- OPEC+ producers agree to nearly 2 million bpd of voluntary cuts
- Saudi Arabia will extend a voluntary cut of 1 million bpd
- Oil prices fell sharply on output cut compliance skepticism
Long considered myth, freakishly large rogue waves are very real and can split apart ships and even damage oil rigs. Using 700 years’ worth of wave data from more than a billion waves, scientists at the University of Copenhagen and University of Victoria have used artificial intelligence to find a formula for how to predict the occurrence of these maritime monsters. The new knowledge can make shipping safer.
Stories about monster waves, called rogue waves, have been the lore of sailors for centuries. But when a 26-metre-high rogue wave slammed into the Norwegian oil platform Draupner in 1995, digital instruments were there to capture and measure the North Sea monster. It was the first time that a rogue had been measured and provided scientific evidence that abnormal ocean waves really do exist.
Since then, these extreme waves have been the subject of much study. And now, researchers from the University of Copenhagen’s Niels Bohr Institute have used AI methods to discover a mathematical model that provides a recipe for how — and not least when — rogue waves can occur.
With the help of enormous amounts of big data about ocean movements, researchers can predict the likelihood of being struck by a monster wave at sea at any given time.
“Basically, it is just very bad luck when one of these giant waves hits. They are caused by a combination of many factors that, until now, have not been combined into a single risk estimate. In the study, we mapped the causal variables that create rogue waves and used artificial intelligence to gather them in a model which can calculate the probability of rogue wave formation,” says Dion Häfner.
Häfner is a former PhD student at the Niels Bohr Institute and first author of the scientific study, which has just been published in the journal Proceedings of the National Academy of Sciences (PNAS).
Rogue waves happen every day
In their model, the researchers combined available data on ocean movements and the sea state, as well as water depths and bathymetric information. Most importantly, wave data was collected from buoys in 158 different locations around US coasts and overseas territories that collect data 24 hours a day. When combined, this data — from more than a billion waves — contains 700 years’ worth of wave height and sea state information.
The researchers analyzed the many types of data to find the causes of rogue waves, defined as being waves that are at least twice as high as the surrounding waves — including extreme rogue waves that can be over 20 meters high. With machine learning, they transformed it all into an algorithm that was then applied to their dataset.
“Our analysis demonstrates that abnormal waves occur all the time. In fact, we registered 100,000 waves in our dataset that can be defined as rogue waves. This is equivalent around 1 monster wave occurring every day at any random location in the ocean. However, they aren’t all monster waves of extreme size,” explains Johannes Gemmrich, the study’s second author.
Artificial intelligence as a scientist
In the study, the researchers were helped by artificial intelligence. They used several AI methods, including symbolic regression which gives an equation as output, rather than just returning a single prediction as traditional AI methods do.
By examining more than 1 billion waves, the researchers’ algorithm has analyzed its own way into finding the causes of rogue waves and condensed it into equation that describes the recipe for a rogue wave. The AI learns the causality of the problem and communicates that causality to humans in the form of an equation that researchers can analyze and incorporate into their future research.
“Over decades, Tycho Brahe collected astronomical observations from which Kepler, with lots of trial and error, was able to extract Kepler’s Laws. Dion used machines to do with waves what Kepler did with planets. For me, it is still shocking that something like this is possible,” says Markus Jochum.
Phenomenon known since the 1700s
The new study also breaks with the common perception of what causes rogue waves. Until now, it was believed that the most common cause of a rogue wave was when one wave briefly combined with another and stole its energy, causing one big wave to move on.
However, the researchers establish that the most dominant factor in the materialization of these freak waves is what is known as “linear superposition.” The phenomenon, known about since the 1700s, occurs when two wave systems cross over each other and reinforce one another for a brief period of time.
“If two wave systems meet at sea in a way that increases the chance to generate high crests followed by deep troughs, the risk of extremely large waves arises. This is knowledge that has been around for 300 years and which we are now supporting with data,” says Dion Häfner.
The researchers’ algorithm is good news for the shipping industry, which at any given time has roughly 50,000 cargo ships sailing around the planet. Indeed, with the help of the algorithm, it will be possible to predict when this “perfect” combination of factors is present to elevate the risk of a monster wave that could pose a danger for anyone at sea.
“As shipping companies plan their routes well in advance, they can use our algorithm to get a risk assessment of whether there is a chance of encountering dangerous rogue waves along the way. Based on this, they can choose alternative routes,” says Dion Häfner.
Both the algorithm and research are publicly available, as are the weather and wave data deployed by the researchers. Therefore, Dion Häfner says that interested parties, such as public authorities and weather services, can easily begin calculating the probability of rogue waves. And unlike many other models created using artificial intelligence, all of the intermediate calculations in the researchers’ algorithm are transparent.
“AI and machine learning are typically black boxes that don’t increase human understanding. But in this study, Dion used AI methods to transform an enormous database of wave observations into a new equation for the probability of rogue waves, which can be easily understood by people and related to the laws of physics,” concludes Professor Markus Jochum, Dion’s thesis supervisor and co-author.
Gas accretion by a galaxy’s central supermassive black hole (SMBH) and the resultant energetic feedback by the accreting active galactic nucleus (AGN) on the gas in and around a galaxy are two tightly intertwined but competing processes that play a crucial role in the evolution of galaxies. Observations of galaxy clusters have shown how the plasma jets emitted by an AGN heat the intracluster medium, preventing cooling of the cluster gas and thereby the infall of this gas onto the central galaxy. On the other hand, outflows of multiphase gas, driven by the jets, can cool as they rise into the intracluster medium, leading to filaments of colder gas. The fate of this cold gas is unclear, but it has been suggested that it plays a role in feeding the central SMBH. We present the results of reprocessed CO(2-1) Atacama Large Millimeter/submillimeter Array observations of the cold molecular gas in the central regions of NGC 1275, the central galaxy of the Perseus cluster and which hosts the radio-loud AGN 3C 84 (Perseus A). These data show in detail how kiloparsec-sized cold gas filaments resulting from the jet-induced cooling of cluster gas are flowing towards the galaxy centre and how they feed the circum-nuclear accretion disk (100 pc diameter) of the SMBH. Thus, cooled gas can, in this way, play a role in feeding the AGN. These results complete our view of the feedback loop of how an AGN can impact its surroundings and how the effects of this impact maintain the AGN activity.
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The calibrated data cube is available from https://astrodrive.astro.rug.nl/index.php/s/g1y6QlCeGFd5XiG, or from the corresponding author on reasonable request.
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This work is based on reprocessing of the ALMA observations carried out under project number 2017.0.01257.S and which were published in original form by Nagai et al.16.
The authors declare no competing interests.
Nature Astronomy thanks Alastair Edge and Jeremy Lim for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Oosterloo, T., Morganti, R. & Murthy, S. Closing the feedback-feeding loop of the radio galaxy 3C 84.
Nat Astron (2023). https://doi.org/10.1038/s41550-023-02138-y
Received: 31 March 2023
Accepted: 19 October 2023
Published: 30 November 2023
Nov 30 (Reuters) – Oil prices fell on Thursday after rising by more than 1% earlier in the session after OPEC+ oil producers agreed to voluntary output cuts approaching 2 million barrels per day (bpd) for early next year, with each country announcing separately its voluntary cut.
Brent crude futures for January fell by 50 cents, or 0.6%, to $82.60 a barrel by 11:30 a.m. EDT (1630 GMT). The front-month Brent contract, down about 6% on the month, expires later on Thursday.
The more liquid February contract was down $2.54, or 3.1%, at $80.34.
U.S. West Texas Intermediate crude futures fell by $2.63, or 3.4%, to $75.24, and is down about 9% on the month.
Brent’s premium to U.S. WTI futures hit its highest since January in the session.
Saudi Arabia, Russia and other members of OPEC+, who pump more than 40% of the world’s oil, held a virtual meeting on Thursday to discuss 2024 output amid concerns the market faces a potential surplus.
OPEC+ said the latest agreement would involve cuts approaching 2 million bpd, including Saudi Arabia extending a voluntary cut of 1 million bpd it has had in place since July.
Their output of some 43 million bpd already reflects cuts of about 5 million bpd aimed at supporting prices and stabilising the market.
The additional OPEC+ cuts for the first quarter of 2024 are set to be voluntary, a delegate said. Each country will announce separately its voluntary cut, according to a source familiar with the matter.
But there is a large degree of skepticism on how individual OPEC members will reach those cuts, according to Bob Yawger, director of energy futures at Mizuho.
“This is a very sketchy report – there is a huge question of their credibility in how these cuts will happen,” Yawger said, adding that the UAE is supposed to be increasing production by 200,000 bpd by 2024.
Nigeria has been given a 2024 output quota of 1.5 million barrels per day (bpd), Angola 1.11 million bpd and Congo 0.277 million bpd, a draft statement from OPEC+ seen by Reuters showed.
Russia will cut 500,000 bpd and others will also contribute cuts, one source said.
Algeria’s energy minister told Reuters his country had agreed to curb its output by 50,000 bpd.
OPEC+ oil-producing countries meeting on Thursday to discuss 2024 output levels will convene again next June on 2024 output levels, according to a source familiar with the matter.
The meeting, being held on the same day as global leaders gather in Dubai for the U.N. climate conference, was originally scheduled for last week but was deferred because of disagreements over output quotas for African producers.
The OPEC+ Joint Ministerial Monitoring Committee (JMMC) ended its meeting on Thursday without making a recommendation regarding 2024 output levels, three delegates told Reuters.
The committee met ahead of the wider meeting of ministers from the OPEC+ group of oil-producing nations.
Implementing additional cuts will send prices higher in the immediate future, but the long-term impact is harder to predict, said Tamas Varga of oil broker PVM.
Compliance will be an issue and the global oil balance is probably much less tight than OPEC estimates, he said, citing the latest commercial inventory data out of the United States and the effect on demand from stubbornly high interest rates in many major economies.
Reporting by Laura Sanicola in Washington, Robert Harvey and Natalie Grover in London and Jeslyn Lerh in Singapore
Additional reporting by Laura Sanicola in Washington
Editing by David Goodman, Kirsten Donovan and Lisa Shumaker
Our Standards: The Thomson Reuters Trust Principles.
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