News Release

AGU journal highlights -- March 11, 2014

Peer-Reviewed Publication

American Geophysical Union

The following highlights summarize research papers that have been recently published in Geophysical Research Letters (GRL), Journal of Geophysical Research-Atmospheres (JGR-D), and Journal of Geophysical Research-Earth Surface (JGR-F).

In this release:

  1. Cassini sheds light on Titan's second largest lake, Ligeia Mare
  2. Tectonic stress feedback loop explains U-shaped glacial valleys
  3. Measuring the effect of water vapor on climate warming
  4. First assessment of noctilucent cloud variability at midlatitudes
  5. Modeling surface circulation patterns in the Gulf of Mexico
  6. New algorithm to improve earthquake early warning systems

Anyone may read the scientific abstract for any already-published paper by clicking on the link provided at the end of each Highlight. You can also read the abstract by going to and inserting into the search engine the full doi (digital object identifier), e.g. doi: 10.1002/2013GL058877. The doi is found at the end of each Highlight below.

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1. Cassini sheds light on Titan's second largest lake, Ligeia Mare

Saturn's second largest moon, Titan, is known for its dense, planet-like atmosphere and large lakes most likely made of methane and ethane. It has been suggested that Titan's atmosphere and surface is a model of early Earth. Since the early 2000s, NASA's Cassini space probe has been unlocking secrets of the distant moon.

The most recent Cassini flyby of Titan on 23 May 2013 reveals new observations of Ligeia Mare, Titan's second largest lake, and offers insight into weather patterns and the chemical makeup of the surrounding terrain. Zebker et al. used radar data to determine that the surface of the lake is flat, ruling out the presence of waves or wind in the region. Other measurements, consistent with previous observations, suggest that Ligeia Mare is most likely composed of liquid methane.

They also find that the surrounding solid terrain is most likely made of solid organic material and not water ice. The authors suggest that these findings not only help scientists to better understand Titan's surface dynamics, but also reveal best practices for how to infer features from remotely sensed data.

Source: Geophysical Research Letters, doi: 10.1002/2013GL058877, 2013

Title: Surface of Ligeia Mare, Titan, from Cassini altimeter and radiometer analysis

Authors: Howard Zebker: Departments of Geophysics and Electrical Engineering, Stanford University, Stanford, California, USA;

Alex Hayes: Department of Astronomy, Cornell University, Ithaca, New York, USA;

Mike Janssen: Jet Propulsion Laboratory, Pasadena, California, USA;

Alice Le Gall: LATMOS, Institute Pierre Simon Laplace, Guyancourt, France;

Ralph Lorenz: Applied Physics Laboratory, Johns Hopkins University, Laurel, Maryland, USA;

Lauren Wye: SRI International, Menlo Park, California, USA.

2. Tectonic stress feedback loop explains U-shaped glacial valleys

In the shadow of the Matterhorn, the broad form of the Matter Valley—like so many throughout the Alps—is interrupted by a deep U-shaped glacial trough. Carved into a landscape reflecting millennia of tectonic uplift and river erosion, growing evidence suggests the 100-meter-deep (328-foot-deep) U-shaped groove was produced shortly after a shift toward major cycles of Alpine glaciation almost a million years ago. Subsequent glaciations may have therefore had little effect on the landscape.

The Matter Valley and other Alpine valleys' U-shaped incisions were carved by glaciers, but the power of ice alone is not enough to explain the location or apparent timing of the troughs' formation. If glacial forces were the sole driver, the valleys would be three times as wide, and would grow consistently deeper during each period of glaciation.

In previous research, Leith et al. proposed a new mechanism to explain characteristic fracturing in bedrock beneath glaciers, and in the present study, they find that this may have driven a one-off period of amplified glacial erosion in the Matter Valley. In the authors' model, bedrock stresses left over from mountain formation are focused beneath the surface at the center of V-shaped valleys. Early periods of glacial erosion carved through the upper bedrock layers, exposing the stressed rock. Thinning glaciers allowed the stressed bedrock to fracture, and broken rock was easily carried away by flowing ice. As the valleys deepened, stresses were further focused at the valley floor, creating more fractured bedrock and making it easier for the glaciers to dig in. Their model suggests that bedrock stresses were relieved once the valley glacier retreated, and that subsequent periods of glaciation may not have encountered similar conditions.

The authors' model shows how glacial erosion promotes the formation of U-shaped valleys of a particular size and with a particular frequency, results which align with their observations in the Matter Valley.

Source: Journal of Geophysical Research-Earth Surface, doi: 10.1002/2012JF002691, 2013

Title: Subglacial extensional fracture development and implications for Alpine valley evolution

Authors: Kerry Leith: Geological Institute, Swiss Federal Institute of Technology, ETH Zurich, Zurich, Switzerland; and Chair of Landslide Research, Technical University of Munich, Munich, Germany;

Jeffrey R. Moore: Geological Institute, Swiss Federal Institute of Technology, ETH Zurich, Zurich, Switzerland; and Geology & Geophysics, University of Utah, Salt Lake City, Utah, USA;

Florian Amann and Simon Loew: Geological Institute, Swiss Federal Institute of Technology, ETH Zurich, Zurich, Switzerland.

3. Measuring the effect of water vapor on climate warming

Water vapor is a potent greenhouse gas. In the atmosphere, the concentration of water vapor increases with the temperature, setting up a powerful positive feedback loop. This water vapor feedback is the strongest known positive feedback, with the potential to roughly double the effect of warming caused by other sources. Determining the exact strength of the water vapor feedback, then, is incredibly important to limiting uncertainty in future climate change projections.

From 2002 to 2009, an infrared sounder aboard NASA's Aqua satellite measured the atmospheric concentration of water vapor. Combined with a radiative transfer model, Gordon et al. used these observations to determine the strength of the water vapor feedback. According to their calculations, atmospheric water vapor amplifies warming by 2.2 plus or minus 0.4 watts per square meter per degree Celsius. This value, however, is only the "short-term" feedback—the strength of the feedback as measured during the observational period. This value is subject to short-term climate variability. The true value of the feedback, the "long-term" value, is what the short-term observed values should trend towards when given enough time.

Using a series of climate models, the authors estimate the strength of the long-term water vapor feedback. Extrapolating from their short-term observations they calculate a long-term feedback strength of 1.9 to 2.8 watts per square meter per degree Celsius. They find that most models get to within 15 percent of their long-term value within 25 years. The accuracy of calculations, then, could be improved with a longer set of observations.

Source: Journal of Geophysical Research-Atmospheres, doi: 10.1002/2013JD020184, 2013

Title: An observationally based constraint on the water-vapor feedback

Authors: N. D. Gordon: Lawrence Livermore National Laboratory, Livermore, California, USA;

A. K. Jonko: National Center for Atmospheric Research, Boulder, Colorado, USA;

P. M. Forster: School of Earth and Environment, University of Leeds, Leeds, UK:

K. M. Shell: College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, Oregon, USA.

4. First assessment of noctilucent cloud variability at midlatitudes

As the Sun dips below the horizon, the last rays of light can glint off crystals of ice high in the atmosphere, lighting up the sky with an electric blue glow. Known as noctilucent clouds, these collections of ice crystals occur most often at high latitudes, but the long polar days make them difficult to see. With the eye, noctilucent clouds can best be seen at night between 50 degrees and 60 degrees latitude in both hemispheres.

Investigations with other techniques, such as lidar, however, have made noctilucent clouds easier to detect during the day as well as at night. Though they show up less than 10 percent of the time at midlatitudes, noctilucent clouds are an important component of the summer atmosphere. Their properties and occurrence may indicate patterns of behavior in the middle atmosphere.

Gerding et al. are the first to have measured the daily variation of noctilucent cloud behavior at midlatitudes from the ground. From a research site in Kühlungsborn, Germany, a town located near 54 degrees north, the authors used a suite of equipment, including lidar, to study how noctilucent clouds evolve throughout the day. From 1,800 hours of summertime observations, the authors find 100 hours that contained noctilucent clouds and observe within them recurrent daily patterns in brightness and activity. The data show that noctilucent cloud activity rises and falls with local solar time, being highest at 5 a.m. and lowest at 7 p.m., with a secondary maximum at 2 p.m. Cloud brightness peaks twice, once at 4 a.m. and once at 6 p.m.

The authors find that noctilucent cloud activity is not related to tidal temperature variation at noctilucent cloud altitudes. Rather, they find that noctilucent cloud activity for their location is highest after a bout of southward polar wind and lowest during weak or northward winds.

Source: Geophysical Research Letters, doi: 10.1002/2013GL057955, 2013

Title: Diurnal variations of midlatitude NLC parameters observed by daylight-capable lidar and their relation to ambient parameters

Authors: M. Gerding, M. Kopp, P. Hoffmann, J. Höffner, and F.-J. Lübken: Leibniz-Institute of Atmospheric Physics, the Rostock University, Kühlungsborn, Germany.

5. Modeling surface circulation patterns in the Gulf of Mexico

During the 2010 Deepwater Horizon oil spill, scientists' understanding of the mesoscale surface circulation patterns of the Gulf of Mexico became a topic of great importance. With the oil slick growing, disaster response teams needed to know where to deploy. Many were concerned with the oil's ultimate destination—whether it would travel towards the Florida Keys and into the Atlantic Ocean, or remain in the Gulf. The drivers of surface circulation patterns are varied, ranging from wind to internal waves to pressure and salinity gradients, and the task of forecasting the oil's motion was a challenge.

In the wake of the oil spill, researchers devised a plan to deploy 300 drifters in the Gulf of Mexico, a project intended to greatly improve their understanding of surface circulation in the Gulf. Known as the Grand Lagrangian Deployment (GLAD), the project was implemented in July 2012 when the fleet of drifters was dropped in the ocean and tracked as they moved along surface currents for the next six months.

Using observations of the drifters' motion, Olascoaga et al. tested the skill of a Lagrangian model in representing surface circulation in the Gulf. The authors' model used satellite observations of the geostrophic velocity (the balance of the pressure gradient and the Coriolis current) to calculate surface circulation patterns. The authors were concerned with modeling the behavior of "Lagrangian coherent structures"—hidden lines in the surface ocean that guide fluid parcel dynamics.

The authors find not only that the simulations made by the Lagrangian model aligned with the surface circulations revealed by the GLAD drifters, but also that the model's identification of Lagrangian coherent structures could actually be used to forecast surface circulation patterns that had yet to develop.

Source: Geophysical Research Letters, doi: 10.1002/2013GL058624, 2013

Title: Drifter motion in the Gulf of Mexico constrained by altimetric Lagrangian coherent structures

Authors: M. J. Olascoaga, F. J. Beron-Vera, M. Iskandarani, B. K. Haus, T. M. Özgökmen and A. J. H. M. Reniers: Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA;

G. Haller: Institute of Mechanical Systems, ETH Zurich, Zurich, Switzerland;

J. Triñanes: Instituto de Investigaciónes Tecnolóxicas, Universidade de Santiago de Compostela, Santiago, Spain;

E. F. Coelho: Physics Department, University of New Orleans, New Orleans, Louisiana, USA;

H. S. Huntley, A. D. Kirwan Jr., and B. L. Lipphardt Jr.: School of Marine Science and Policy, University of Delaware, Newark, Delaware, USA;

G. Jacobs: Naval Research Laboratory, Stennis Space Center, Mississippi, USA;

A. Valle-Levinson: Department of Civil and Coastal Engineering, University of South Florida, Gainesville, Florida, USA.

6. New algorithm to improve earthquake early warning systems

When a fault line ruptures, seismic waves race out from the earthquake epicenter. Compressional seismic waves, known as primary or P waves travel fastest. Shear waves—secondary or S waves—travel more slowly, but are the source of the bulk of earthquake-induced damage. Using the opportunity afforded by the difference in travel times between these two types of waves, researchers have begun to design and implement earthquake early warning systems.

To calculate the properties of an earthquake that is just seconds old, these early warning systems analyze the first few seconds of P waves arriving at seismic monitoring stations. Pulling observations from multiple monitoring stations enables the calculation of the earthquake's location, and analyzing the P waves' properties gives a way to estimate the earthquake's magnitude. Exactly which properties of a P wave to measure to best derive a magnitude estimate, however, is a matter of ongoing research.

For the California Integrated Seismic Network's warning system, magnitude estimation is done three different ways, using three different algorithms and three sets of input variables. These approaches each use measures of the P wave's amplitude and frequency. In a new study, however, Kuyuk and Allen find that in this case less is more: a new algorithm that relies solely on the P wave's vertical amplitude can estimate earthquake magnitude with strong statistical reliability, outperforming the other techniques.

Source: Geophysical Research Letters, doi: 10.1002/2013GL058580, 2013

Title: A global approach to provide magnitude estimates for earthquake early warning alerts

Authors: Huseyin Serdar Kuyuk and Richard M. Allen: Seismological Laboratory, University of California, Berkeley, California, USA.


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