Tyler O'Neal, Staff Editor

Japanese researchers uncover a key clue as to whether hurricanes will decay or re-intensify after hitting land

  • Hurricanes that make landfall typically decay but sometimes transition into extratropical cyclones and re-intensify, causing widespread damage to inland communities
  • The presence of a cold-core is currently used to identify this transition, but a new study has now found that a cold-core naturally forms in all landfalling hurricanes
  • The cold-core was detected when scientists ran simulations of landfalling hurricanes that accounted for moisture stored within the cyclone
  • Over time, the scientists saw a cold-core growing from the bottom of the hurricane, replacing the warm core
  • The research could help forecasters make more accurate predictions on whether communities farther inland will be impacted by these extreme weather events

Hurricanes are powerful weather events born in the open sea. Fueled by moisture from the warm ocean, hurricanes can intensify in strength, move vast distances across the water, and ultimately unleash their destruction upon the land. But what happens to hurricanes after they've made landfall remains an open question. Air in a Northern Hemisphere hurricane circulates counterclockwise at tremendous speeds. As it spins, air also moves inwards, rises upwards and then moves outwards. The rising moist air condenses, which releases heat and forms a warm core inside the hurricane. Professor Pinaki Chakraborty and Dr. Lin Li studied the thermodynamics of hurricanes as part of a study in Physical Review Fluids.

Now, a recent study in Physical Review Fluids has used simulations to explore the fate of landfalling hurricanes. The scientists found that after landfall, the warm, dynamic heart of a hurricane is replaced by a growing cold-core - an unexpected finding that could help forecasters predict the level of extreme weather that communities farther inland may face.

"Generally, if a hurricane hits land, it weakens and dies," said Professor Pinaki Chakraborty, senior author and head of the Fluid Mechanics Unit at the Okinawa Institute of Science and Technology Graduate University (OIST). "But sometimes, a hurricane can intensify again deep inland, creating a lot of destruction, like flooding, in communities far away from the coast. So, predicting the course that a hurricane will take is crucial."

These re-intensification events occur when hurricanes, also known as tropical cyclones or typhoons in other global regions, transition into extratropical cyclones: storms that occur outside the Earth's tropics. Unlike tropical cyclones that harness their strength from ocean moisture, extratropical cyclones gain their energy due to unstable conditions in the surrounding atmosphere. This instability comes in the form of weather fronts - boundaries that separate warmer, lighter air from colder, denser air.

"Weather fronts are always unstable, but the release of energy is typically very slow. When a hurricane comes, it can disturb the front and trigger a faster release of energy that allows the storm to intensify again," said first author Dr. Lin Li, a former Ph.D. student in Prof. Chakraborty's unit. Once a hurricane moves over land, it loses its moisture supply so the air contains less moisture. Air must rise further before it reaches a temperature where it can no longer hold the level of water vapor. The vapor therefore condenses and releases heat as a higher point, shrinking the warm core to the upper half of the hurricane, while the rising air forms a cold core at the bottom. Professor Pinaki Chakraborty and Dr. Lin Li studied the thermodynamics of landfalling hurricanes as part of a study in Physical Review Fluids.

However, predicting if this transition will occur is challenging for weather forecasters as hurricanes must interact with this front in a specific and complex way. Currently, forecasters use one key characteristic to objectively identify this transition: the presence of a cold-core within a landfalling hurricane, caused by an inward rush of cold air from the weather front.

However, when Prof. Chakraborty and Dr. Li simulated what happens to hurricanes after hitting land, they found that a cold-core was present in all landfalling hurricanes, growing upwards from the bottom of the hurricanes as they decayed, despite a stable atmosphere with no weather fronts.

"This appears to be a natural consequence of when a hurricane makes landfall and starts to decay," said Dr. Li.

Previous theoretical models of landfalling hurricanes missed the growing cold-core as they didn't account for the moisture stored within landfalling hurricanes, explained the researchers.

Prof. Chakraborty said, "Once hurricanes move over land and lose their moisture supply, models typically viewed them as just a spinning, dry vortex of air, which like swirling tea in a cup, rubs over the surface of the land and slows down due to friction."

However, the store of moisture within landfalling hurricanes means that thermodynamics still plays a critical role in how they decay.

In hurricanes over a warm ocean, the air that enters the hurricane is heavily saturated with moisture. As this air rises upward, it expands and cools, which lowers the amount of water vapor each "parcel" of air can hold. The water vapor within each air parcel therefore condenses, releasing heat. This means that these air parcels cool slower than the surrounding air outside the hurricane, generating a warm core.

But once a hurricane hits land, the air entering the hurricane contains less moisture. As these air parcels rise, they must travel higher before they reach a temperature cool enough for the water vapor to condense, delaying the release of heat. This means that at the bottom of the hurricane, where all the air parcels are moving upwards, it is comparatively cooler than the surrounding atmosphere, where air parcels move randomly in all directions, resulting in a cold-core.

"As the hurricane keeps decaying, it eats up more and more of the moisture stored within the hurricane, so the air parcels must rise even higher before condensation occurs," said Dr. Li. "So over time, the cold-core grows and the warm core shrinks."

The researchers hope that a better understanding of cold cores could help forecasters more accurately distinguish between decaying hurricanes and ones transitioning into extratropical cyclones.

"It's no longer as simple as hurricanes having a warm core and extratropical cyclones having a cold core," said Prof. Chakraborty. "But in decaying hurricanes, the cold-core we see is restricted to the lower half of the cyclone, whereas in an extratropical cyclone, the cold-core spans the whole hurricane - that's the signature that forecasters need to look for."

German researchers discover the largest rotation in the universe

Tyler O'Neal, Staff Editor

By mapping the motion of galaxies in huge filaments that connect the cosmic web, astronomers at the Leibniz Institute for Astrophysics Potsdam (AIP) Germany have found that these long tendrils of galaxies spin on the scale of hundreds of millions of light-years. A rotation on such enormous scales has never been seen before. The results from supercomputing the astronomy data signify that angular momentum can be generated on unprecedented scales. Artist’s impression of cosmic filaments: huge bridges of galaxies and dark matter connect clusters of galaxies to each other. Galaxies are funnelled on corkscrew like orbits towards and into large clusters that sit at their ends. Their light appears blue-shifted when they move towards us, and red-shifted when they move away. Credit: AIP/ A. Khalatyan/ J. Fohlmeister

Cosmic filaments are huge bridges of galaxies and dark matter that connect clusters of galaxies to each other. They funnel galaxies towards and into large clusters that sit at their ends. “By mapping the motion of galaxies in these huge cosmic superhighways using the Sloan Digital Sky survey – a survey of hundreds of thousands of galaxies – we found a remarkable property of these filaments: they spin,” says Peng Wang, first author of the now published study and astronomer at the AIP. “Despite being thin cylinders – similar in dimension to pencils – hundreds of millions of light-years long, but just a few million light-years in diameter, these fantastic tendrils of matter rotate,” adds Noam Libeskind, initiator of the project at the AIP. “On these scales, the galaxies within them are themselves just specs of dust. They move on helixes or corkscrew-like orbits, circling around the middle of the filament while traveling along with it. Such a spin has never been seen before on such enormous scales, and the implication is that there must be an as yet unknown physical mechanism responsible for torquing these objects.”

How the angular momentum responsible for the rotation is generated in a cosmological context is one of the key unsolved problems of cosmology. In the standard model of structure formation, small overdensities present in the early universe grow via gravitational instability as matter flows from under to overdense regions. Such a potential flow is irrotational or curl-free: there is no primordial rotation in the early universe. As such any rotation must be generated as structures form. The cosmic web in general and filaments, in particular, are intimately connected with galaxy formation and evolution. They also have a strong effect on galaxy spin, often regulating the direction of how galaxies and their dark matter halos rotate. However, it is not known whether the current understanding of structure formation predicts that filaments themselves, being uncollapsed quasi-linear objects, should spin.

“Motivated by the suggestion from the theorist Dr. Mark Neyrinck that filaments may spin, we examined the observed galaxy distribution, looking for filament rotation,” says Noam Libeskind. “It's fantastic to see this confirmation that intergalactic filaments rotate in the real Universe, as well as in computer simulation.” By using a sophisticated mapping method, the observed galaxy distribution was segmented into filaments. Each filament was approximated by a cylinder. Galaxies within it were divided into two regions on either side of the filament spine (in projection) and the mean redshift difference between the two regions was carefully measured. The mean redshift difference is a proxy for the velocity difference (the Doppler shift) between galaxies on the receding and approaching side of the filament tube. It can thus measure the filament’s rotation. The study implies that depending on the viewing angle and endpoint mass, filaments in the universe show a clear signal consistent with rotation.

Deep learning with SPECT accurately predicts major adverse cardiac events

Tyler O'Neal, Staff Editor

An advanced artificial intelligence technique known as deep learning can predict major adverse cardiac events more accurately than current standard imaging protocols, according to research presented at the Society of Nuclear Medicine and Molecular Imaging 2021 Annual Meeting. Utilizing data from a registry of more than 20,000 patients, researchers developed a novel deep learning network that has the potential to provide patients with an individualized prediction of their annualized risk for adverse events such as heart attack or death.

Deep learning is a subset of artificial intelligence that mimics the workings of the human brain to process data. Deep learning algorithms use multiple layers of "neurons," or non-linear processing units, to learn representations and identify latent features relevant to a specific task, making sense of multiple types of data. It can be used for tasks such as predicting cardiovascular disease and segmenting lungs, among others.

The study utilized information from the largest available multicenter SPECT dataset, the "REgistry of Fast myocardial perfusion Imaging with NExt generation SPECT" (REFINE SPECT), with 20,401 patients. All patients in the registry underwent SPECT MPI, and a deep learning network was used to score them on how likely they were to experience a major adverse cardiac event during the follow-up period. Subjects were followed for an average of 4.7 years. Prediction performance

The deep learning network highlighted regions of the heart that were associated with the risk of major adverse cardiac events and provided a risk score in less than one second during testing. Patients with the highest deep learning scores had an annual major adverse cardiac event rate of 9.7 percent, a 10.2-fold increased risk compared to patients with the lowest scores.

"These findings show that artificial intelligence could be incorporated in standard clinical workstations to assist physicians in accurate and fast risk assessment of patients undergoing SPECT MPI scans," said Ananya Singh, MS, a research software engineer in the Slomka Lab at Cedars-Sinai Medical Center in Los Angeles, California. "This work signifies the potential advantage of incorporating artificial intelligence techniques in standard imaging protocols to assist readers with risk stratification."

Abstract 50. "Improved risk assessment of myocardial SPECT using deep learning: report from REFINE SPECT registry," Ananya Singh, Yuka Otaki, Paul Kavanagh, Serge Van Kriekinge, Wei Chih-Chun, Tejas Parekh, Joanna Liang, Damini Dey, Daniel Berman and Piotr Slomka, Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California; Robert Miller, Department of Cardiac Sciences, University of Calgary, Calgary, Alberta, Canada, and Department of Imaging, Cedars-Sinai Medical Center, Los Angeles, California; Tali Sharir, Department of Nuclear Cardiology, Assuta Medical Centers, Tel Aviv, and Ben Gurion University of the Negev, Beer Sheba, Israel; Andrew Einstein, Division of Cardiology, Department of Medicine and Department of Radiology, Columbia University, Irving Medical Center and New York-Presbyterian Hospital, New York, New York; Mathews Fish, Oregon Heart and Vascular Institute, Sacred Heart Medical Center, Springfield, Oregon; Terrence Ruddy, Division of Cardiology, University of Ottawa Heart Institute, Ottawa, Ontario, Canada; Philipp Kaufmann, Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, Zurich, Switzerland; Albert Sinusas and Edward Miller, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine New Haven, Connecticut; Timothy Bateman, Department of Imaging, Cardiovascular Imaging Technologies LLC, Kansas City, Missouri; Sharmila Dorbala and Marcelo Di Carli, Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Brigham and Women's Hospital, Boston, Massachusetts.