Tyler O'Neal, Staff Editor APPLICATIONS

SwRI, international team use deep learning to create virtual 'super instrument'

Virtual instrument can analyze complex data through advanced artificial intelligence and learn to synthesize useful scientific data

A study co-written by a Southwest Research Institute scientist describes a new algorithm that combines the capabilities of two spacecraft instruments, which could result in lower cost and higher efficiency space missions. The virtual "super instrument," is a computer algorithm that utilizes deep learning to analyze ultraviolet images of the Sun, taken by NASA's Solar Dynamics Observatory, and measure the energy that the Sun emits as ultraviolet light.

"Deep learning is an emerging capability that is revolutionizing the way we interact with data," said Dr. Andrés Muñoz-Jaramillo, senior research scientist at SwRI. Muñoz-Jaramillo co-authored the study, published this month in Science Advances, alongside collaborators from nine other institutions as part of NASA's Frontier Development Laboratory. The laboratory is an applied artificial intelligence research accelerator that applies deep learning and machine learning techniques to challenges in space science and exploration. {module In-article}

Deep learning is a type of machine learning methods that mimic the way the human brain processes information. The result of deep learning is machines accomplishing things that previously required human intelligence, such as translation between foreign languages, driving a vehicle and facial recognition. Things like Netflix suggesting what to watch next, an iPhone unlocking upon sight of its owner's face and Alexa responding to a vocal request are all results of deep learning.

"All missions beyond Earth have a host of instruments that have been designed with specific capabilities to answer specific scientific questions," Muñoz-Jaramillo said. "When we combine them into virtual super instruments, we can produce more cost-effective missions with higher scientific impact or use measurements by one instrument to help answer the science questions of another."

Muñoz-Jaramillo stresses in the study that these virtual super instruments will not make hardware obsolete. They will always require a spacecraft to collect the necessary data for virtualization.

"Deep learning instruments cannot make something out of nothing, but they can significantly enhance the capabilities of existing technology," he said.

Their virtual super instrument is already in use as part of a Frontier Development Laboratory project for forecasting ionospheric disturbances. Muñoz-Jaramillo is currently working on additional super instruments that combine other capabilities.

"In essence, deep learning involves sophisticated transformation of data," he said. "We can make these transformations into scientifically useful data and modernize the way we view not just the Sun, but a great number of scientific questions."

UMD scientists create method for first global picture of mutual predictability of atmosphere, ocean

Tyler O'Neal, Staff Editor APPLICATIONS

World-renowned climate scientist J. Shukla calls the new paper by University of Maryland scientists 'a very important paper in the history of predictability research'

University of Maryland (UMD) scientists have carried out a novel statistical analysis to determine for the first time a global picture of how the ocean helps predict the low-level atmosphere and vice versa. They observed ubiquitous influence of the ocean on the atmosphere in the extratropics, which has been difficult to demonstrate with dynamic models of atmospheric and oceanic circulation. The results are published today in the Journal of Climate, "Local atmosphere-ocean predictability: dynamical origins, lead times, and seasonality." The study discovered for the first time ubiquitous influence of the ocean on the atmosphere (left), and reveal the detailed spatial structures of the atmosphere's influence on the ocean (right).{module In-article}

The research draws on a classic statement often heard in introductory statistics classes that "correlation is not causation." Clive Granger was a Nobel-laureate mathematician who came up with a novel method to address this issue by distinguishing correlation from causation.

"The Granger method relies upon a simple but important notion that a cause precedes its effect, and should improve the prediction of its effect in the future. We realized that this could be a powerful method to study the interactions between atmosphere and ocean, and to provide a global picture of how well they predict each other," said applied mathematician Safa Motesharrei, an Environmental Systems Scientist at UMD. "This method sheds light on both the potential to better predict regional climate as well as the nature of the interactions."

"There are many physical processes that govern the interaction between the atmosphere and ocean," said lead author Eviatar Bach, PhD student in the Department of Atmospheric and Oceanic Science (AOSC) at UMD. "For example, wind blowing on the ocean surface creates currents, and the sea surface heats up the lower atmosphere. These interactions between the atmosphere and ocean play a major role in climate and our ability to predict it, so understanding their geographical structure is important."

"It has been known that in the tropical oceans, the ocean is predominantly driving the atmospheric changes, while in the extratropics the atmosphere generally drives the ocean," said co-author Eugenia Kalnay, Distinguished University Professor of AOSC at UMD. "I developed a dynamical rule to determine the direction of the forcing in 1986, and others have addressed this question using climate models.This study provides a definitive answer."

The basic Granger method was introduced in 1969, but the authors "cleverly applied it for the first time to atmosphere and ocean data," said Juergen Kurths, Head of Complexity Science Department at Potsdam Institute for Climate Impact Research in Germany, who was not a co-author. Kurths is a prominent physicist who has developed many novel mathematical methods for studying climate and other nonlinear systems.

"The most novel finding of this research is that the method of Granger causality found the ocean to influence the atmosphere almost everywhere in the extratropics," said Samantha Wills, a postdoctoral researcher at NOAA's Pacific Marine Environmental Laboratory, who was not a co-author. "This can be a challenging task given that the atmosphere dominates air-sea interaction in the extratropics, and the influence of the ocean on the atmosphere is not much larger than internal variability."

"This had not been demonstrated by previous General Circulation Model experiments. Although there have been a few special cases where it has been shown that mid-latitude sea-surface temperatures have a significant impact on the atmosphere, this relationship was not known to be as ubiquitous as this paper has shown," said J. Shukla, University Professor at George Mason University, who was not a co-author. Shukla is a world renowned climate scientist who pioneered studies of predictability.

Moreover, the study's estimates of the spatial structure of predictability could help to further advance the science of coupled data assimilation, the nascent field that attempts to leverage the interactions between atmosphere and ocean to improve climate prediction.

"The ability to anticipate changes to the ocean or atmosphere based on information from the other system provides society with the opportunity to prepare for future impacts, such as to agriculture and fisheries," said Wills.

"This is a very important paper in the history of predictability research," said Shukla, "It will surely inspire further research by the predictability research community. In particular, this paper identifies geographical regions on the globe over which there exists potential predictability which can be harvested for improving operational predictions."

Australian scientists play important role in safeguarding the world's largest tuna fishery

Tyler O'Neal, Staff Editor APPLICATIONS

Understanding the impact of modern fishing techniques is critical to ensure the sustainability of the Western and Central Pacific Ocean (WCPO) tuna fishery, the largest tuna fishery in the world that accounts for 55% of the total tropical tuna catch and provides up to 98% of government revenue for some Pacific Island nations.

Multiple agreements have been signed by Pacific island countries and territories to maintain the sustainability of this important ocean resource. However, the advent of Fish Aggregating Devices (FADs) and their impact on fishing efficiency over the past 20 years has added a large unknown to the management required to maintain the sustainability of this key fishery into the future.

Researchers from The Pacific Community’s Oceanic Fisheries Program (SPC) and the ARC Centre of Excellence for Climate Extremes have recently published two papers that used a combination of records from captains and scientific observers, FAD tracking data, ocean models and cutting edge supercomputer simulation methods to reveal for the first time the trajectories and potential impact these FADs may have on fisheries and the island nations. Tuna school by Jet Kim Unsplash {module In-article}

“Around 30,000-65,000 FADs are released every year in this region but we have very little understanding of where they ended up, how they were being used, and the impact this has had on coastal areas and the overall catch of the fishery,” said Dr. Lauriane Escalle, a fisheries scientist at SPC.

“While we know FADs make fishing more efficient, allowing fishing vessels to use less fuel and reduce fishing effort, there are unanswered questions around potential overfishing, impacts on bycatch species, ghost fishing and reef damage caused by FADs washing up on coral reefs and islands.”

Aside from catch data and ocean models, modern FADs themselves played an important role in helping the researchers get their answers.

Traditional FADs work because ocean-going species, like tuna, tend to aggregate around floating objects like floating logs. Why they do this is still not fully understood but fishers have long known this fact and taken advantage by releasing bamboo rafts into the ocean – the world’s first FADs. Over time commercial fishers added old ropes and nets to slow the drift through the ocean.

Today, FADs are high-tech buoys with solar-powered devices that record the position, scan the ocean below to estimate the number of aggregated fish and transmit all this information to vessels via satellite. This modern technology opened the door to detailed observations of FAD life history while they drift across the Pacific.

Combining this real-world information with catch data and cutting-edge supercomputer simulations based on ocean models allowed the researchers to examine the dynamics of FAD connectivity and to test different hypotheses explaining the high number of FADs beaching incidents in some areas. This key information could significantly add to the management of the Western and Central Pacific Ocean tuna fishery and the exclusive economic zones within it.

The studies found that:

  • More than 2000 FADs wash up on beaches and coral reefs every year.
  • Up to 6000 FADs fished on in the WCPO had drifted in from another fishery in the Eastern Pacific Ocean, which has different management systems;
  • FADs spent more time in the exclusive economic zone of Tuvalu and the Solomon Islands than any other part of the fishery.
  • The highest number of FAD beaching events occurred in the Solomon Islands, Papua New Guinea, and Tuvalu. This was more the result of ocean currents than where the FADs were deployed, making the management of this issue more difficult.
  • Kiribati, located along the equator, experienced a high number of FADs drifting through its waters, alongside significant levels of beaching, as a result of where fishers deployed FADs.
  • Results from these studies will help effectively manage tuna resources, through measures on the number and location of FADs deployments; the use of biodegradable FADs; programs to recover lost FAD before reaching sensitive areas; and more research on FAD impact on tuna and bycatch populations.

“Access to this unique regional database of FAD tracking data by fishing companies and managers allowed us to not only validate ocean models but also to test different deployment hypotheses using millions of virtual FADs,” said Dr. Joe Scutt Phillips, another fisheries scientist at SPC.

“This method allows us to look back in time and make good estimates of the movement and impact of FADs from before tracking programs, as well as examine their potential impact on tuna behavior.”

“This collaboration between fishing companies, regional management organizations and researchers has resulted in an extraordinary amount of useful data that will go a long way towards helping Pacific island nations and the fisheries managers maintain the sustainability of this valuable $6 billion a year industry. It’s a great example of managers, industry, and researchers working together for the benefit of all.”