Tech Transfer

NCAR partners with UC San Diego on visualization capabilities

BOULDER - The National Center for Atmospheric Research (NCAR) is partnering with the University of California, San Diego (UC San Diego) to expand and enhance visualization capabilities in the bio- and geosciences through a grant from the National Science Foundation. The collaboration builds on existing software capabilities developed at NCAR and UC San Diego, and it will combine them to produce new open-source tools for scientists to explore large data sets. The project is known as WASP (Wavelet-enabled Progressive Data Access and Storage Protocol). Current advances in digital imaging and numerical modeling technologies have enabled the creation of vast amounts of data. A challenge for many researchers is making sense out of these digital outputs. One way of dealing with extremely large data sets is known as progressive data access (PDA), which is the enabling technology behind consumer applications like Google Maps. In mapping applications, PDA reduces data volumes by only loading areas of interest, not the entirety of the map database, and allows the user to view these images in greater or lesser detail. The problem is that similar tools are scarce in the biosciences, despite a need for analyzing data gathered from advanced imaging technologies such as MRI and CT scans. Also, as the size and complexity of the data increase, the computing resources commonly available for data analysis are over-subscribed. The geosciences encounter similar issues, with models for weather, climate, oceans and other Earth systems generating very large and complex data. Given the similar nature of the challenge across various disciplines, researchers at NCAR and UC San Diego put their heads together to work on a solution, capitalizing on complementary work that was already ongoing at both institutions. Though the bio- and geosciences are very different scientific disciplines, with different data, the underlying forms and structure of the data are very similar, allowing for shared methods of dealing with the information. Two software approaches This high-resolution simulation of 2005's Hurricane Katrina as is it makes landfall on the Gulf Coast was visualized with VAPOR. (Image courtesy John Clyne, NCAR.) An NCAR team has developed a software solution known as VAPOR (Visualization and Analysis Platform for Ocean, Atmosphere and Solar Researchers). VAPOR provides an interactive 3D-visualization environment that runs on most UNIX and Windows systems. At the heart of VAPOR is a progressive data access scheme based on mathematical linear transforms using wavelets. An NSF grant launched the development of the technology in 2003, and VAPOR is currently on its third major release, with over 6,000 users worldwide. “VAPOR is an application specifically designed to facilitate researchers’ interaction with very large data sets, but while using only relatively modest computing resources,” said John Clyne, a software engineer and computer scientist who is the principal investigator for VAPOR in NCAR’s Computational and Information Systems Laboratory (CISL). “VAPOR is already widely used in the geosciences community, and with this award we will not only be able to expand and improve it for its current users, but also make it usable for the biosciences and bioimaging communities.” At UC San Diego, the Center for Scientific Computation in Imaging has been developing a general analysis and visualization software toolkit for the bioimaging community, known as the Shape Analysis for Phenomics from 3D Imaging Data (SAPID) ToolKit (STK). The goal of the SAPID project is to develop advanced computational methods for researchers in evolutionary biology to characterize subtle morphological variations from high-resolution 3D voxel-based digital imaging modalities. (A voxel is analogous to a pixel, but in three-dimensional space.) A critical issue that arose during this project was the necessity of being able to handle very large datasets.  This new NSF award will address this important issue and thus provide innovative capabilities to the bioimaging community. “This award is exciting because it allows us to take our existing software, combine and reuse it in new ways, and expand its capabilities to serve more broadly across scientific disciplines,” said Lawrence Frank, the principal investigator for the WASP award and the SAPID Project and a researcher at UC San Diego’s Institute of Engineering in Medicine at the Jacobs School. This image demonstrates progressive data access applied to a high-resolution CT scan of a seadragon. The leftmost view of the seadragon head was constructed using a fraction of the data (1/100th), yet is morphologically identical to the rightmost image constructed using all of the available CT data. (Image courtesy UC San Diego.) Both Frank and Clyne point out that the most important aspect of this collaboration is it will reuse existing NSF-funded software to provide a common framework benefitting both biological digital imaging and geosciences numerical modeling communities. It will have a profound impact for scientists working with large data sets. “We’ll be able to provide better tools to the climate and weather science communities, while providing the first such tools for the biosciences community,” said Clyne. “It’s especially gratifying that NSF’s initial investments in both VAPOR and STK can be augmented with this award to produce an impactful and inter-disciplinary tool.”

NCAR renewable energy prediction system wins prestigious Governor’s Award

BOULDER – A cutting-edge wind and solar energy forecasting system that has saved electricity consumers $40 million has won a prestigious 2014 Colorado Governor's Award for High-Impact Research in the Sustainability category as well as an honorable mention in Public-Private Partnerships. The advanced system, developed by the National Center for Atmospheric Research and implemented for Xcel Energy, has dramatically increased the amount of renewable energy provided to the grid. It was funded by Xcel Energy, which is a national leader on wind energy. Workers install panels being used by the U.S. Department of Energy to leverage a Power Purchase Agreement with Sun Edison and Xcel Energy. A prediction system developed at NCAR is helping Xcel Energy increase the amount of power going from renewable energy systems into the grid.  (Wikimedia Commons photo by Dennis Schroeder.) "It is very gratifying to take our scientific and technological expertise and apply it in a way that has a meaningful impact on society," said William Mahoney, deputy director of NCAR's Research Applications Lab. "We're developing systems that offer the dual benefit of saving costs and reducing emissions of pollutants that are harmful to the environment." The Governor's Award is given each year by CO-LABS, a nonprofit that works to inform the public about the breakthroughs and impacts from Colorado's 30 federally funded labs and research facilities. The CO-LABS consortium includes Colorado federal research laboratories, research universities, state and local governments, economic development organizations, private businesses, and nonprofit organizations. Ken Lund, executive director of Colorado's Office of Economic Development and International Trade, will present the awards at this year's reception on November 12 to teams from NCAR and three other Colorado-based research centers for extraordinary research in the areas of Atmospheric Science, Foundational Technology, Public Health, and Sustainability. The awards presentation will take place at the Denver Museum of Science & Nature.  The sponsor, the Alliance for Sustainable Energy, manages the National Renewable Energy Laboratory (NREL) on behalf of the Department of Energy (DOE).  NREL is the DOE's primary national laboratory for renewable energy and energy efficiency research and development. The annual reception is the major CO-LABS event to showcase Colorado's research facilities and the work of the CO-LABS organization. NCAR's energy forecasting system relies on a suite of tools, including highly detailed observations of atmospheric conditions, energy generation, an ensemble of cutting-edge computer models, and advanced statistical techniques, to issue high-resolution forecasts of wind energy generation that are updated with new information every 15 minutes. "The wind and solar forecasting system developed with NCAR has given Xcel Energy increased confidence each day in determining the amount of renewable energy we can expect, as we strive to provide reliable power at a competitive price for our Colorado customers," said David Eves, president and CEO of Public Service Co. of Colorado, an Xcel Energy company. "We believe this modeling will provide equal certainty for other U.S. utilities as they also increase the amount of renewable generation in their portfolios." "We're very pleased that this investment in an energy forecasting system has paid such significant dividends," said UCAR president Thomas Bogdan. “This work illustrates how an increasingly detailed understanding of the atmosphere leads to important advances for society." NCAR also received honorable mention in the Sustainability category this year for the Global Energy and Water Exchanges (GEWEX) Project, which focuses on developing better ways to understand global and regional climate, especially water resources. NCAR senior scientist Kevin Trenberth and the international GEWEX research team collectively studies the water cycle and how to translate research results into practical applications. Trenberth chaired the GEWEX scientific steering committee from 2010 to 2013. Other winners of this year's Governor's Award include: Atmospheric Science"Into the Air"Cooperative Institute for Research in Environmental Sciences and the National Oceanic and Atmospheric Administration Foundational Technology"Commercialization of Cold-Atom Technology"JILA, University of Colorado Boulder Public Health"An Oral Vaccine Produced in Rice Grain to Reduce the Risk of Lyme Disease" Centers for Disease Control and Prevention (CDC) "Researchers in Colorado's federal laboratories continue to lead the nation with valuable study that addresses some of today's most pressing problems," said Scott Sternberg, chair of CO-LABS. "Our annual ceremony does more than just recognize new discoveries, it also celebrates the impact research and science have on our state." The University Corporation for Atmospheric Research (UCAR) manages NCAR under sponsorship by the National Science Foundation. Any opinions, findings, conclusions, or recommendations expressed in this release do not necessarily reflect the views of the National Science Foundation.    

Will climate change shift renewable energy resources?

October 8, 2014 | Building a large-scale wind farm or solar power plant involves an enormous investment in time and money. Requirements include exploring prime sites for capturing energy from wind or sunshine, purchasing the land, undergoing a potentially lengthy permitting process, and installing costly infrastructure. Not surprisingly, utilities expect such facilities to last many decades. But what if, years from now, changes in climate caused some of the wind or sunshine to shift away from major facilities? An array of wind turbines generates power on a sunny afternoon at the Cedar Creek wind farm in northeast Colorado. New research is providing estimates of how the availability of wind and solar energy might shift as a result of climate change over the next few decades. (©UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.) To help provide guidance to utilities, scientists at NCAR and the National Renewable Energy Laboratory have produced maps that show how wind speeds and solar irradiance may evolve by 2060 across the continental United States. The maps (see bottom of page for a sample) include projections for each season and for different times of day, while taking into account natural variability. The maps provide a first, rough sketch of how wind and solar patterns may shift with climate change. Research into regional climate change remains a challenging field because of uncertainties over how warming temperatures will affect particular parts of the country. The maps were created for the Department of Energy's Regional Energy Deployment System (ReEDS) model, which helps the Energy Department optimize and visualize the build-out of U.S. electricity generation and transmission systems. The underlying research will be submitted to a peer-reviewed publication. As this sampling of maps shows, the United States is likely to experience some noticeable changes in wind and sunshine patterns by 2060. For example, the Northeast should prepare for a slight increase in wintertime winds in the morning at the height of wind turbine hubs (about 250 feet above the ground). In summer and fall, a noticeable reduction in winds at the same time of day is likely. Parts of the Southwest, in contrast, are likely to have less wind at hub height in winter and somewhat more in summer and fall. By 2060, much of the country can expect more energy from the Sun during an average summer morning. In the winter, however, the northern tier is likely to get less energy from the Sun while the southern states receive more. The shifts are not overwhelming—generally 10 percent or less. But they can be important for energy planning. “These are subtle changes but they can make a difference in where a utility sites a wind or solar facility now,” said Sue Haupt, who oversees renewable energy research at NCAR. “Energy managers need to consider whether a resource is going to decline or become stronger in the future.” To create the maps, Haupt and her team drew on an advanced, NCAR-based database of current wind and solar resources, known as the Climate Four Dimensional Data Assimilation System. They then turned to simulations of projected future regional climate conditions that had already been generated by a number of computer models for the North American Regional Climate Change Assessment Program. By using artificial intelligence techniques, they were able to emphasize those computer models that most accurately captured current wind and sunshine conditions and apply those models to produce outlooks of future conditions. Haupt said she hopes to update the maps in a few years, drawing on more sophisticated climate models. Note - October 14, 2014 | The fourth paragraph and maps caption have been updated to clarify that this research, performed for the Department of Energy, will be submitted to a peer-reviewed journal. Writer/contactDavid Hosansky, NCAR & UCAR Communications Collaborating institutionNational Renewable Energy Laboratory FunderNational Renewable Energy Laboratory (U.S. Department of Energy) DIVE DEEPER The maps below indicate possible changes in projected solar radiation (top) and wind speed (bottom) during morning hours, averaged across each of the four seasons, for the year 2060 vs. 1995. Created for the U.S. Department of Energy, the maps provide a first, rough sketch of how wind and solar patterns may shift with climate change. The researchers also created additional maps for afternoon, evening, and overnight conditions. The underlying research will be submitted to a peer-reviewed journal. (Images courtesy Sue Haupt, NCAR.)    

Predicting the Lyme disease season

July 9, 2014 | Warmer temperatures, higher humidity, and less rain are correlated with an earlier start and peak of each year’s Lyme disease season, researchers have found. Using the dates of Lyme disease cases reported to the U.S. Centers for Disease Control and Prevention (CDC) and meteorological data from 1992 to 2007, researchers at NCAR and the CDC have for the first time analyzed the timing of the warm-season ramp-up of Lyme disease transmission. The research should help forecasters develop predictions of the onset and peak of future Lyme disease seasons. More than 20,000 cases of Lyme disease are reported in the United States each year. On this map, one dot is placed randomly within the county of residence for each confirmed case in 2011 reported to the U.S. Centers for Disease Control and Prevention for locations within the map domain. In 2012, 95% of U.S. cases of Lyme disease were reported from just 12 states; all are shown on this map. Though Lyme disease cases have been reported in nearly every state, cases are reported based on the county of residence, not necessarily the county of infection. (Image courtesy CDC.) Lyme disease is a tick-borne illness primarily found in the northeastern United States (from southern Maine to northern Virginia) and Wisconsin and Minnesota. The start and peak of the human infection season occur earlier in the spring in southern states, and later in northern states, but vary overall from year to year. The researchers found that for all but the northernmost states, higher cumulative temperatures above a baseline of 50°F (10°C) measured from the beginning of the year were reliably associated with an earlier start to the Lyme disease season. For all regions, a greater amount of precipitation accumulating from the start of the year was consistently associated with a later beginning to the season. The start of the Lyme disease season (defined as the week the number of Lyme disease cases increased most rapidly) varied by up to 6 weeks in the same state over the 16-year period analyzed. The average season begins in late May and lasts for 14 weeks. The team of researchers, led by Sean Moore, a former public health and climate postdoctoral fellow at NCAR and the CDC, published the findings earlier this year in the American Journal of Tropical Medicine and Hygiene. NCAR scientist Andrew Monaghan supervised the team’s meteorological analysis. “While you can predict the Lyme season more accurately as the beginning of the season nears, we found that, by looking at the daily temperatures out to the 10th week of the year, we could predict the start of the season almost as well as waiting until the 20th week,” Monaghan said. With more validation, the CDC could eventually use the analysis to provide public warnings about the likelihood of encountering ticks bearing Lyme disease, he said. Lyme disease is the most common vector-transmitted disease in the United States. It may progress from causing a characteristic bull’s-eye rash to triggering serious neurological or heart problems, meningitis, or arthritis, if left untreated. It is caused by a bacterial spirochete that is primarily transmitted by Ixodid ticks. The ticks pass on the bacteria when they attach to mammals to obtain the blood they need to complete each of three developmental stages. Nymphal ticks, which are about the size of a poppy seed, cause most of the cases of Lyme disease in humans because their small size makes them very hard to find and remove. Nymphal ticks develop faster with warmer temperatures, and more actively seek hosts for a blood meal between late spring and fall when there are warmer temperatures, higher humidity, and the absence of heavy precipitation. These same weather conditions are also ones that encourage people to spend more time outside, the researchers noted. The availability of other hosts, such as rodents and deer, also plays a role in maintaining tick populations and may increase the transmission of Lyme disease. ContactDavid Hosansky, NCAR/UCAR Communications ResearchersSean Moore (former NCAR/CDCpostdoctoral researcher,now at Johns HopkinsSchool of Public Health)Rebecca Eisen, CDCPaul Mead, CDCAndrew Monaghan, NCAR Collaborating institutionsNational Center for Atmospheric ResearchU.S. Centers for Disease Control and Prevention (CDC) Funders CDC National Science Foundation  

Predicting flu season

December 20, 2013 | Using methods from weather and climate forecasting, researchers have developed a forecasting system for the flu that can incorporate real-time data to predict the week that influenza levels will peak. A research team that included NCAR’s Alicia Karspeck made 12 weekly forecasts for 108 U.S. cities during the 2012-13 flu season, and found the system accurately predicted the outbreak’s peak for 60 percent of the cities weeks in advance. People wear face masks in Mexico during a 2009 outbreak of the flu. Scientists have created a pilot system to forecast flu outbreaks. (Photo by Henry Merino, Wikimedia Commons.) The researchers, led by Jeffrey Shaman of Columbia University, combined a model of disease transmission with data from Google Flu Trends, which tracks internet searches on flu-related terms, and with data from the Centers for Disease Control, which tracks the number of people testing positive for flu. Karspeck focused on advanced data assimilation techniques, which combined observations with computer simulations to estimate the current state of flu cases. This enabled the researchers to tune the model with real-time data as the season progressed. The study was published earlier this month in Nature Communications. Karspeck’s usual work is with the data assimilation system for the ocean component of the Community Earth System Model, a global climate model that incorporates data about the atmosphere, land surface, ocean and sea ice to make long-term climate predictions. But five years ago, while at a conference, she had a discussion about forecasting with a former graduate school classmate who was creating a model of influenza outbreaks. “It’s a sort of technology transfer, in the sense that we have a very strong group here at NCAR that works in data assimilation to support forecast initialization,” Karspeck said. “We took the same technology and methodologies and crossed disciplines.” Data assimilation allows the model to reflect actual influenza conditions in a population, she said, such as the number of susceptible people, the number of people who already have the flu, and those who have some immunity to it. Data assimilation was also used to tune the model in real time, so that it could better reflect population and virus characteristics that are relevant to the evolving outbreak. The researchers believe that this leads to more accurate predictions as the season progresses. The number of people who have the flu usually peaks sometime between December and April. The researchers will test the model again this winter and plan to validate the forecasts after the season ends. Having advance notice of when the number of people infected will rapidly increase could help reduce the severity of flu outbreaks by motivating more people to be vaccinated in advance, or giving officials the option to close schools or cancel events that could facilitate flu transmission. Influenza is associated with the deaths of anywhere from 3,000 to 49,000 people each year in the United States. Jeffrey Shaman, Alicia Karspeck, Wan Yang, James Tamerius, Marc Lipsitch, Real-time influenza forecasts during the 2012–2013 season, Nature Communications, 4, December 3, 2013. doi:10.1038/ncomms3837

NCAR powers up renewable energy forecasts

BOULDER—The National Center for Atmospheric Research (NCAR), building on a pioneering wind energy forecasting system that saved millions of dollars for Xcel Energy ratepayers in eight states, has entered into a new agreement with the utility for even more sophisticated weather forecasts. Wind turbines in northeast Colorado. (©UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.) In the next two years, NCAR scientists and engineers will develop custom forecasting systems to predict sudden changes in wind, shut down turbines ahead of potentially damaging icing events, and even predict the amount of energy generated by private solar panels. The systems will be used by Xcel Energy control centers in Denver; Minneapolis; and Amarillo, Texas. The cutting-edge forecasts will help Xcel Energy, and potentially other utilities, to provide reliable power to their customers and reduce costs while moving to greater use of wind and solar. “This is pushing the state-of-the-art still further, using the latest science to enable Xcel Energy to generate energy from the atmosphere more effectively,” says NCAR program director Sue Ellen Haupt, who is overseeing the new project. “Every improvement to the forecasts results in additional savings.” Xcel Energy officials say the more accurate forecasts are critical as they increase their use of renewable energy. “The importance and value of accurate renewable energy generation forecasts increases with the size of our renewable energy generation portfolio,” says Ben Fowke, chairman, president, and CEO of Xcel Energy. “Xcel Energy has been the largest utility provider of wind energy for the last nine years and we are continuing to grow our renewable energy portfolio.” The new project represents the latest venture by NCAR into renewable energy. In addition to the lab’s earlier work with Xcel, it is also spearheading a three-year, nationwide project to create unprecedented, 36-hour forecasts of incoming energy from the Sun for solar energy power plants. “By creating more detailed and accurate forecasts of wind and Sun, we can produce a major return on investment for utilities,” says Thomas Bogdan, president of the University Corporation for Atmospheric Research, which manages NCAR on behalf of the National Science Foundation. “This type of cutting-edge research helps make renewable energy more cost competitive.” Reliable forecasts needed Xcel Energy has been utilizing increasing amounts of energy from renewable sources, especially wind. But this shift means relying on resources that are challenging to predict and manage. Changes in weather can have significant impacts on wind energy production. This graphic shows how passing thunderstorms and a cold front generated an 800-megawatt jump in energy production over the course of just four hours. (Image courtesy Sue Ellen Haupt, NCAR. This image is freely available for nonprofit and media use.) Energy generated by a wind turbine, solar panel, or any other source must be promptly consumed because large amounts of electricity cannot be stored in a cost-effective manner. If an electric utility powers down a coal or natural gas facility in anticipation of wind-driven energy, those plants may not be able to power up fast enough should the winds fail to blow. The only option in such a scenario is to buy energy on the spot market, which can be very costly. In order to help utility managers anticipate wind energy more reliably, NCAR began designing a wind energy prediction system for Xcel Energy in 2009 that saved the utility’s customers over $6 million in 2010 alone. The specialized system relies on a suite of tools, including highly detailed observations of atmospheric conditions, an ensemble of powerful computer models, and artificial intelligence techniques to issue high-resolution forecasts for wind farm sites. Following up on that work, NCAR has entered into a two-year agreement with Xcel Energy to focus on the following areas: Forecasting “ramp” events. A new system under development at NCAR can provide utility managers with advance notice of a major change in wind energy over a few hours due to a passing front or another atmospheric event. The system, known as VDRAS (Variational Doppler Radar Analysis System) relies on techniques that combine observations from radars and other tools with computer simulations to create more accurate forecasts for particular wind farms. Predicting ice and extreme temperatures. To keep aircraft safe from potentially lethal icing conditions while aloft, NCAR has created state-of-the-art ice forecasting systems that use computer models and specialized algorithms. Applying similar technology, researchers at NCAR and Pennsylvania State University will develop a 48-hour forecasting system at designated wind farms to predict the impacts of freezing rain and fog on wind turbines, which cannot operate when coated in ice. The team also will forecast extreme low and high temperatures, which can cause wind farms to temporarily shut down. Generating solar forecasts. Xcel Energy customers who have their own solar panels draw far less energy from the grid while the sun is out, and can even sell excess energy back to the utility. To help Xcel Energy better anticipate when their customers are getting power from their own panels, NCAR will create a solar energy forecasting system, using a combination of computer models and specialized cloud observing tools. Some of these new systems will provide “probabilistic forecasts,” estimating the chances that a particular weather event will occur. This means that utility managers will be able to make decisions based on whether there is an 80 percent chance of certain weather events at a wind farm the next day, or a 20 percent chance. “We’re taking our expertise in critical areas, such as keeping airplanes safe from icing, and applying it to obtaining as much energy as possible from the atmosphere,” says NCAR program manager Marcia Politovich, who is overseeing the development of icing and extreme temperature forecasts. “This is cutting-edge science.” Once the systems are finalized, they will be turned over to Xcel Energy or a utility contractor for ongoing operation. NCAR researchers will publish the results in peer-reviewed journals, enabling other utilities and forecast providers to learn about the technologies. “Xcel Energy is recognized by the energy industry as a national leader in proactively moving forward with the utilization of renewable energy,” says William Mahoney, deputy director of NCAR's Research Applications Laboratory. "This new project is an example of how improved understanding of the atmosphere can provide significant benefits to society."  

Solar energy to get boost from cutting-edge forecasts

BOULDER—Applying its atmospheric expertise to solar energy, the National Center for Atmospheric Research (NCAR) is spearheading a three-year, nationwide project to create unprecedented, 36-hour forecasts of incoming energy from the Sun for solar energy power plants. A new research initiative is designed to lead to unprecedented 36-hour forecasts of incoming energy from the Sun, thereby helping utilities obtain energy more efficiently from solar energy power plants. (Wikimedia Commons photo by Thomas R. Machnitzki.) The research team is designing a prototype system to forecast sunlight and resulting power every 15 minutes over specific solar facilities, thereby enabling utilities to continuously anticipate the amount of available solar energy. The work, funded primarily with a $4.1 million U.S. Department of Energy grant, will draw on cutting-edge research techniques at leading government labs and universities across the country, in partnership with utilities, other energy companies, and commercial forecast providers. Much of the focus will be on generating detailed predictions of clouds and atmospheric particles that can reduce incoming energy from the Sun. “It’s critical for utility managers to know how much sunlight will be reaching solar energy plants in order to have confidence that they can supply sufficient power when their customers need it,” says Sue Ellen Haupt, director of NCAR’s Weather Systems and Assessment Program and the lead researcher on the solar energy project. “These detailed cloud and irradiance forecasts are a vital step in using more energy from the Sun.” The project takes aim at one of the greatest challenges in meteorology: accurately predicting cloud cover over specific areas. In addition to helping utilities tap solar energy more effectively, detailed cloud predictions can also improve the accuracy of shorter-term weather forecasts. The project expands NCAR’s focus on renewable energy. NCAR designed a highly detailed wind energy forecasting system with Xcel Energy that saved Xcel ratepayers an estimated $6 million in a single year. The center is also creating advanced prediction capabilities to enable wind farm developers to anticipate wind energy potential anywhere in the world. “Improving forecasts for renewable energy from the Sun produces a major return on investment for society,” says Thomas Bogdan, president of the University Corporation for Atmospheric Research, which manages NCAR on behalf of the National Science Foundation. “By helping utilities produce energy more efficiently from the Sun, we can make this market more cost competitive.” Clouded forecasts More than half of all states in the U.S. have mandated that utilities increase their use of renewable energy as a way to reduce dependence on fossil fuels such as coal, oil, and natural gas, which affect air quality and release greenhouse gases associated with climate change. But the shift to energy sources such as solar or wind means relying on resources that are difficult to predict. Because large amounts of electricity cannot be stored in a cost-effective manner, power generated by a solar panel or any other source must be promptly consumed. If an electric utility powers down a coal- or natural gas-fired facility in anticipation of solar energy, those plants may not be able to power up fast enough if clouds roll in. The only option in such a scenario is to buy energy on the spot market, which can be very costly. Conversely, if more sunshine reaches a solar farm than expected, the extra energy can go to waste. But predicting clouds, which form out of microscopic droplets of water or ice, is also notoriously difficult. Clouds are affected by a myriad of factors, including winds, humidity, sunlight, surface heat, and tiny airborne particles, as well as chemicals and gases in the atmosphere. Solar energy output is affected not just by when and where clouds form, but also by the types of clouds present. The thickness and elevation of clouds have greatly differing effects on the amount of sunlight reaching the ground. Wispy cirrus clouds several miles above the surface, for example, block far less sunlight than thick, low-lying stratus clouds. To design a system that can generate such detailed forecasts, NCAR and its partners will marshal an array of observing instruments, including lidars (which use laser-based technology to take measurements in the atmosphere); specialized computer models; and mathematical and artificial intelligence techniques. Central to the effort will be three total sky imagers in each of several locations, which will observe the entire sky, triangulate the height and depth of clouds, and trace their paths across the sky. The team will test these advanced capabilities during different seasons in several geographically diverse U.S. locations: the Northeast, Florida, Colorado/New Mexico, and California. The goal is to ensure that the system works year round in different types of weather patterns. Not just for solar energy Once the system is tested, the techniques will be widely disseminated for use by the energy industry and meteorologists. “This will raise the bar for providing timely forecasts for solar power, ” Haupt says. “It also represents a great opportunity for providing far more detail about clouds in the everyday weather forecasts that we all rely on.” One application for such detailed forecasts could be short-term predictions of pavement temperatures. Such information would be useful to airport managers, road crews, and professional race car drivers. “Pavement temperatures make quite a bit of difference in how tires grip the surface,” says Sheldon Drobot, deputy director of NCAR’s Weather Systems and Assessment Program. “This has substantial safety implications.” NCAR is launching the solar project with numerous partners in the public and private sectors. These include: Government labs: National Renewable Energy Laboratory, Brookhaven National Laboratory, the National Oceanic and Atmospheric Administration’s Earth System Research Laboratory and other NOAA facilities; Universities: The Pennsylvania State University, Colorado State University, University of Hawaii, and University of Washington; Utilities: Long Island Power Authority, New York Power Authority, Public Service Company of Colorado, Sacramento Municipal Utility District (SMUD), Southern California Edison, and the Hawaiian Electric Company; Independent system operators: New York ISO, Xcel Energy, SMUD, California ISO, and Hawaiian Electric; and Commercial forecast providers: Schneider Electric, Atmospheric and Environmental Research, Global Weather Corporation, and MDA Information Systems. Computing time will be provided by the New York State Department of Economic Development's Division of Science, Technology and Innovation on an IBM Blue Gene supercomputer at Brookhaven National Laboratory.

Bringing science to market

September 21, 2012 | The NCAR-Wyoming Supercomputing Center is a major public-private partnership, but it’s not the only one at UCAR that helps turn meteorological know-how into tangible benefits for the public and the economy. As a research organization, UCAR is not designed to develop or market products specifically for commercial applications. Instead, the UCAR Foundation—a nonprofit subsidiary of UCAR—has helped start up small, specialized companies that focus on market research and product development to move new technologies into the commercial sector, where they can meet important societal needs. Bill Gail (©UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.) “There are tremendous capabilities and knowledge within academia that could provide a public benefit,” explains Bill Gail, chief technology officer of Global Weather Corporation, a company formed by the UCAR Foundation for the purpose of technology transfer. Legislation such as the 1980 Bayh-Dole Act encourages UCAR and other recipients of federal research dollars to demonstrate progress toward transferring technology to the business world. One of the organization’s first such transfers took place in 1987, when it granted the commercial rights for the NCAR mass storage system to Mesa Archival Systems, a company formed by the UCAR Foundation specifically to develop and commercialize the system. Since then, other companies formed by the foundation have moved additional products into the marketplace. These include the Weather Support to De-Icing Decision Making System (WSDDM), which helps airport decision makers handle flight operations during wintry weather. An airport worker deices a commercial jet before winter take-off. NCAR's WSDDM system provides snowfall "nowcasts" specifically tailored to airport deicing operations. (©UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.) More recently, Global Weather has worked to commercialize an advanced weather forecasting system developed at NCAR known as the Dynamic Integrated Forecast System, or DICast. The system generates highly localized forecasts of winds, temperature, humidity, and other atmospheric parameters. Utilities are adopting it to help forecast winds at wind farms, and road crews can also take advantage of its capabilities to keep traffic flowing during inclement weather. The technology has been developed over more than a decade under the leadership of RAL scientist and engineer Bill Myers. Moving a research product into the commercial sector is challenging, says Jeff Reaves, chief operating officer for the UCAR Foundation. The product must be significantly modified for user groups that range from specific sectors to the general public, a process that involves market research as well as engineering. At the end, the process can lead to specialized and sophisticated products that save lives and safeguard property, as well as bolstering the nation’s economy. “It’s all about finding applications for our knowledge and technology that benefit society,” explains Reaves. Gail, who worked in the meteorological sensor field at Ball Aerospace and in software services at Microsoft, says there are numerous opportunities to move research at NCAR and the broader university community into the commercial sector in order to help users. “There are many, many new ways of using weather that people are just beginning to understand,” he says. “Weather information is surprisingly under-utilized in the world today.” For more on related NCAR and UCAR efforts, visit NCAR Community Resources: Technology Transfer and  UCAR Foundation: Technology Commercialization.

New airport system facilitates smoother take-offs and landings

BOULDER—For airline passengers who dread bumpy rides to mountainous destinations, help may be on the way. A new turbulence avoidance system has for the first time been approved for use at a U.S. airport and can be adapted for additional airports in rugged settings across the United States and overseas. The new turbulence avoidance system enables pilots to view areas of moderate (yellow) and severe (red) turbulence. (©UCAR. Screen capture from NCAR's Juneau Airport Warning System. This image is freely available for media & nonprofit use.) The system, developed by the National Center for Atmospheric Research (NCAR), provides information pilots can use to route aircraft away from patches of potentially dangerous turbulence. It uses a network of wind measuring instruments and computational formulas to interpret rapidly changing atmospheric conditions. The Federal Aviation Administration formally commissioned the system in July for Alaska’s Juneau International Airport. NCAR researchers can now turn their attention to adapting the system to other airports that often have notoriously severe turbulence, in areas ranging from southern California and the Mountain West to Norway and New Zealand. The Juneau system was patterned after a similar system, also designed by NCAR, that has guided aircraft for several years at Hong Kong’s heavily trafficked Chek Lap Kok Airport. “By alerting pilots to areas of moderate and severe turbulence, this system enables them to fly more frequently and safely in and out of the Juneau airport in poor weather,” says Alan Yates, an NCAR program manager who helped oversee the system’s development. “It allows pilots to plan better routes, helping to reduce the bumpy rides that passengers have come to associate with airports in these mountainous settings.” The system offers the potential to substantially reduce flight delays. In Alaska’s capital city, where it is known as the Juneau Airport Wind System or JAWS, it enables the airport to continue operations even during times of turbulence by highlighting corridors of smooth air for safe take-offs and landings. Al Yates (©UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.) “The JAWS system has nearly eliminated all the risk of flying in and out of Juneau,” says Ken Williams, a Boeing 737 captain and instructor pilot with Alaska Airlines. “I wish the system would be deployed in other airports where there are frequent encounters with significant turbulence, so pilots can get a true understanding of what the actual winds are doing on the surrounding mountainous terrain as you approach or depart.” The project was funded by the Federal Aviation Administration. NCAR is sponsored by the National Science Foundation. Steep terrain, rough rides Turbulence has long been a serious concern for pilots approaching and departing airports in steep terrain. Rugged peaks can break up air masses and cause complex and rapidly changing patterns of updrafts and downdrafts, buffeting an aircraft or even causing it to unexpectedly leave its planned flight path. In Juneau, after several turbulence-related incidents in the early 1990s—including one in which a jet was flipped on its side during flight and narrowly avoided an accident—the FAA imposed strict rules of operation that effectively shut down the airport during times of atmospheric disturbance. The agency then asked NCAR to develop a system that would allow pilots to avoid regions of turbulence. Otherwise, Alaska’s capital would be isolated at many times from the rest of the state, since the only way to travel in and out of Juneau is by airplane or boat. The NCAR team used research aircraft and computer simulations to determine how different wind patterns—such as winds that come from the north over mountains and glaciers and winds that come from the southeast over water—correlated with specific areas of turbulence near the airport. To do this they installed anemometers and wind profilers at key sites along the coast and on mountain ridges. The team has installed ruggedized, heated instruments that can keep functioning even when exposed to extreme cold, wind, and heavy icing conditions. The Federal Aviation Administration accepted JAWS for operational use this year.    The five anemometer sites and three wind profiler sites around the airport transmit data multiple times every minute. Pilots can get near-real-time information about wind speed and direction, and a visual readout showing regions of moderate and severe turbulence in the airport’s approach and departure corridors, from the FAA’s Flight Service Station or online at a National Weather Service website, where an integrated display "app" is also available for download. “Juneau was an extremely challenging case, and we’re pleased that the new system met the FAA’s high standards,” Yates says. “We look forward to exploring opportunities to support development of turbulence avoidance systems at additional airports. Our goal is to improve flying safety and comfort for millions of passengers.”
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