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News Article | December 1, 2016
Site: www.eurekalert.org

New York, NY--December 1, 2016--Tornadoes and severe thunderstorms kill people and damage property every year. Estimated U.S. insured losses due to severe thunderstorms in the first half of 2016 were $8.5 billion. The largest U.S. impacts of tornadoes result from tornado outbreaks, sequences of tornadoes that occur in close succession. Last spring a research team led by Michael Tippett, associate professor of applied physics and applied mathematics at Columbia Engineering, published a study showing that the average number of tornadoes during outbreaks--large-scale weather events that can last one to three days and span huge regions--has risen since 1954. But they were not sure why. In a new paper, published December 1 in Science via First Release, the researchers looked at increasing trends in the severity of tornado outbreaks where they measured severity by the number of tornadoes per outbreak. They found that these trends are increasing fastest for the most extreme outbreaks. While they saw changes in meteorological quantities that are consistent with these upward trends, the meteorological trends were not the ones expected under climate change. "This study raises new questions about what climate change will do to severe thunderstorms and what is responsible for recent trends," says Tippett, who is also a member of the Data Science Institute and the Columbia Initiative on Extreme Weather and Climate. "The fact that we don't see the presently understood meteorological signature of global warming in changing outbreak statistics leaves two possibilities: either the recent increases are not due to a warming climate, or a warming climate has implications for tornado activity that we don't understand. This is an unexpected finding." The researchers used two NOAA datasets, one containing tornado reports and the other observation-based estimates of meteorological quantities associated with tornado outbreaks. "Other researchers have focused on tornado reports without considering the meteorological environments," notes Chiara Lepore, associate research scientist at the Lamont-Doherty Earth Observatory, who is a coauthor of the paper. "The meteorological data provide an independent check on the tornado reports and let us check for what would be expected under climate change." U.S. tornado activity in recent decades has been drawing the attention of scientists. While no significant trends have been found in either the annual number of reliably reported tornadoes or of outbreaks, recent studies indicate increased variability in large normalized economic and insured losses from U.S. thunderstorms, increases in the annual number of days on which many tornadoes occur, and increases in the annual mean and variance of the number of tornadoes per outbreak. In the current study, the researchers used extreme value analysis and found that the frequency of U.S. outbreaks with many tornadoes is increasing, and is increasing faster for more extreme outbreaks. They modeled this behavior using extreme value distributions with parameters that vary to match the trends in the data. Extreme meteorological environments associated with severe thunderstorms showed consistent upward trends, but the trends did not resemble those currently expected to result from global warming. They looked at two factors: convective available potential energy (CAPE) and a measure of vertical wind shear, storm relative helicity. Modeling studies have projected that CAPE will increase in a warmer climate leading to more frequent environments favorable to severe thunderstorms in the U.S. However, they found that the meteorological trends were not due to increasing CAPE but instead due to trends in storm relative helicity, which has not been projected to increase under climate change. "Tornadoes blow people away, and their houses and cars and a lot else," says Joel Cohen, coauthor of the paper and director of the Laboratory of Populations, which is based jointly at Rockefeller University and Columbia's Earth Institute. "We've used new statistical tools that haven't been used before to put tornadoes under the microscope. The findings are surprising. We found that, over the last half century or so, the more extreme the tornado outbreaks, the faster the numbers of such extreme outbreaks have been increasing. What's pushing this rise in extreme outbreaks is far from obvious in the present state of climate science. Viewing the thousands of tornadoes that have been reliably recorded in the U.S. over the past half century or so as a population has permitted us to ask new questions and discover new, important changes in outbreaks of these tornadoes." Adds Harold Brooks, senior scientist at NOAA's National Severe Storms Laboratory, who was not involved with this project, "The study is important because it addresses one of the hypotheses that has been raised to explain the observed change in number of tornadoes in outbreaks. Changes in CAPE can't explain the change. It seems that changes in shear are more important, but we don't yet understand why those have happened and if they're related to global warming." Better understanding of how climate affects tornado activity can help to predict tornado activity in the short-term, a month, or even a year in advance, and would be a major aid to insurance and reinsurance companies in assessing the risks posed by outbreaks. "An assessment of changing tornado outbreak size is highly relevant to the insurance industry," notes Kelly Hererid, AVP, Senior Research Scientist, Chubb Tempest Re R&D. "Common insurance risk management tools like reinsurance and catastrophe bonds are often structured around storm outbreaks rather than individual tornadoes, so an increasing concentration of tornadoes into larger outbreaks provides a mechanism to change loss potential without necessarily altering the underlying tornado count. This approach provides an expanded view of disaster potential beyond simple changes in event frequency." Tippett notes that more studies are needed to attribute the observed changes to either global warming or another component of climate variability. The research group plans next to study other aspects of severe thunderstorms such as hail, which causes less intense damage but is important for business (especially insurance and reinsurance) because it affects larger areas and is responsible for substantial losses every year. The study was partially funded by Columbia University Research Initiatives for Science and Engineering (RISE) award; the Office of Naval Research; NOAA's Climate Program Office's Modeling, Analysis, Predictions and Projections; Willis Research Network; and the National Science Foundation.


News Article | December 5, 2016
Site: news.yahoo.com

Tornados are behaving strangely: The number of tornado outbreaks per year is fairly constant, but the number of tornados per outbreak has skyrocketed. And scientists aren't entirely sure why. In an effort to learn more, researchers looked at meteorological factors related to tornado outbreaks, and then dug into the data to see whether these factors had changed over time, said study lead researcher Michael Tippett, an associate professor of applied physics and applied mathematics at Columbia University. The analyses did yield a result, but an unexpected one, Tippett said. [The Top 5 Deadliest Tornado Years in US History] "The meteorological factors that are related with tornado outbreaks have also become more extreme," Tippett told Live Science in an email. "The surprising finding was that the change in meteorological factors did not have the expected signature of climate change." That's not to say that climate change isn't involved, he said, but it does leave two possibilities: "Either the recent increases are not due to a warming climate, or a warming climate has implications for tornado activity that we don't understand," Tippett said in a statement. Tippett said he became interested in tornadoes in the spring of 2011, when multiple deadly twister outbreaks struck the U.S. That includes the multivortex tornado that hit Joplin, Missouri, killing 158 people and injuring more than 1,000. "The public was asking what caused these record-breaking outbreaks, and scientists didn't have an answer," Tippett said. In the following years, Tippett and other scientists published studies on tornado clusters, a sequence of six or more tornadoes that happen within several days of one another. In the new study, Tippett and his colleagues found that the number oftwisters in the most extreme outbreaks has increased over the years, making these clusters more dangerous than in the past, he said. For instance, between 1965 and 2015, over five-year periods, the estimated number of tornadoes in the most extreme outbreaks (clusters with 12 or more tornados) roughly doubled, from 40 in 1965 to almost 80 in 2015, he said. To see whether this mysterious increase was connected to climate change, Tippett and his colleagues looked at two data sets from the National Oceanic and Atmospheric Administration (NOAA), one that included tornado reports and another with observation-based estimates of meteorological factors associated with tornado outbreaks, he said. They were particularly interested in a factor called "convective available potential energy" (CAPE), the amount of energy available for convection in which hot, less dense material rises, and cold, dense material sinks. CAPE is related to the vertical wind speed, meaning that higher CAPE values indicate that severe weather will be more extreme, according to WeatherOnline. As the climate warms, CAPE is expected to increase, past studies have suggested, the researchers wrote in the study. However, CAPE has stayed fairly steady. Instead, "we see trends in the winds," Tippett said. The wind metric he looked at, called storm relative helicity (SRH), is a measure of corkscrew-like upward winds, something that was not expected to increase with climate change, he said. [Tornado Chasers: See Spinning Storms Up-Close (Photos)] The finding is unexpected but important, said Harold Brooks, a senior scientist at NOAA's National Severe Storms Laboratory, who was not involved with the study. "The fact that they can explain the tornado changes by storm relative helicity changes is, in one aspect, not surprising (it's a much better predictor of whether a storm will make a tornado than CAPE is)," Brooks wrote in an email to Live Science. "But, in another aspect, [the results are] difficult to explain. We don't really have a good conceptual model for why high SRH values should increase as the planet warms." The study is "intriguing," but it has several limitations, said Victor Gensini an associate professor of meteorology at the College of DuPage in Illinois. For starters, the study includes tornados only from 1979 to the present, which is a "fairly short historical record," Gensini said in an email to Live Science. It's also possible that tornado reporting has gotten better over time, and that earlier records left out some tornadoes, he said. In addition, past studies have shown an increase in the variability of the U.S. tornado season, and climate models suggest that future severe weather will become more variable, Gensini said. But, in general, "there are better environmental metrics to examine tornado environments that the authors failed to use here," he said. "This is just one study, and people shouldn't hang their hat on one study." The study was published online Dec. 1 in the journal Science. In Images: Extreme Weather Around the World


News Article | December 2, 2016
Site: www.csmonitor.com

Climate models suggest that conditions for tornado outbreaks should be increasing with rising temperatures, but do the data agree? No more watching videos at work: Facebook will now default to audio This Monday, May 26, 2014 photo from video provided by Dan Yorgason shows a tornado in a worker's camp near Watford City, N.D. As global temperatures warm, climate scientists expect to see more tornadoes reaching their long, swirling bodies down to Earth. But the data isn't exactly cooperating in a straightforward manner. Scientists have reported that, over the last 50 years, the average number of tornadoes that touch down in the United States each year has not risen. But analysis of this data suggests that the most extreme outbreaks, when several twisters appear as part of a single weather event, are on the rise. Surely climate change is playing a role in the rise of those extreme events, a team of researchers at Columbia University expected. But when they analyzed the data they didn't find the signs they expected, they report in a paper published Thursday in the journal Science. No, that doesn't mean climate change isn't behind the rise of extreme tornado outbreaks across the country, study lead author Michael Tippett, a mathematician at Columbia University, tells The Christian Science Monitor in a phone interview. "We're just saying that it's not playing the role that we expected." There are two ingredients that make for conditions conducive to tornadoes, Dr. Tippett explains. One is the propensity of air to rise, called the convective available potential energy (CAPE), and the other is vertical wind shear. Warmer, moist air near the surface of the Earth particularly tends to rise, so climate projections predicted an increased CAPE with climate change and therefore more of one of the key ingredients for tornadoes. As such, Tippett and his colleagues expected to see an increased CAPE in the environments where extreme tornado outbreaks were occurring. But when they dug into the data, that wasn't the case. In fact, wind shear seems to have increased. "The lack of a change in CAPE that correlates with the change in tornadoes is a significant result," Harold Brooks, a researcher at the National Severe Storms Laboratory who was not involved in the research, writes in an email to the Monitor. "Increases in CAPE are, in the convective storms world, the thing we’re most confident in as the planet warms. It’s a fairly direct connection between surface warming and higher CAPE. The fact that they can explain the tornado changes by storm relative helicity (related to shear) changes is, in one aspect, not surprising (it’s a much better predictor of whether a storm will make a tornado than CAPE is), but, in another aspect, difficult to explain. We don’t really have a good conceptual model for why high SRH values should increase as the planet warms." Tippett agrees that his research poses more questions than it answers, particularly when it comes to the role global warming may be playing in tornado trends. "One possibility is that there are aspects of climate change that we don't understand yet," Tippett says. "The other possibility is it's not climate change." The data Tippett and his colleagues are working off might not be the full story, Charles Konrad, director of the Southeast Regional Climate Center who was not involved in the study, points out. The methods and technologies for cataloguing tornado events greatly improved in the 1960s and 1970s, a few decades into the time period they focus on. "We don't have a clear grasp early in the period of tornado intensity or exactly how many tornadoes," he says in a phone interview with the Monitor. Michael Mann, director of the Earth System Science Center at Pennsylvania State University who was also not involved in the research, disagrees. "The trend analysis in the tornado data seems sound, but not especially novel – the increase that is found is consistent with other previous work," he writes in an email to the Monitor. But, Dr. Mann says, "the climate change interpretation is fatally flawed." "We published an article in Science only last year showing that the simple procedures used by the current authors (assuming that the climate change component of a time series is reflected by a simple linear trend) are entirely unsound and produce profound artifacts when trying to separate anthropogenic trends from natural variability. In fact, we have published four articles demonstrating this, back to 2006," he writes. So could this mean Tippett and his colleagues' conclusions that the CAPE is not rising are flawed? "Yep," Mann says. One challenge with this data, Tippett says, is that climate trends are assessed on the scale of centuries, not decades. So 50 years is a relatively short period for looking at climate signals. "To do that only using the data is very challenging, so we would like to move to using numerical models which simulate the environment" and allow scientists to manipulate the data to include or exclude climate change or other variables, he explains, "so we can try to isolate what's going on."


News Article | December 2, 2016
Site: www.csmonitor.com

Climate models suggest that conditions for tornado outbreaks should be increasing with rising temperatures, but do the data agree? No more watching videos at work: Facebook will now default to audio This Monday, May 26, 2014 photo from video provided by Dan Yorgason shows a tornado in a worker's camp near Watford City, N.D. As global temperatures warm, climate scientists expect to see more tornadoes reaching their long, swirling bodies down to Earth. But the data isn't exactly cooperating in a straightforward manner. Scientists have reported that, over the last 50 years, the average number of tornadoes that touch down in the United States each year has not risen. But analysis of this data suggests that the most extreme outbreaks, when several twisters appear as part of a single weather event, are on the rise. Surely climate change is playing a role in the rise of those extreme events, a team of researchers at Columbia University expected. But when they analyzed the data they didn't find the signs they expected, they report in a paper published Thursday in the journal Science. No, that doesn't mean climate change isn't behind the rise of extreme tornado outbreaks across the country, study lead author Michael Tippett, a mathematician at Columbia University, tells The Christian Science Monitor in a phone interview. "We're just saying that it's not playing the role that we expected." There are two ingredients that make for conditions conducive to tornadoes, Dr. Tippett explains. One is the propensity of air to rise, called the convective available potential energy (CAPE), and the other is vertical wind shear. Warmer, moist air near the surface of the Earth particularly tends to rise, so climate projections predicted an increased CAPE with climate change and therefore more of one of the key ingredients for tornadoes. As such, Tippett and his colleagues expected to see an increased CAPE in the environments where extreme tornado outbreaks were occurring. But when they dug into the data, that wasn't the case. In fact, wind shear seems to have increased. "The lack of a change in CAPE that correlates with the change in tornadoes is a significant result," Harold Brooks, a researcher at the National Severe Storms Laboratory who was not involved in the research, writes in an email to the Monitor. "Increases in CAPE are, in the convective storms world, the thing we’re most confident in as the planet warms. It’s a fairly direct connection between surface warming and higher CAPE. The fact that they can explain the tornado changes by storm relative helicity (related to shear) changes is, in one aspect, not surprising (it’s a much better predictor of whether a storm will make a tornado than CAPE is), but, in another aspect, difficult to explain. We don’t really have a good conceptual model for why high SRH values should increase as the planet warms." Tippett agrees that his research poses more questions than it answers, particularly when it comes to the role global warming may be playing in tornado trends. "One possibility is that there are aspects of climate change that we don't understand yet," Tippett says. "The other possibility is it's not climate change." The data Tippett and his colleagues are working off might not be the full story, Charles Konrad, director of the Southeast Regional Climate Center who was not involved in the study, points out. The methods and technologies for cataloguing tornado events greatly improved in the 1960s and 1970s, a few decades into the time period they focus on. "We don't have a clear grasp early in the period of tornado intensity or exactly how many tornadoes," he says in a phone interview with the Monitor. Michael Mann, director of the Earth System Science Center at Pennsylvania State University who was also not involved in the research, disagrees. "The trend analysis in the tornado data seems sound, but not especially novel – the increase that is found is consistent with other previous work," he writes in an email to the Monitor. But, Dr. Mann says, "the climate change interpretation is fatally flawed." "We published an article in Science only last year showing that the simple procedures used by the current authors (assuming that the climate change component of a time series is reflected by a simple linear trend) are entirely unsound and produce profound artifacts when trying to separate anthropogenic trends from natural variability. In fact, we have published four articles demonstrating this, back to 2006," he writes. So could this mean Tippett and his colleagues' conclusions that the CAPE is not rising are flawed? "Yep," Mann says. One challenge with this data, Tippett says, is that climate trends are assessed on the scale of centuries, not decades. So 50 years is a relatively short period for looking at climate signals. "To do that only using the data is very challenging, so we would like to move to using numerical models which simulate the environment" and allow scientists to manipulate the data to include or exclude climate change or other variables, he explains, "so we can try to isolate what's going on."


News Article | December 2, 2016
Site: www.csmonitor.com

Climate models suggest that conditions for tornado outbreaks should be increasing with rising temperatures, but do the data agree? No more watching videos at work: Facebook will now default to audio This Monday, May 26, 2014 photo from video provided by Dan Yorgason shows a tornado in a worker's camp near Watford City, N.D. As global temperatures warm, climate scientists expect to see more tornadoes reaching their long, swirling bodies down to Earth. But the data isn't exactly cooperating in a straightforward manner. Scientists have reported that, over the last 50 years, the average number of tornadoes that touch down in the United States each year has not risen. But analysis of this data suggests that the most extreme outbreaks, when several twisters appear as part of a single weather event, are on the rise. Surely climate change is playing a role in the rise of those extreme events, a team of researchers at Columbia University expected. But when they analyzed the data they didn't find the signs they expected, they report in a paper published Thursday in the journal Science. No, that doesn't mean climate change isn't behind the rise of extreme tornado outbreaks across the country, study lead author Michael Tippett, a mathematician at Columbia University, tells The Christian Science Monitor in a phone interview. "We're just saying that it's not playing the role that we expected." There are two ingredients that make for conditions conducive to tornadoes, Dr. Tippett explains. One is the propensity of air to rise, called the convective available potential energy (CAPE), and the other is vertical wind shear. Warmer, moist air near the surface of the Earth particularly tends to rise, so climate projections predicted an increased CAPE with climate change and therefore more of one of the key ingredients for tornadoes. As such, Tippett and his colleagues expected to see an increased CAPE in the environments where extreme tornado outbreaks were occurring. But when they dug into the data, that wasn't the case. In fact, wind shear seems to have increased. "The lack of a change in CAPE that correlates with the change in tornadoes is a significant result," Harold Brooks, a researcher at the National Severe Storms Laboratory who was not involved in the research, writes in an email to the Monitor. "Increases in CAPE are, in the convective storms world, the thing we’re most confident in as the planet warms. It’s a fairly direct connection between surface warming and higher CAPE. The fact that they can explain the tornado changes by storm relative helicity (related to shear) changes is, in one aspect, not surprising (it’s a much better predictor of whether a storm will make a tornado than CAPE is), but, in another aspect, difficult to explain. We don’t really have a good conceptual model for why high SRH values should increase as the planet warms." Tippett agrees that his research poses more questions than it answers, particularly when it comes to the role global warming may be playing in tornado trends. "One possibility is that there are aspects of climate change that we don't understand yet," Tippett says. "The other possibility is it's not climate change." The data Tippett and his colleagues are working off might not be the full story, Charles Konrad, director of the Southeast Regional Climate Center who was not involved in the study, points out. The methods and technologies for cataloguing tornado events greatly improved in the 1960s and 1970s, a few decades into the time period they focus on. "We don't have a clear grasp early in the period of tornado intensity or exactly how many tornadoes," he says in a phone interview with the Monitor. Michael Mann, director of the Earth System Science Center at Pennsylvania State University who was also not involved in the research, disagrees. "The trend analysis in the tornado data seems sound, but not especially novel – the increase that is found is consistent with other previous work," he writes in an email to the Monitor. But, Dr. Mann says, "the climate change interpretation is fatally flawed." "We published an article in Science only last year showing that the simple procedures used by the current authors (assuming that the climate change component of a time series is reflected by a simple linear trend) are entirely unsound and produce profound artifacts when trying to separate anthropogenic trends from natural variability. In fact, we have published four articles demonstrating this, back to 2006," he writes. So could this mean Tippett and his colleagues' conclusions that the CAPE is not rising are flawed? "Yep," Mann says. One challenge with this data, Tippett says, is that climate trends are assessed on the scale of centuries, not decades. So 50 years is a relatively short period for looking at climate signals. "To do that only using the data is very challenging, so we would like to move to using numerical models which simulate the environment" and allow scientists to manipulate the data to include or exclude climate change or other variables, he explains, "so we can try to isolate what's going on."


Amy McGovern, a computer scientist at the University of Oklahoma, has been studying tornadoes, nature's most violent storms for eight years. She uses computational thinking to help understand and solve these scientific problems. Computational thinking is a way of solving problems, designing systems, and understanding human behavior that draws on concepts fundamental to computer science. In science and engineering, computational thinking is an essential part of the way people think about and understand the world. "Since 2008, we've been trying to understand the formation of tornadoes, what causes tornadoes, and why some storms generate tornadoes and other storms don't," McGovern said. "Weather is a real world application where we can really make a difference to people." She wants to find solutions that are useful. Specifically, she is trying to identify precursors of tornadoes in supercell simulations by generating high resolution simulations of these thunderstorms. Supercell storms, sometimes referred to as rotating thunderstorms, are a special kind of single cell thunderstorm that can persist for many hours. They are responsible for nearly all of the significant tornadoes produced in the U.S. and for most of the hailstorms larger than golf ball size. McGovern would like to generate as many as 100 different supercell simulations during this project. In addition to high resolution simulations, McGovern is also using a combination of data mining and visualization techniques as she explores the factors that separate tornado formation from tornado failure. Studying tornadoes and violent weather comes with a high learning curve, as it requires the application of science and technology to predict the state of the atmosphere for a given location. When McGovern first started the research with a National Science Foundation (NSF) Career Grant, she had to attend several classes so that she would understand more about meteorology, the interdisciplinary scientific study of the atmosphere. She worked closely with meteorology students who taught her about the atmosphere, and she, in turn, taught them about computer science. They went back and forth until they understood each other. The early research generated by the NSF Career Grant resulted in developing data mining software and developing initial techniques on lower resolution simulations. "Now, we're trying to make high resolution simulations of super cell storms, or tornadoes," McGovern said. "What we get with the simulations are the fundamental variables of whatever our resolution is—we've been doing 100 meter x 100 meter cubes—there's no way you can get that kind of data without doing simulations. We're getting the fundamental variables like pressure, temperature and wind, and we're doing that for a lot of storms, some of which will generate tornadoes and some that won't. The idea is to do data mining and visualization to figure out what the difference is between the two." Corey Potvin, a research scientist with the OU Cooperative Institute for Mesoscale Meteorological Studies and the NOAA National Severe Storms Laboratory, said: "I knew nothing about data mining until I started working with Amy on this project. I've enjoyed learning about the data mining techniques from Amy, and in turn teaching her about current understanding of tornadogenesis. It's a very fun and rewarding process. Both topics are so deep that you really need experts in both fields to tackle this problem successfully." The process to do this research requires five steps: 1) Running the simulations; 2) Post-processing the simulation to merge the data; 3) Visualizing the data (to ensure the simulation was valid); 4) Extracting the meta-data; and 5) Data mining (discovering patterns or new knowledge in very large data sets). McGovern's research is related to the National Oceanic and Atmospheric Administration's (NOAA) Warn-on-Forecast program, tasked to increase tornado, severe thunderstorm, and flash flood warning lead times to reduce loss of life, injury, and damage to the economy. NOAA believes the current yearly-averaged tornado lead times are reaching a plateau, and a new approach is needed. "My ideal goal would be to find something that no one has thought of...discovering new science," McGovern said. According to the National Weather Service, on average, nearly three out of every four tornado warning issues are false alarms. How do we reduce the false alarm rate for tornado prediction and increase warning lead time? This is a question that McGovern asks on a continual basis. Right now the lead time is about 15 minutes on average for every tornado, but McGovern and team want to be able to better predict it. They're trying to do this by issuing warnings based on probabilities from the weather forecast rather than issuing warnings based on weather that is already about to form. "Once the weather is already starting to form, you won't get a two hour lead time," McGovern said. How Is the Extreme Science and Engineering Discovery Environment (XSEDE) Helping? When asked about XSEDE, McGovern replied: "XSEDE is fabulous. We've been using XSEDE resources for years. I started out with the resources at my university and then quickly outgrew what they had. They pointed me to XSEDE. I started out at NICS using Darter, and when that went away, I started using Stampede at TACC. These resources are fundamental...you can't do this kind of data mining on your PC." Stampede is one of the largest, most capable high-performance computing (HPC) systems in the world. McGovern says she is one of the few people that's using HPC and data mining for severe weather. In addition to using XSEDE's Stampede for high resolution simulations, McGovern is taking advantage of XSEDE's Extended Collaborative Service and Support (ECSS) program. McGovern has been working with Greg Foss at the Texas Advanced Computing Center (TACC) for visualization expertise. ECSS experts like Foss are available for collaborations lasting months to a year to help researchers fundamentally advance their use of XSEDE resources. Foss is an expert in scientific visualization, a field devoted to graphically illustrating scientific data to enable scientists and non-scientists to understand, illustrate, and glean insight from their data. "Greg comes at the problem from a completely different perspective, and provides new ways of looking at the data that you wouldn't have thought of in the beginning," McGovern noted. "Once you get into a domain, it's easy to think, 'This is the only way to look at it,' but then someone else comes along and asks, 'Why are you doing it like that?" Serving as a bridge between science research and the lay person, Foss says he enjoys working through XSEDE and highlighting the value and validity of the program. "I believe in our mission and I believe in the visualization field. It's quite a sense of accomplishment to help our users and even be a part of the science." For this project, Foss says that he's learned more about all of the aspects of weather than any of his six past weather projects. "Ultimately, we're trying to discover if a 3-D visualization approach will be a useful data mining tool for violent weather testbeds," Foss said. Foss, McGovern and Potvin are working together to find storm features (objects) in the tornado simulations. Weather simulations must capture as much of the state of the atmosphere at each time step as possible, and this results in a tremendous amount of data. For example, in one of their first simulated data sets, McGovern had to sort through 352 million data points per time step. "Since you can't save all of this data or mine it, you try to find the high level features because you don't want to do that for 100 simulations by hand, which is the traditional method of studying storms in meteorology. There's no way you can take traditional analysis techniques to that set and find an answer. Data mining is designed to help us sift through that data set and find statistical patterns that are causing tornadoes. The simulations are run in Fortran, the post-processing is in Python, and the data mining is in Java or Python," she said. For Foss, this project is unique. "Instead of designing an interesting way to present the storm event, we're applying visualization techniques, ideas, and training to data mining. We're using the process to explore ways to identify individual storm features, and characteristics that wouldn't be found with other data mining methods," Foss said. McGovern built the first dataset using Darter (decommissioned as of June 2016) at the National Institute for Computation Sciences. The beginning of the process was writing out different variables and transferring this huge dataset (approx. 5.7 TB from one simulation) to TACC. Then, Foss recruited another TACC visualization specialist, Greg Abram, to program a custom data reader for ParaView, and the visualization work could commence. "ParaView is the software I've been using the most at TACC," he said. "Once I get the data and can read it correctly, my goal is to build scenes from different variables, looking for critical values and viewpoints that the researchers confirm are accurate and useful, and hopefully end up with something visually interesting," Foss said. There are variables expected in a storm simulation, such as velocity (direction, distance). "This is the first project where I used velocity's vertical component to model strong updrafts, key indicators of violent weather. The visualization process isn't just building models- it's allowing a viewer to see the data, so it's important a scene communicates accurately, and doesn't mislead or confuse," Foss said. "Visualizing these datasets is important because they are extremely complex, making it difficult to pull out the most physically important information, in this case, processes contributing to tornadogenesis," Potvin said. "The graphics will be used to help develop the storm feature (objects) definitions for the data mining, to ensure automatically extracted objects match visually and subjectively, and to develop definitions for new objects." Potvin continued, "Using the visualizations to guide our object definitions is critical, he said. "We need the data mining to "know" about the storm features that most matter to whether a tornado forms so that it can tell us about the relationships between those features and tornadogenesis. My primary role in the project is to use my familiarity with current conceptual models of these storms to help isolate features known to be important to tornadoes, and to guide identification of features that aren't typically examined in simulations but that may actually play an important role in tornadogenesis." So far, Foss's visualization work has identified six weather features, data mining 'objects' that can potentially be used to learn about tornados and violent weather: hook echoes, bounded weak echo regions, updrafts, cold pools, helicity with regions of strong vorticity, and vertical pressure perturbation gradients. The results came from Foss exploring variables by experimenting with different values and various models, and looking for consistent patterns and interesting structures over the life of the simulated storm. The goal is to compare these simulated storms with real storms. In real weather, you can't actually see these objects. The simulated data sets turn the tornado or storm into what would be actual objects. In real weather, you can't see an updraft, for example. "Greg's visualizations are of much higher quality than what meteorologists typically use, since most of us lack the skills and computational resources," Potvin said. "The four-dimensionality and high resolution provide a much fuller perspective on how storms and tornadoes evolve. I've been studying these storms for over a decade, and these visualizations have changed the way I think about them." In summary, the XSEDE ECSS team investigated computationally intensive datasets using 3D visualization techniques and an interactive user interface with datamining for identifying 'tornadogenesis' precursors in supercell thunderstorm simulations. They found that the results will assist in defining storm features extracted and input to the data mining: ensuring automatically extracted objects match visually identified ones. "We strongly believe that using data science methods will enable us to discover new knowledge about the formation of tornados," McGovern concluded. Explore further: Supercomputer simulations to help predict tornadoes


News Article | December 1, 2016
Site: www.sciencemag.org

The number of tornadoes pounding the United States during the most extreme outbreaks has roughly doubled over the past 50 years, a new analysis shows. But the study also yields a big surprise: The increased severity of such tornado outbreaks, at least at first glance, doesn’t seem to be related to climate change. “Either the recent increases are not due to a warming climate, or a warming climate has implications for tornado activity that we don’t understand,” says study author Michael Tippett, a climate scientist at Columbia University. When Tippett and his colleagues pored through tornado statistics from 1965 through 2015, they identified 435 “extreme outbreaks”—clusters of a dozen or more twisters rated strong enough to have caused at least moderate damage to structures. (Because tornado numbers vary so much from year to year, the team grouped their data into 5-year intervals.) Across that half-century, the number of such outbreaks didn’t change very much, Tippett says. However, the total number of tornadoes in those outbreaks jumped dramatically: In 1965, the worst outbreak included about 40 tornadoes, but in 2015 that number had statistically grown to include nearly 80 ground-scouring twisters, the researchers report online today in . The increase doesn’t seem to be related to better reporting in recent years, says Tippett, so the trends seem to be genuine. The team then looked to weather data for a scientific explanation. One parameter meteorologists use to help identify regions at increased risk of severe weather is called convective available potential energy (CAPE). It’s a measure of the tendency for warm air at Earth’s surface to rise, and most climate models suggest that CAPE will increase as the world’s climate warms. But when Tippett and his colleagues looked at day-to-day estimates for CAPE over the contiguous United States between 1979 (the earliest data available) and 2015, they didn’t see any long-term increase. “This is an unexpected finding,” he notes. But the team did find a substantial increase in another known risk factor for tornado formation: a parameter called storm relative helicity (SRH), which is related to the differences in wind speed and direction at various altitudes between ground level and 3 kilometers. Current models don’t suggest that this factor will increase as the climate warms, but the new study shows that it has in recent years. That, in turn, hints that scientists may not fully understand the link between SRH and climate. “I think the work is well done and intriguing,” says Harold Brooks, a meteorologist at the National Severe Storms Laboratory in Norman, Oklahoma, who was not involved in the study. Overall, the team’s findings provide at least a partial answer to the disturbing trend of the last 50 years, he says. The link between the changes in severe tornado outbreaks and an increase in storm relative helicity is unsurprising but difficult to explain, Brooks says. “We don’t really have a good conceptual model for why SRH should increase as the planet warms.” The next big question, adds Brooks, is to sort out whether long-term climate cycles such as the Atlantic Multidecadal Oscillation are playing a role in those tornado trends. The Atlantic Multidecadal Oscillation is related to sea surface temperatures in the North Atlantic Ocean and, like El Niño, it affects weather far away. Alternatively, researchers might find via further analyses that the increase in SRH is truly to blame. “My money is on the latter,” says Brooks, “but I want essentially even odds and small amounts being wagered.”


Dahl J.M.L.,North Carolina State University | Parker M.D.,North Carolina State University | Wicker L.J.,National Severe Storms Laboratory
Monthly Weather Review | Year: 2012

This study addresses the sensitivity of backward trajectories within simulated near-surface mesocyclones to the spatiotemporal resolution of the velocity field. These backward trajectories are compared to forward trajectories computed during run time within the numerical model. It is found that the population of backward trajectories becomes increasingly contaminated with "inflow trajectories" that owe their existence to spatiotemporal interpolation errors in time-varying and strongly curved, confluent flow. These erroneous inflow parcels may mistakenly be interpreted as a possible source of air for the near-surface vortex. It is hypothesized that, unlike forward trajectories, backward trajectories are especially susceptible to errors near the strongly confluent intensifying vortex. Although the results are based on model output, dual-Doppler analysis fields may be equally affected by such errors. © 2012 American Meteorological Society.


Mazur V.,National Severe Storms Laboratory | Ruhnke L.H.,University of Oklahoma
Journal of Geophysical Research: Atmospheres | Year: 2014

Current cutoff in lightning channels, which takes place in the development of both intracloud and cloud-to-ground flashes, is still poorly understood. A new evaluation of the conditions leading to current cutoff, and also of the two existing hypotheses of the cutoff mechanism, is the main objective of the paper. We reviewed the literature with results of measurements and modeling of free-burning arcs in a laboratory (the closest analogs of lightning leaders) focusing on the relationship between the internal electric field and current. This relationship governs the leader's behavior in the current cutoff. In our analysis of the mechanisms leading to current cutoff, we identify the two types of current cutoff in lightning channels: the current cutoff in a single, unbranched leader channel, which occurs as the result of reaching the threshold conditions for leader propagation; and the current cutoff in branched leaders, when screening by the leader branches alters the ambient electrical environment, thus diminishing the leader current and causing cutoff at a branching point or at the base of the straight channel that preceded branching. We advance the electrostatic model of the screening effect of branching on current cutoff, introduced by Mazur and Ruhnke (1993), and we provide the evidence of this mechanism from lightning observations. We also critically evaluate the concept of lightning-channel instability, proposed by Heckman (1992), as a suggested mechanism leading to current cutoff. We show that the fundamentals of this concept and therefore the concept in its entirety are invalid. © 2014 American Geophysical Union. All Rights Reserved.


Merrelli A.,University of Wisconsin - Madison | Turner D.D.,National Severe Storms Laboratory
Journal of Atmospheric and Oceanic Technology | Year: 2012

The information content of high-spectral-resolution midinfrared (MIR; 650-2300 cm -1) and far-infrared (FIR; 200-685 cm -1) upwelling radiance spectra is calculated for clear-sky temperature and water vapor profiles. The wavenumber ranges of the two spectral bands overlap at the central absorption line in theCO 2 ν 2 absorption band, and each contains one side of the full absorption band. Each spectral band also includes a water vapor absorption band; the MIR contains the first vibrational-rotational absorption band, while the FIR contains the rotational absorption band. The upwelling spectral radiances are simulated with the line-byline radiative transfer model (LBLRTM), and the retrievals and information content analysis are computed using standard optimal estimation techniques. Perturbations in the surface temperature and in the trace gases methane, ozone, and nitrous oxide (CH 4, O 3, and N 2O) are introduced to represent forward-model errors. Each spectrum is observed by a simulated infrared spectrometer, with a spectral resolution of 0.5 cm -1, with realistic spectrally varying sensor noise levels. The modeling and analysis framework is applied identically to each spectral range, allowing a quantitative comparison. The results show that for similar sensor noise levels, the FIR shows an advantage in water vapor profile information content and less sensitivity to forward-model errors. With a higher noise level in the FIR, which is a closer match to current FIR detector technology, the FIR information content drops and shows a disadvantage relative to the MIR. © 2012 American Meteorological Society.

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