CU News
News from the University of Colorado in Boulder.
Arctic sea ice reaches lowest extent ever recorded, says CU-Boulder research team
Aug 27th
The blanket of sea ice floating on the Arctic Ocean melted to its lowest extent ever recorded since satellites began measuring it in 1979, according to the University of Colorado Boulder’s National Snow and Ice Data Center.
On Aug. 26, the Arctic sea ice extent fell to 1.58 million square miles, or 4.10 million square kilometers. The number is 27,000 square miles, or 70,000 square kilometers below the record low daily sea ice extent set Sept. 18, 2007. Since the summer Arctic sea ice minimum normally does not occur until the melt season ends in mid- to late September, the CU-Boulder research team expects the sea ice extent to continue to dwindle for the next two or three weeks, said Walt Meier, an NSID scientist.
“It’s a little surprising to see the 2012 Arctic sea ice extent in August dip below the record low 2007 sea ice extent in September,” he said. “It’s likely we are going to surpass the record decline by a fair amount this year by the time all is said and done.”
On Sept. 18, 2007, the September minimum extent of Arctic sea ice shattered all satellite records, reaching a five-day running average of 1.61 million square miles, or 4.17 million square kilometers. Compared to the long-term minimum average from 1979 to 2000, the 2007 minimum extent was lower by about a million square miles — an area about the same as Alaska and Texas combined, or 10 United Kingdoms.
While a large Arctic storm in early August appears to have helped to break up some of the 2012 sea ice and helped it to melt more quickly, the decline seen in in recent years is well outside the range of natural climate variability, said Meier. Most scientists believe the shrinking Arctic sea ice is tied to warming temperatures caused by an increase in human-produced greenhouse gases pumped into Earth’s atmosphere.
CU-Boulder researchers say the old, thick multi-year ice that used to dominate the Arctic region has been replaced by young, thin ice that has survived only one or two melt seasons — ice which now makes up about 80 percent of the ice cover. Since 1979, the September Arctic sea ice extent has declined by 12 percent per decade.
The record-breaking Arctic sea ice extent in 2012 moves the 2011 sea ice extent minimum from the second to the third lowest spot on record, behind 2007. Meier and his CU-Boulder colleagues say they believe the Arctic may be ice-free in the summers within the next several decades.
“The years from 2007 to 2012 are the six lowest years in terms of Arctic sea ice extent in the satellite record,” said Meier. “In the big picture, 2012 is just another year in the sequence of declining sea ice. We have been seeing a trend toward decreasing minimum Arctic sea ice extents for the past 34 years, and there’s no reason to believe this trend will change.”
The Arctic sea ice extent as measured by scientists is the total area of all Arctic regions where ice covers at least 15 percent of the ocean surface, said Meier.
Scientists say Arctic sea ice is important because it keeps the polar region cold and helps moderate global climate — some have dubbed it “Earth’s air conditioner.” While the bright surface of Arctic sea ice reflects up to 80 percent of the sunlight back to space, the increasing amounts of open ocean there — which absorb about 90 percent of the sunlight striking the Arctic — have created a positive feedback effect, causing the ocean to heat up and contribute to increased sea ice melt.
Earlier this year, a national research team led by CU embarked on a two-year effort to better understand the impacts of environmental factors associated with the continuing decline of sea ice in the Arctic Ocean. The $3 million, NASA-funded project led by Research Professor James Maslanik of aerospace engineering sciences includes tools ranging from unmanned aircraft and satellites to ocean buoys in order to understand the characteristics and changes in Arctic sea ice, including the Beaufort Sea and Canada Basin that are experiencing record warming and decreased sea ice extent.
NSIDC is part of CU-Boulder’s Cooperative Institute for Research in Environmental Sciences — a joint institute of CU-Boulder and the National Oceanic and Atmospheric Administration headquartered on the CU campus — and is funded primarily by NASA. NSIDC’s sea ice data come from the Special Sensor Microwave Imager/Sounder sensor on the Defense Meteorological Satellite Program F17 satellite using methods developed at NASA’s Goddard Space Flight Center in Greenbelt, Md.
For more information and graphics visit CU-Boulder’s NSIDC website at http://nsidc.org/arcticseaicenews/2011/091511.html. For more information on CIRES visithttp://cires.colorado.edu/.
Wrap your mind around this! photo origami CU Boulder
Aug 27th
CU-Boulder ‘photo origami’ proposal
wins $2 million NSF grant
wins $2 million NSF grant
The art of origami has inspired children and artists all over the world because of the amazing objects that can be created by folding a simple piece of paper.
Now an engineering research team at the University of Colorado Boulder has won a $2 million grant from the National Science Foundation to develop a light-controlled approach for “self-assembly” mechanisms in advanced devices based on the same principles.
Known as “photo origami,” the idea is supported by NSF’s Emerging Frontiers in Research and Innovation program, which supports interdisciplinary teams working on rapidly advancing frontiers of fundamental engineering research.
CU-Boulder associate professor of mechanical engineering Jerry Qi will lead the team developing the photo origami technique. Collaborators will include CU faculty Robert McLeod of electrical engineering, Kurt Maute of aerospace engineering sciences and Elisabeth “Beth” Stade of mathematics, along with Patrick Mather of Syracuse University.
The ability to transform a flat polymer sheet into a sophisticated, mechanically robust 3-D structure will enable new approaches to manufacturing and design of devices from the microscopic to centimeter scales, according to the team. Examples include using extremely low-weight, high-strength materials to create micro-electromechanical systems with complicated 3-D architectures that can be used for microscopic sensors such as antennas or microphones, and miniature robotic devices for environmental monitoring.
Present barriers to the development of folding and unfolding mechanisms stem from the lack of understanding of scaling laws that allow researchers to generalize results obtained at various size scales, the inability to easily cause matter to “reorient” itself to achieve the desired folding patterns, and challenges in automated, sequential folding.
To overcome these challenges, the CU team will make use of recent fundamental advances in the control of polymer architecture through light-triggered chemical reactions.
“One has to accurately control how much deformation a material should have in order to obtain a precise folding angle and to determine where to fold or stop folding in order to avoid interference in the folding path and form the desired structure,” said McLeod, who will use the interaction of light with material deformation to develop optical waveguide transistors.
In this new form of logic circuit, light triggers the deformation of a soft polymer, which in turn switches the light on or off. In this way, the optical waveguide transistor will enable a structure to be pre-programmed with a folding pattern through a sequential set of switching events controlled by the shape of an origami sheet.
In recent years, CU researchers and their collaborators have made significant progress in using light to control and alter the structure of a polymer. They are able to both bend and stiffen polymer structures and to develop new, soft, shape-memory composite materials through photo-initiation techniques. Shape-memory composites are “smart” materials that have the ability to return from a temporary, deformed shape to their original shape when induced by a trigger.
In addition, the team will work with the local school district to provide research and educational opportunities for K-12 students and teachers.
CU study: Romney to win presidency
Aug 22nd
Analysis of election factors points to
Romney win, University of Colorado study says
A University of Colorado analysis of state-by-state factors leading to the Electoral College selection of every U.S. president since 1980 forecasts that the 2012 winner will be Mitt Romney.
The key is the economy, say political science professors Kenneth Bickers of CU-Boulder and Michael Berry of CU Denver. Their prediction model stresses economic data from the 50 states and the District of Columbia, including both state and national unemployment figures as well as changes in real per capita income, among other factors.
“Based on our forecasting model, it becomes clear that the president is in electoral trouble,” said Bickers, also director of the CU in DC Internship Program.
According to their analysis, President Barack Obama will win 218 votes in the Electoral College, short of the 270 he needs. And though they chiefly focus on the Electoral College, the political scientists predict Romney will win 52.9 percent of the popular vote to Obama’s 47.1 percent, when considering only the two major political parties.
“For the last eight presidential elections, this model has correctly predicted the winner,” said Berry. “The economy has seen some improvement since President Obama took office. What remains to be seen is whether voters will consider the economy in relative or absolute terms. If it’s the former, the president may receive credit for the economy’s trajectory and win a second term. In the latter case, Romney should pick up a number of states Obama won in 2008.”
Their model correctly predicted all elections since 1980, including two years when independent candidates ran strongly, 1980 and 1992. It also correctly predicted the outcome in 2000, when Al Gore received the most popular vote but George W. Bush won the election.
The study will be published this month in PS: Political Science & Politics, a peer-reviewed journal of the American Political Science Association. It will be among about a dozen election prediction models, but one of only two to focus on the Electoral College.
While many forecast models are based on the popular vote, the Electoral College model developed by Bickers and Berry is the only one of its type to include more than one state-level measure of economic conditions.
In addition to state and national unemployment rates, the authors looked at per capita income, which indicates the extent to which people have more or less disposable income. Research shows that these two factors affect the major parties differently: Voters hold Democrats more responsible for unemployment rates while Republicans are held more responsible for per capita income.
Accordingly — and depending largely on which party is in the White House at the time — each factor can either help or hurt the major parties disproportionately.
Their results show that “the apparent advantage of being a Democratic candidate and holding the White House disappears when the national unemployment rate hits 5.6 percent,” Berry said. The results indicate, according to Bickers, “that the incumbency advantage enjoyed by President Obama, though statistically significant, is not great enough to offset high rates of unemployment currently experienced in many of the states.”
In an examination of other factors, the authors found that none of the following had any statistically significant effect on whether a state ultimately went for a particular candidate: The location of a party’s national convention; the home state of the vice president; or the partisanship of state governors.
In 2012, “What is striking about our state-level economic indicator forecast is the expectation that Obama will lose almost all of the states currently considered as swing states, including North Carolina, Virginia, New Hampshire, Colorado, Wisconsin, Minnesota, Pennsylvania, Ohio and Florida,” Bickers said.
In Colorado, which went for Obama in 2008, the model predicts that Romney will receive 51.9 percent of the vote to Obama’s 48.1 percent, again with only the two major parties considered.
The authors also provided caveats. Factors they said may affect their prediction include the timeframe of the economic data used in the study and close tallies in certain states. The current data was taken five months in advance of the Nov. 6 election and they plan to update it with more current economic data in September. A second factor is that states very close to a 50-50 split may fall an unexpected direction.
“As scholars and pundits well know, each election has unique elements that could lead one or more states to behave in ways in a particular election that the model is unable to correctly predict,” Berry said.
Election prediction models “suggest that presidential elections are about big things and the stewardship of the national economy,” Bickers said. “It’s not about gaffes, political commercials or day-to-day campaign tactics. I find that heartening for our democracy.”
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