increased. The Forest Fire Danger Index – which measures the frequency and severity of the weather most conducive to fire – has increased dramatically since the 1970s, and particularly in the 1990s and 2000s. This – along with a great deal of other evidence – indicates that a major change in the climate is looming.

In a study published today in Royal Society Open Science, we show that bushfire frequency has increased by 40% over the past five years.

This is part of our work to better predict bushfires using weather information. We developed a model that can predict bushfires over a week-long period with an accuracy of 91%. While we can’t yet use this to predict fires definitively, it is a big step forward in planning for and predicting fires.

There is an urgent need for scientific research that can contribute to Australia’s future bushfire preparedness. The knowledge gained from this research could help save lives and property, underpin effective building codes and help land-management decisions.

Fire forecasting gets smart

We wanted to find bushfire “hotspots” – places where a bushfire might happen in the future based on recent weather patterns. They don’t show that a bushfire will definitely happen, and similarly we need to be careful that people don’t assume a fire won’t happen if there is no hotspot.

To do this we developed a model that combined data on fires (from satellite images) with data on climate, including soil moisture, dry fuel load, wind speed, temperature and humidity.

We are using a machine learning approach to model future bushfire hotspots – in short, a form of artificial intelligence that allows the model to learn on its own. Our model used other forms of learning to produce maps of bushfire hotspots.

Map showing predicted hotspots (green) and real fires (purple). Red dots show fires not predicted by the model.
Ritaban Dutta

Predicting hotspots

We tested our model by looking at bushfires retrospectively. Our predictions achieved 91% global accuracy. The analysis also indicates that, on a week-by-week basis, the frequency of Australian bushfires, particularly during summer months, has increased by 40% over the past five years.

We conducted extensive research in Australian bushfire history, to make sure the data on the conditions and behaviour of 36 major fires were correct.

Two types of Australian vegetation are prone to fire: grasslands and forests. We found that our model could predict both.

Fighting fires

Although new technologies are being developed to manage the growing number of unplanned bushfires in Australia, we do not have, and are never likely to have, a way to avert natural fire disasters.

The recent history of Australian bushfires indicates that the most effective way to save lives is early planned evacuation, combined with timely advice and alerts to the people potentially at risk.

Early estimation of the likely frequency of future bushfires, and accurate hot-spot estimation of the locations most likely to be affected could provide great support to land managers, and assist in reducing the damage caused.

But as yet, our system exists only as a research model. Its impact and effectiveness could only be fully evaluated if a real system were implemented as a decision support tool for land managers and emergency services, to accurately forecast the most likely bushfire hot spots, at a detailed and fine-grained resolution and a timely scale.

The Conversation

Ritaban Dutta, Senior Research Scientist and Research Project Leader, Data61, CSIRO

This article was originally published on The Conversation. Read the original article.