NCAR

Decades of data on world's oceans reveal a troubling oxygen decline

NCAR scientist Matthew Long is a co-author of a new study appearing in Geophysical Research Letters. This is an excerpt from a news release by Georgia Tech, a UCAR member institution. May 11, 2017 | A new analysis of decades of data on oceans across the globe has revealed that the amount of dissolved oxygen contained in the water – an important measure of ocean health – has been declining for more than 20 years.Researchers at Georgia Institute of Technology looked at a historic dataset of ocean information stretching back more than 50 years and searched for long term trends and patterns. They found that oxygen levels started dropping in the 1980s as ocean temperatures began to climb.“The oxygen in oceans has dynamic properties, and its concentration can change with natural climate variability,” said Taka Ito, an associate professor in Georgia Tech’s School of Earth and Atmospheric Sciences who led the research. “The important aspect of our result is that the rate of global oxygen loss appears to be exceeding the level of nature's random variability.”The study, which was published April in Geophysical Research Letters, was sponsored by the National Science Foundation and the National Oceanic and Atmospheric Administration. The team included researchers from the National Center for Atmospheric Research, the University of Washington-Seattle, and Hokkaido University in Japan.Read the full news release from Georgia Tech.Global map of the linear trend of dissolved oxygen at the depth of 100 meters. (Image courtesy Georgia Tech.) About the articleTitle: Upper ocean O2 trends: 1958–2015Authors: Takamitsu Ito, Shoshiro Minobe, Matthew C. Long, and Curtis DeutschJournal: Geophysical Research Letters, DOI: 10.1002/2017GL073613

Warmer temperatures cause decline in key runoff measure

BOULDER, Colo. — Since the mid-1980s, the percentage of precipitation that becomes streamflow in the Upper Rio Grande watershed has fallen more steeply than at any point in at least 445 years, according to a new study led by the National Center for Atmospheric Research (NCAR).While this decline was driven in part by the transition from an unusually wet period to an unusually dry period, rising temperatures deepened the trend, the researchers said.The study paints a detailed picture of how temperature has affected the runoff ratio — the amount of snow and rain that actually makes it into the river — over time, and the findings could help improve water supply forecasts for the Rio Grande, which is a source of water for an estimated 5 million people.The study results also suggest that runoff ratios in the Upper Rio Grande and other neighboring snow-fed watersheds, such as the Colorado River Basin, could decline further as the climate continues to warm.Sandhill cranes in the San Luis Valley of Colorado. The mountains ringing the valley form the headwaters of the Rio Grande River, which flows south into New Mexico and along the border between Texas and Mexico. (Photo courtesy of the National Park Service.)"The most important variable for predicting streamflow is how much it has rained or snowed," said NCAR scientist Flavio Lehner, lead author of the study. "But when we looked back hundreds of years, we found that temperature has also had an important influence  — which is not currently factored into water supply forecasts. We believe that incorporating temperature in future forecasts will increase their accuracy, not only in general but also in the face of climate change."The study, published in the journal Geophysical Research Letters, was funded by the Bureau of Reclamation, Army Corps of Engineers, National Oceanic and Atmospheric Administration (NOAA), and National Science Foundation, which is NCAR's sponsor.Co-authors of the paper are Eugene Wahl, of NOAA; Andrew Wood, of NCAR; and Douglas Blatchford and Dagmar Llewellyn, both of the Bureau of Reclamation.Over-predicting water supplyBorn in the Rocky Mountains of southern Colorado, the Rio Grande cuts south across New Mexico before hooking east and forming the border between Texas and Mexico. Snow piles up on the peaks surrounding the headwaters throughout the winter, and in spring the snowpack begins to melt and feed the river.The resulting streamflow is used both by farmers and cities, including Albuquerque, New Mexico, and El Paso, Texas, and water users depend on the annual water supply forecasts to determine who gets how much of the river. The forecast is also used to determine whether additional water needs to be imported from the San Juan River, on the other side of the Continental Divide, or pumped from groundwater.Current operational streamflow forecasts depend on estimates of the amount of snow and rain that have fallen in the basin, and they assume that a particular amount of precipitation and snowpack will always yield a particular amount of streamflow.In recent years, those forecasts have tended to over-predict how much water will be available, leading to over-allocation of the river. In an effort to understand this changing dynamic, Lehner and his colleagues investigated how the relationship between precipitation and streamflow, known as the runoff ratio, has evolved over time.Precipitation vs. streamflow: Tree rings tell a new storyThe scientists used tree ring-derived streamflow data from outside of the Upper Rio Grande basin to reconstruct estimates of precipitation within the watershed stretching back to 1571. Then they combined this information with a separate streamflow reconstruction within the basin for the same period. Because these two reconstructions were independent, it allowed the research team to also estimate runoff ratio for each year: the higher the ratio, the greater the share of precipitation that was actually converted into streamflow."For the first time, we were able to take these two quantities and use them to reconstruct runoff ratios over the past 445 years," Wahl said.They found that the runoff ratio varies significantly from year to year and even decade to decade. The biggest factor associated with this variation was precipitation. When it snows less over the mountains in the headwaters of the Rio Grande, not only is less water available to become streamflow, but the runoff ratio also decreases. In other words, a smaller percentage of the snowpack becomes streamflow during drier years.But the scientists also found that another factor affected the runoff ratio: temperature. Over the last few centuries, the runoff ratio was reduced when temperatures were warmer. And the influence of temperature strengthened during drier years: When the snowpack was shallow, warm temperatures reduced the runoff ratio more than when the snowpack was deep, further exacerbating drought conditions. The low runoff ratios seen in dry years were two and a half to three times more likely when temperatures were also warmer."The effect of temperature on runoff ratio is relatively small compared to precipitation," Lehner said. "But because its greatest impact is when conditions are dry, a warmer year can make an already bad situation much worse."A number of factors may explain the influence of temperature on runoff ratio. When it's warmer, plants take up more water from the soil and more water can evaporate directly into the air. Additionally, warmer temperatures can lead snow to melt earlier in the season, when the days are shorter and the angle of the sun is lower. This causes the snow to melt more slowly, allowing the meltwater to linger in the soil and giving plants added opportunity to use it.The extensive reconstruction of historical runoff ratio in the Upper Rio Grande also revealed that the decline in runoff ratio over the last three decades is unprecedented in the historical record. The 1980s were an unusually wet period for the Upper Rio Grande, while the 2000s and 2010s have been unusually dry. Pair that with an increase in temperatures over the same period, and the decline in runoff ratio between 1986 and 2015 was unlike any other stretch of that length in the last 445 years.The graph shows changes to runoff ratio in the Upper Rio Grande over time. (Image courtesy Flavio Lehner, NCAR.) Upgrading the old approachesThis new understanding of how temperature influences runoff ratio could help improve water supply forecasts, which do not currently consider whether the upcoming months are expected to be hotter or cooler than average. The authors are now assessing the value of incorporating seasonal temperature forecasts into water supply forecasts to account for these temperature influences. The study complements a multi-year NCAR project funded by the Bureau of Reclamation and the Army Corps of Engineers that is evaluating prospects for enhancing seasonal streamflow forecasts for reservoir management.“Forecast users and stakeholders are increasingly raising questions about the reliability of forecasting techniques if climate is changing our hydrology," said Wood, who led the effort. "This study helps us think about ways to upgrade one of our oldest approaches — statistical water supply forecasting — to respond to recent trends in temperature. Our current challenge is to find ways to make sure the lessons of this work can benefit operational streamflow forecasts.” Because the existing forecasting models were calibrated on conditions in the late 1980s and 1990s, it's not surprising that they over-predicted streamflow in the drier period since 2000, Lehner said."These statistical models often assume that the climate is stable," Lehner said. "It's an assumption that sometimes works, but statistical forecasting techniques will struggle with any strong changes in hydroclimatology from decade to decade, such as the one we have just experienced."Lehner is a Postdoc Applying Climate Expertise (PACE) fellow, which is part of the Cooperative Programs for the Advancement of Earth System Science (CPAESS). CPAESS is a community program of the University Corporation for Atmospheric Research (UCAR).About the articleTitle: Assessing recent declines in Upper Rio Grande River runoff efficiency from a paleoclimate perspectiveAuthors: Flavio Lehner, Eugene R. Wahl, Andrew W. Wood, Douglas B. Blatchford, and Dagmar LlewellynJournal: Geophysical Research Letters, DOI: 10.1002/2017GL073253Writer:Laura Snider, Senior Science Writer and Public Information Officer

NCAR to develop advanced wind and solar energy forecasting system for Kuwait

BOULDER, Colo. — Expanding its work in renewable energy, the National Center for Atmospheric Research (NCAR) is launching a three-year project to develop specialized forecasts for a major wind and solar energy facility in Kuwait."We're putting our expertise and technology to work around the world," said NCAR Senior Scientist Sue Ellen Haupt, the principal investigator on the project. "This landmark project meets our mission of science in service to society."The $5.1 million project will focus on developing a system to provide detailed forecasts of wind and solar irradiance at Kuwait's planned 2-gigawatt Shagaya renewable energy plant. After NCAR develops the system, the technology will be transferred to the Kuwait Institute for Scientific Research (KISR) for day-to-day operations.Salem Al-Hajraf of KISR and Antonio J. Busalacchi of UCAR shake hands over an agreement to create a renewable energy forecasting system. Behind them are NCAR scientists (left to right): Gerry Wiener, Branko Kosovic, Sue Ellen Haupt, and William Mahoney. (©UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.)The forecasts will help Kuwait reach its goal of generating 15 percent of its energy from renewable sources by 2030. With the ability to anticipate the amount of electricity that sun and wind will produce hours to days in advance, energy operators will be able to power up or down traditional plants as needed to meet demand."This technology will provide us with important benefits," said Salem Al-Hajraf, manager of KISR's Renewable Energy Program. "We are providing green energy to the grid using abundant sources of energy, which are sun and wind."Reducing renewable energy costsWhen electric utilities integrate power from intermittent sources such as wind or solar into the grid, they temporarily reduce or shut off traditional sources such as oil or natural gas. But if weather conditions fail to come together as expected, the utility may not be able to power up traditional plants in time to meet their customer needs.To help utility managers anticipate renewable wind energy more reliably, NCAR has designed and is constantly improving a wind energy prediction system for Xcel Energy that has saved tens of millions of dollars for the utility’s customers in Colorado and nearby states. The specialized system relies on a suite of tools, including highly detailed observations of atmospheric conditions, advanced computer modeling, and artificial intelligence techniques that enable Xcel Energy to issue high-resolution forecasts for wind farm sites.With funding from the U.S. Department of Energy, NCAR has also led a national team of scientists who have developed a cutting-edge forecasting system with the potential to save the solar energy industry hundreds of millions of dollars in the United States alone through improved forecasts. The new Sun4CastTM system, unveiled last year, greatly improves predictions of clouds and other atmospheric conditions that influence the amount of energy generated by solar arrays.Adapting to new conditionsIn Kuwait, the NCAR team will build on these technologies to develop both wind and solar energy forecasts. The scientists will customize the system to predict dust storms that can blot out sunlight and damage wind turbines. They will also incorporate the influence of nearby mountain ranges and the Persian Gulf on local weather patterns."This is a great opportunity to do research into dust and other particulates, which we haven't previously needed to focus on to this extent for wind and solar energy prediction," Haupt said. "This kind of work will pay multiple dividends for energy forecasting as well as better understanding and predicting of weather in certain desert environments."Haupt and her team will collaborate with researchers at Pennsylvania State University and Solar Consulting Services in Florida, as well as with KISR."This is an exciting international partnership that will both generate significant economic benefits and advance our understanding of the atmosphere," said Antonio J. Busalacchi, president of the University Corporation for Atmospheric Research. "In addition to reducing energy costs for our partners in Kuwait, the knowledge that we gain will help us further improve weather prediction skills here in the United States."The University Corporation for Atmospheric Research is a nonprofit consortium of 110 North American colleges and universities that manages the National Center for Atmospheric Research under sponsorship by the National Science Foundation.KISR leads and partners internationally to develop, deploy, and exploit the best science, technology, knowledge, and innovation for public and private sector clients, for the benefit of Kuwait and others facing similar challenges and opportunities. Sun4Cast is a trademark of the University Corporation for Atmospheric Research.

Promoting diversity in high-performance computing

May 2, 2017 | Justin Moore was supporting his family of four with a job at an auto parts store while juggling classes at Salish Kootenai College, a Native American college in Montana, when he heard about a computing internship in 2014 at the National Center for Atmospheric Research (NCAR) in Boulder, Colo.The internship, which used a small, low-cost computer called Raspberry Pi to teach key concepts of high-performance computing, quickly paid off. Today, Moore works full-time as an IT network specialist at Energy Keepers Inc., which manages the hydroelectric plant on the Flathead Indian Reservation in Montana, while he continues to chip away at his degree."I believe the skills I obtained in the internship can be directly attributed to my success in my field," Moore said. "It also gave me the chance to network with some of the brightest minds in the country."Justin Moore turned a summer internship at NCAR into a full-time computer networking job at a hydroelectric plant on the Flathead Indian Reservation in Montana. (©UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.)Since 2014, NCAR has been using Raspberry Pi as part of the SIParCS (Summer Internships in Parallel Computational Science) program to teach "hot" computing skills to small groups of university students, including one or two who are underrepresented in the sciences. In March, in efforts to reach more students, NCAR pivoted to an "externship" model, bringing the Raspberry Pi training to Miami Dade College faculty who can teach the skills to dozens of students at a time. “Raspberry Pi is a perfect platform for high-performance computing education because the credit-card sized mother boards can be linked together to mimic the parallel processing capabilities of a supercomputer and perform simplified geoscience applications,” said Rich Loft, director of technology development in NCAR's Computational and Information Systems Laboratory.A Raspberry Pi, which costs $35 or less, can run a full Linux operating system — the same system used by nearly all supercomputers, in more than 90 percent of smartphones, and in many other electronic devices.A Raspberry Pi kit used during the NCAR training at Miami Dade College. The Raspberry Pi circuit board is in the upper right-hand corner, connected to a blue cable. Components plug into a breadboard in the center of the picture (Photo courtesy Rich Loft, NCAR.)"It's inexpensive. It levels the playing field," said Loft, who led the training at Miami Dade College. "In my view it busts the digital divide."Loft noted that the previous internship approach wasn't reaching as many students as NCAR had hoped, partly because many students found it too difficult to relocate to Boulder during the summer. Miami Dade proved an ideal testbed for an externship model, since it's one of the country's largest universities, with eight campuses and more than 90,000 students, 70 percent of whom are Hispanic and 17 percent of whom are African American."This approach has scalability," Loft said, shortly after returning from the intensive two-day faculty workshop. "You can't scale up a program training one student at a time, even though it's very rewarding."The NCAR directorate, which supported the Miami Dade training through a diversity grant, hopes that an expanded program will reap even greater outcomes.A legacy of successThe Raspberry Pi internship approach already has yielded additional success stories, with students going on to graduate school and receiving prestigious scholarships.Lauren Patterson, for example, was a student at Hampton University in Virginia when she learned Raspberry Pi as a SIParCs intern at NCAR, also in 2014. "I loved that I was able to work hands-on and assemble the Raspberry Pi cluster myself," Patterson said.Lauren Patterson has received an Apple scholarship and will start a job at Google after completing her summer internship on Raspberry Pi at NCAR. (@UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.) She said her experience led to an Apple internship under its scholars program, a $25,000 scholarship, and a software engineering job at Google starting next fall in New York City. Apple scholars participate in a 12-week internship at Apple headquarters in California, receive ongoing coaching and guidance, and serve as Apple ambassadors on their campuses.Gaston Seneza, a senior at Philander Smith College in Arkansas, said that before NCAR's SIParCS 2015 internship he had no practical knowledge of computers.He learned about Linux, sensors, programming, cloud storage, and scientific research, and now has a passion for computer science. "Raspberry Pi was a game-changer for me," he said.Gaston Seneza, who is from Rwanda, also won an Apple scholarship after his summer internship at NCAR. (@UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.) The Rwandan native also was named an Apple scholar, and aspires to go into the field of artificial intelligence. "My dream is to see a world where intelligent machines work for us."Said Loft: "We're trying to get these kids on the hi-tech career onramp. You put machine learning or experience with parallel computing on your resume and you can get hired by Apple, Google, or Amazon – or get into graduate school. These are hot skills." Machine learning is a type of artificial intelligence in which a computer program can change or "learn" as it encounters new data.Moore, Patterson, and Seneza all praised the mentoring by Loft, an NCAR senior scientist, and Raghu Raj Prassana Kumar, an NCAR project scientist who has worked with the Raspberry Pi training project since its beginning."It's a lot of fun, and it's very rewarding to help these young people learn," Kumar said.Kumar is also known at NCAR for creative uses of Raspberry Pi, including connecting 12 of them to calculate Pi to a million digits on Pi Day in 2015. (It took longer than a day and one Raspberry Pi burned out from exertion, but it was successful.)Connecting learning to everyday lifeAt the recent Miami Dade workshop, Kumar and Loft, along with University of Wyoming Professor Suresh Muknahallipatna and three of his students, taught 20 Miami Dade faculty members how to set up and program simple projects with a Raspberry Pi. One group used sensors to measure things like temperature, pressure, and humidity, while another created a word frequency histogram from the complete works of William Shakespeare using a Raspberry Pi Hadoop cluster.Ana Guzman (far right), a Miami Dade College associate professor of electricial engineering, gets Raspberry Pi tips from Cena Miller, a University of Wyoming student. A group of Miami Dade faculty members were trained recently on using the low-cost computers for hands-on teaching by a team that included NCAR computer scientists and University of Wyoming students. (Photo courtesy Rich Loft, NCAR.) David Freer, a Miami Dade computer science professor, said he and his colleagues thought the workshop was terrific. "We worked with flame sensors that sent messages to users on their cell phones, along with other cool projects," he said.Djuradj Babich, director of Miami Dade's School of Engineering and Technology, said he hopes to "ride the excitement wave" from the training and develop an ongoing relationship with NCAR. Loft said NCAR also hopes to reach out to additional universities.Qiong Cheng, an assistant professor at Miami Dade, has since set up a Raspberry Pi in her office, complete with a motion detector. She said she will use the Raspberry Pi platform in her classes this fall, which are part of a new bachelor's program in data analytics.She likes the fact that Raspberry Pi, combined with sensors, is an inexpensive way to measure data in the real world, and thus connect learning to everyday life.  "Students are more interested in that," she said, adding that Raspberry Pi supports "our mission to reach underrepresented students — to motivate them, to inspire them, and to provide them with a hands-on learning experience."That's the kind of talk that excites Loft."We want to continue to collaborate to drive this home. Which means that Miami Dade is using this in their curriculum as the workhorse in their computer lab for students," he said. "That's what's going to make me very happy."Writer/Contact:Jeff Smith, Science Writer and Public Information Officer  

Capturing a detailed portrait of wind

April 28, 2017 | For two autumns in the early 1980s, researchers covered an isolated, gently sloping hill in Scotland with dozens of scientific instruments to measure the behavior of wind as it blew up and over from the nearby coast. More than three decades later, the resulting data set gathered on Askervein hill is still the benchmark for validating how well a computer model can simulate winds flowing over complex terrain.An image of the hill at Askervein. (Image courtesy of York University.)But that's about to change.The National Center for Atmospheric Research (NCAR) is partnering with colleagues in Europe and the United States on a field project in Portugal, called Perdigão, that will measure wind at an unprecedented resolution, both in time and space, as it moves through a more topographically diverse study area.The experiment aims to help scientists improve their understanding of the basic physics of wind in the boundary layer (the lowest few hundred feet of the atmosphere). The completed data set will also serve as a new, more detailed, and more complex benchmark for testing the accuracy of the next generation of wind models.Having accurate models of wind behavior in the boundary layer, where most weather occurs, is critical for a wide range of applications, from harvesting wind energy to predicting the spread of air pollution to piloting drones.'No easy feat'When scientists selected the Perdigão study area in central Portugal, they were looking for a place more complex than the single hill at Askervein but still relatively simple and easy to model.Perdigão has two nearly parallel ridgelines that stand just a couple of kilometers apart, and the wind typically hits these ridges at a perpendicular angle, either from the southwest or the northeast. Unlike the Askervein hill, which was covered largely in heather and small shrubs, the landscape at Perdigão includes both forested and agricultural lands. Such differences in terrain and land cover can have important influences on local winds.For the project, which begins its six-week "intensive operations period" on May 1, NCAR's Earth Observing Lab was tasked with outfitting 47 observational towers with instruments that will collect data on wind speed and direction, as well as temperature and humidity, from a variety of heights. The NCAR team is also in charge of networking all the instruments being used for the field campaign so they can talk to each other and to the researchers."This is the largest ground-based project we have ever taken on," said Alison Rockwell, who is managing the project for NCAR. "Networking that many towers with that many instruments — it's no easy feat."The Perdigão study area, with its nearly parallel ridges, as seen using Google Earth. (©UCAR. Courtesy NCAR Earth Observing Laboratory. This image is freely available for media & nonprofit use.) A unique look at the wind's mysteriesThe measurements taken by the instruments on the 47 towers outfitted by NCAR, along with those from five additional towers provided by project partners, will be supplemented by observations from a variety of other balloon-borne and ground-based instruments. Those include lidars, which can remotely measure the basic structure of the wind field using laser beams."One of the totally unique aspects of this experiment is the use of lidars to measure the main wind field," said NCAR scientist Steve Oncley, a contributing investigator on the project. "It frees up the instruments on the towers to measure the fine-scale turbulence close to the ground."This ability to measure the wind at multiple scales simultaneously is another reason that data gathered during Perdigão is expected to be a vast improvement over the 1980s data set. While a similar number of towers were deployed at the Askervein hill, the instruments primarily measured wind at only one height, leaving much of the structure of fine-scale turbulence occurring close to ground a mystery.One of the questions that Oncley hopes the experiment will answer in particular — which the 1980s data could not — is how wind behaves as it blows over the crest of the ridge: "When you have a strong wind, does it actually blow through the trees, down to the soil? Or does it just graze the tops of the trees as it flows over?"The answer matters for understanding how much momentum is extracted from the wind, as well as how much heat and carbon dioxide are transferred between wind and landscape.The Perdigão project is part of a larger effort to publish a digital New European Wind Atlas, supported by a European Union funding instrument called ERANET+. The Europeans are particularly interested in the detailed wind velocity data for use in wind energy development.U.S. principal investigators are Joe Fernando (University of Notre Dame), Julie Lundquist (University of Colorado, Boulder), Petra Klein (University of Oklahoma), Rebecca Barthelmie (Cornell University), Sara Pryor (Cornell University), Tina Katopodes Chow (University of California, Berkeley), Chris Hocust (U.S. Army Research Laboratory), and Laura Leo (University of Notre Dame).European Principal Investigators are Jakob Mann (Technical University of Denmark) and José Palma (University of Porto, Portugal).Data from a long-range wind scanner at the Perdigão site  Writer/contact:Laura Snider, Senior Science Writer and Public Information Officer

Building roads to match tomorrow's weather

April 20, 2017 | When engineers design roads, bridges, and other types of transportation infrastructure, they need to account for local weather patterns. Extreme heat or freeze-thaw cycles can lead to ruts and cracks in roads, and heavy rains can overwhelm inadequate drainage systems, washing out bridges and flooding key transportation corridors.But how should engineers design new transportation projects, which may last for a half-century, if climate change will greatly alter weather patterns? The extent to which temperatures and precipitation may change in the future has become a major concern for the transportation industry.To address this issue, climate scientists at the National Center for Atmospheric Research (NCAR) are launching an innovative collaboration with civil and environmental engineers at Carnegie Mellon University and the RAND Corporation. They're using global and regional computer models, along with statistical techniques, to generate projections of future climate in ways that will be most helpful to infrastructure designers and planners, especially when it comes to drainage.A girl looks at a washed-out road in Louisville, Colorado, after damaging floods in 2013. Engineers are teaming up with climate scientists to design transportation infrastructure that can withstand shifting weather patterns. (Photo by David Hosansky.)The three-year project, funded by the National Science Foundation, will focus on Pittsburgh and several other cities across the country that will likely be affected in different ways by future climate."Our overriding goal is to enable transportation agencies to maximize the lifetime performance of new infrastructure while minimizing the costs to ensure its resilience to extreme weather events," said NCAR senior scientist Linda Mearns, the principal investigator on the project.Several recent studies led by NCAR scientists have underscored the extent to which climate change may affect future temperature and precipitation extremes in the United States. One concluded that, if emissions of greenhouse gases continue along a business-as-usual course, record daily high temperatures will outpace record daily lows by about 15 to 1 later in the century. A second study, also looking at emissions continuing on a business-as-usual path, concluded that incidents of extreme rainfall may increase by as much as five times in parts of the country.More detail means more uncertaintyTo conduct the new project, Mearns and her colleagues are working closely with local transportation officials and other stakeholders. Rather than analyzing the overall ways that climate is likely to change in the target cities, they're focusing on information that will be most useful to the design and construction of drainage infrastructure and other transportation systems."This requires very active engagement with stakeholders," Mearns said. "It's working together to determine what they want versus what we can actually provide and coming up with measures of uncertainty that are meaningful for them. This is in the realm of true coproduction of knowledge."For example, an engineer designing a drainage system along a highway might want an estimate of how much precipitation will fall in 15-minute increments. Although climate models do not provide such detailed information, Mearns and her colleagues can provide a partial answer by using a combination of techniques to produce projections of future precipitation every hour to several hours, as well as characterizing the uncertainty around those projections.A major challenge is that more detailed projections have greater uncertainty. While climate models consistently show that emissions of greenhouse gases lead to higher average global temperatures, the outlook is less clear for temperature and precipitation patterns by region. The type of information most needed by infrastructure planners and designers—projections of extreme temperatures and precipitation for specific locations and time periods—is even more uncertain. As a result, the study team will have to make compromises between the need for high-resolution data and the need for reliable data.Mearns said it's critical to give engineers a clear understanding of the uncertainty of a particular projection in order to prevent transportation projects from being based on a false sense of precision in climate projections. "The challenge," she said, "is developing sound engineering strategies for extremes under uncertainty."In addition to Mearns, the NCAR scientists working on the project include Seth McGinnis, Melissa Bukovsky, Rachel McCrary, and Doug Nychka. The Carnegie Mellon team is being led by Costa Samaras, who directs the school's Center for Engineering and Resilience for Climate Adaptation.“This project is a unique interdisciplinary collaboration that will advance the ways engineers and climate scientists will work together in the future,” said Samaras. “Infrastructure can last for many decades, and engineers need to design infrastructure to be resilient at the end of the infrastructure life span as well as in the beginning. Working with NCAR is critical to advancing the research needed to transform the way we design infrastructure in the United States."The benefit of different techniquesTo generate climate projections, Mearns and her colleagues will use two types of techniques to translate the coarse resolution of a global computer model, which typically simulates climate processes that are larger than about 100 miles, into the localized weather events that are of interest to transportation experts.One of these techniques, known as dynamical downscaling, will use a combination of three coarser-resolution global climate models and two higher-resolution regional models (including the NCAR-based Weather Research and Forecasting model, or WRF). This will enable the researchers to simulate the entire globe in coarse resolution while zooming in on selected regions with much higher resolution. This approach doesn't need as much supercomputing power as trying to simulate the entire globe in high resolution, although it still can be computationally intensive.The other technique, known as statistical downscaling, involves developing statistical relationships between large-scale atmospheric patterns and local temperatures and precipitation. This technique, which requires even less computing, can help scientists link conditions in a global model (such as a large area of low pressure) to a localized weather event (such as intermittent downpours).The combined approaches will enable the scientists to generate projections for at least every six hours, and possibly—with the use of additional specialized techniques—as frequently as every hour. Using both the dynamical and statistical approaches also will enable the team to better understand the uncertainties around future climate as well as evaluate the relative strengths of the techniques."Transportation systems are critical to the U.S. economy, and they represent some of the largest investments of our tax dollars," Mearns said. "We want to make sure that they'll hold up to a future climate."FunderNational Science FoundationPartnersCarnegie Mellon UniversityRAND CoroporationWriter/contactDavid Hosansky, Manager of Media Relations

Our People - Rory Kelly

April 19, 2017 | On weekdays in winter, while most people are still sleeping, Rory Kelly is driving to a ski area in the dark, slipping into his ski mountaineering gear, and training for two hours before heading back to Boulder for his job as a software engineer in NCAR's Computational and Information Systems Laboratory (CISL).

Drones need aviation forecasts, too

UAS Weather ForumWhat: An opportunity for stakeholders from the UAS community -- including manufacturers, operators, regulators, and researchers -- to come together to discuss weather effects on drones and the support needed to mitigate those impacts.When: 9 a.m. - 12 p.m., Monday, May 8, 2017Where: XPONENTIAL, Kay Bailey Hutchison Convention Center, Dallas Click here for more information.April 13, 2017 | The possible future uses for drones are spectacularly diverse. Unmanned aircraft systems (UAS) could make door-to-door deliveries, search for a lost hiker, survey agricultural crops, inspect infrastructure, or collect scientific data from difficult-to-reach places, among other things. Already Amazon is experimenting with drone delivery of packages, for example, and BNSF Railway is testing the use of drones to inspect hundreds of miles of railroad tracks.Yet the ultimate success of efforts like these may hinge on a good weather forecast. The National Center for Atmospheric Research (NCAR), long a trusted provider of critical weather information to the aviation industry, is beginning to lend its expertise to the UAS community as well.Staff in NCAR's Research Applications Laboratory are already working with NASA to provide low-level turbulence forecasts for NASA's project to create a UAS Traffic Management (UTM) system, which would be similar to the air traffic control system for crewed airplanes. And in May, the NCAR team is hosting a UAS Weather Forum in Dallas. The forum will be co-located with XPONENTIAL, a conference on "all things unmanned" that is organized by the Association of Unmanned Vehicle Systems International."As the aircraft get smaller and smaller, the challenges of providing the needed weather information increase," said NCAR scientist Matthias Steiner, deputy director of RAL's Aviation Applications Program. "These small UAS's are more sensitive to winds, temperature, turbulence, precipitation — essentially the full range of weather — than larger planes flying at higher altitudes."NASA engineers prepare to launch a remotely piloted aircraft during practice runs for an Unmanned Aircraft Systems Traffic Management test. (Image courtesy NASA.)Weather impacts on dronesDrones, at least the small ones allowed under current Federal Aviation Administration rules, fly in the lowest few hundred feet of the atmosphere, where weather can be highly dynamic and less predictable.This layer of the atmosphere is heavily affected by land surface and topography. Consider, for example, wind as it blows through a city. The buildings force the wind to speed through "urban canyons" and swirl into tight eddies behind structures. Uneven heating — the sunny side of the street warming more than the shady side, for example — can create circulating downdrafts and updrafts.Piloting a drone through a built-up area could be tricky without a detailed understanding of the local atmospheric circulation patterns. And even with that information, it's important to understand how different drones will be affected. The tinier and lighter the drone, the more vulnerable it is to the vagaries of the weather, just as a small Cessna is more vulnerable to turbulence than a giant 747. And the type of drone, such as a fixed wing or a quadcopter, matters as well because each has a different ability to respond.The concern is not just crashing on the ground; severe weather conditions could also lead to a collision in the sky. NASA's UTM project is exploring the possibility of managing a high volume of drones by essentially assigning individual UAS's to a lane of airspace. But weather will affect the ability of a drone to stay in its lane. An abrupt updraft, for instance, could force a drone that is supposed to fly at a lower altitude into the higher-altitude lane assigned to another UAS (or a crewed aircraft in mixed airspace), increasing the possibility of a collision between the two.Weather can have less obvious impacts on drone operation as well. Extremely cold weather, headwinds, or turbulence that requires a lot of flight control adjustments could drain the aircraft's battery more quickly, reducing its range and, potentially, its ability to return home. Facilitating a community dialogueThese kinds of weather challenges would likely not surprise a seasoned aviator. But many of the organizations interested in using drones today come to the UAS community from the technology side, not the aviation side, and may lack a full understanding of the impacts that atmospheric conditions can have on flight.This is where NCAR has expertise to offer. For decades, NCAR has been providing the aviation industry with the tools they need to increase flight safety, including wind shear alerts, turbulence forecasts, and information on inflight icing potential.In an effort to stay on top of the latest weather challenges facing the aviation industry, NCAR launched the Friends and Partners in Aviation Weather Forum in 1997. The meeting, now held twice yearly, is an opportunity for stakeholders from the operational, regulatory, and research sectors to come together."We created these meetings as a means of fostering dialogue," Steiner said. "We want to know: 'What are your operational sensitivities? How can we help you?' Now we are emulating these forums with the UAS community. "The UAS Weather Forum at the XSPONENTIAL conference on May 8 is the first effort at starting a similar meeting—and fostering the dialogue needed to advance drone safety, even in the face of challenging weather conditions."We want drone operators to know NCAR is a partner that can help them address their weather impacts," Steiner said.Writer/contact: Laura Snider, Senior Science Writer and Public Information Officer

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