NCAR

High-resolution regional modeling (no supercomputer needed)

Annual precipitation over Colorado as modeled by the low-resolution, global Community Earth System Model (top) compared to the high-resolution, regional Weather Research and Forecasting model (below). (Images courtesy Ethan Gutmann, NCAR.) February 13, 2017 | In global climate models, the hulking, jagged Rocky Mountains are often reduced to smooth, blurry bumps. It's a practical reality that these models, which depict the entire planet, typically need to be run at a relatively low resolution due to constraints on supercomputing resources. But the result, a virtual morphing of peaks into hills, affects the ability of climate models to accurately project how precipitation in mountainous regions may change in the future — information that is critically important to water managers.To address the problem, hydrologists have typically relied on two methods to "downscale" climate model data to make them more useful. The first, which uses statistical techniques, is fast and doesn't require a supercomputer, but it makes many unrealistic assumptions. The second, which uses a high-resolution weather model like the Weather Research and Forecasting model (WRF), is much more realistic but requires vast amounts of computing resources.Now hydrologists at the National Center for Atmospheric Research (NCAR) are developing an in-between option: The Intermediate Complexity Atmospheric Research Model (ICAR) gives researchers increased accuracy using only a tiny fraction of the computing resources."ICAR is about 80 percent as accurate as WRF in the mountainous areas we studied," said NCAR scientist Ethan Gutmann, who is leading the development of ICAR. "But it only uses 1 percent of the computing resources. I can run it on my laptop."Drier mountains, wetter plainsHow much precipitation falls in the mountains — and when — is vitally important for communities in the American West and elsewhere that rely on snowpack to act as a frozen reservoir of sorts. Water managers in these areas are extremely interested in how a changing climate might affect snowfall and temperature, and therefore snowpack, in these regions.But since global climate models with low resolution are not able to accurately represent the complex topography of mountain ranges, they are unsuited for answering these questions.For example, as air flows into Colorado from the west, the Rocky Mountains force that air to rise, cooling it and causing moisture to condense and fall to the ground as snow or rain. Once these air masses clear the mountains, they are drier than they otherwise would have been, so there is less moisture available to fall across Colorado's eastern plains.Low-resolution climate models are not able to capture this mechanism — the lifting of air over the mountains — and so in Colorado, for example, they often simulate mountains that are drier than they should be and plains that are wetter. For a regional water manger, these small shifts could mean the difference between full reservoirs and water shortages."Climate models are useful for predicting large-scale circulation patterns around the whole globe, not for predicting precipitation in the mountains or in your backyard," Gutmann said.Precipitation in millimeters over Colorado between Oct. 1 and May 1 as simulated by the Weather Research and Forecasting model (WRF), the Intermediate Complexity Atmospheric Research model (ICAR), and the observation-based Parameter-Elevation Regressions on Independent Slopes Model. (Images courtesy Ethan Gutmann.)A modeling middle groundA simple statistical fix for these known problems may include adjusting precipitation data to dry out areas known to be too wet and moisten areas known to be too dry. The problem is that these statistical downscaling adjustments don't capture the physical mechanisms responsible for the errors. This means that any impact of a warming climate on the mechanisms themselves would not be accurately portrayed using a statistical technique.That's why using a model like WRF to dynamically downscale the climate data produces more reliable results — the model is actually solving the complex mathematical equations that describe the dynamics of the atmosphere. But all those incredibly detailed calculations also take an incredible amount of computing.A few years ago, Gutmann began to wonder if there was a middle ground. Could he make a model that would solve the equations for just a small portion of the atmospheric dynamics that are important to hydrologists — in this case, the lifting of air masses over the mountains — but not others that are less relevant?"I was studying statistical downscaling techniques, which are widely used in hydrology, and I thought, 'We should be able to do better than this,'" he said. "'We know what happens when you lift air up over a mountain range, so why don’t we just do that?'"Gutmann wrote the original code for the model that would become ICAR in just a few months, but he spent the next four years refining it, a process that's still ongoing.100 times as fastLast year, Gutmann and his colleagues — Martyn Clark and Roy Rasmussen, also of NCAR; Idar Barstad, of Uni Research Computing in Bergen, Norway; and Jeffrey Arnold, of the U.S. Army Corps of Engineers — published a study comparing simulations of Colorado created by ICAR and WRF against observations.The authors found that ICAR and WRF results were generally in good agreement with the observations, especially in the mountains and during the winter. One of ICAR's weaknesses, however, is in simulating storms that build over the plains in the summertime. Unlike WRF, which actually allows storms to form and build in the model, ICAR estimates the number of storms likely to form, given the atmospheric conditions, a method called parameterization.Even so, ICAR, which is freely available to anyone who wants to use it, is already being run by teams in Norway, Austria, France, Chile, and New Zealand."ICAR is not perfect; it's a simple model," Gutmann said. "But in the mountains, ICAR can get you 80 to 90 percent of the way there at 100 times the speed of WRF. And if you choose to simplify some of the physics in ICAR, you can get it close to 1,000 times faster."About the articleTitle: The Intermediate Complexity Atmospheric Research Model (ICAR)Authors: Ethan Gutmann, Idar Barstad, Martyn Clark, Jeffrey Arnold, and Roy RasmussenJournal: Journal of Hydrometeorology, DOI: 10.1175/JHM-D-15-0155.1Funders:U.S. Army Corps of EngineersU.S. Bureau of ReclamationCollaborators:Uni Research Computing in NorwayU.S. Army Corps of EngineersWriter/contact: Laura Snider, Senior Science Writer

Scientists take to the skies to test cloud seeding

February 7, 2017 | Does cloud seeding successfully increase snowfall? This winter, scientists with the National Center for Atmospheric Research (NCAR) are taking part in a field project in Idaho that will help answer the question.The project, called SNOWIE (Seeded and Natural Orographic Wintertime Clouds — the Idaho Experiment), is taking place from Jan. 7 to March 17 in the Payette Basin region north of Boise. A public-private partnership, SNOWIE is led by scientists at the University of Wyoming and other universities in collaboration with NCAR, with funding from the National Science Foundation (which is NCAR's sponsor) and the Idaho Power Company.The research team is using airborne and ground-based radars, high-resolution snow gauges, and computer modeling to gain insights into what happens after clouds are seeded with silver iodide. Snow from winter storms develops when ice crystals form on dust and other particles known as "ice nuclei." In cloud seeding, silver iodide is used to make artificial nuclei to encourage snowflakes to form.Silver iodide is released during the SNOWIE field project in such a way that it disperses downwind to the east, with its highest concentrations forming a zigzag pattern (shown in red). This allows scientists to fly a research aircraft from west to east through both seeded and unseeded regions and compare differences in ice crystal formation. (Image by Lulin Xue, ©UCAR. This image is freely available for media & nonprofit use.)NCAR scientists are focusing much of their work on observations taken by a University of Wyoming King Air plane that is flying though plumes of silver iodide released by a seeding aircraft. The silver iodide disperses downwind in a zigzag pattern, enabling the King Air to intercept it multiple times. The scientists will compare the formation of ice crystals in regions of clouds that are seeded with those that are not.The results can also be used to improve the NCAR-based Weather Research and Forecasting model (WRF), especially its simulation of cloud microphysics related to cloud seeding.Although scientists think that cloud seeding and other types of weather modification can increase precipitation in certain circumstances, the effects are difficult to quantify."NCAR's role in these weather modification experiments is to provide an unbiased viewpoint," said NCAR scientist Sarah Tessendorf, a principal investigator on SNOWIE. "The project uses observations and computer models to determine what is happening during a cloud seeding program and whether it is effective as a water augmentation tool."For more about the project, see the NSF news release.Writer/contactDavid Hosansky, Manager of Media RelationsFundersNational Science FoundationIdaho Power CompanyPartnersUniversity of WyomingIdaho Power CompanyUniversity of Colorado BoulderUniversity of Illinois at Urbana-ChampaignBoise State UniversityCenter for Severe Weather ResearchWeather Modification, Inc.

New apps set atmospheric data spinning in 3D

Feburary 6, 2017 | Students of microbiology can grow bacteria in petri dishes to better understand their subject. Paleontology students have fossils, and chemistry students have beakers bubbling with reactions. But students of the atmospheric and related sciences are often left with something much less tangible: data, and lots of it.The Meteo AR app uses augmented-reality techniquest to make atmospheric science data more accessible to the public. (©UCAR. This animation is freely available for media & nonprofit use.)Datasets in the atmospheric sciences cover everything from observations made by weather balloons to satellite measurements of cloud cover to output from climate model runs.Now the National Center for Atmospheric Research (NCAR) is helping make those data less abstract and more concrete  — a little closer to a rock sample and a little further from a computer file. The result is two apps: one using virtual-reality and one using augmented-reality techniques to create 3D visualizations of datasets on a globe that students can move around and view from different perspectives. Meteo VR (Virtual Reality) and Meteo AR (Augmented Reality) are available for use on iPhone, iPad, and Android devices. They were developed by NCAR's Computational and Information Systems Lab (CISL)."The goal is to make our data more accessible to the public, especially to students," said Tim Scheitlin, a senior software engineer at CISL's Visualization Lab. "We think it's a fun way to start a dialogue about atmospheric science. If people can get excited about using the app, then maybe they'll start asking questions that will lead to a deeper understanding."The 'wow' factor and beyondThe Meteo AR app takes advantage of the camera on a personal device. When the camera's pointed at an image from a visualization — of sea surface temperature anomalies during an El Niño, or of the inner workings of a hurricane, for example — the visualization pops up onto a 3D globe that can be spun around with a finger.The Meteo VR app requires a virtual reality headset, such as Google Cardboard, and allows the user to "fly around" the globe to look at the projected dataset from any angle.Development of the two apps was led by Nihanth Cherukuru, a doctoral student at Arizona State University. He came to NCAR last summer as part of CISL's Summer Internships in Parallel Computational Science (SIParCS) program, which strives "to make a long-term, positive impact on the quality and diversity of the workforce needed to use and operate 21st century supercomputers."Cherukuru said one of the challenges of the project was to wrestle the vast amounts of data into a format that wouldn’t crash a handheld device. "Mobile phones are tiny devices and the atmospheric data can be really huge," Cherukuru said. "We needed to take that data and trim it down. We created a single image for each timestamp and then we made animations to reduce the computational burden on the phones."While Cherukuru has returned to Arizona State after his SIParCS internship, he is still working with the Visualization Lab. The goal is to expand the apps' capabilities, perhaps, for example, by having users click on parts of the data to get more information."There's kind of a 'wow' factor you get when you first use the app," Scheitlin said. "Our goal is to get past that and make it as educational as we can." Download the appsMeteo AR:For iPhone or iPadFor AndroidMeteo VR:For iPhone or iPadFor Android Writer/contact:Laura Snider, senior science writer

Turbocharging science

CHEYENNE, Wyoming — The National Center for Atmospheric Research (NCAR) is launching operations this month of one of the world's most powerful and energy-efficient supercomputers, providing the nation with a major new tool to advance understanding of the atmospheric and related Earth system sciences.Named "Cheyenne," the 5.34-petaflop system is capable of more than triple the amount of scientific computing performed by the previous NCAR supercomputer, Yellowstone. It also is three times more energy efficient.Scientists across the country will use Cheyenne to study phenomena ranging from wildfires and seismic activity to gusts that generate power at wind farms. Their findings will lay the groundwork for better protecting society from natural disasters, lead to more detailed projections of seasonal and longer-term weather and climate variability and change, and improve weather and water forecasts that are needed by economic sectors from agriculture and energy to transportation and tourism."Cheyenne will help us advance the knowledge needed for saving lives, protecting property, and enabling U.S. businesses to better compete in the global marketplace," said Antonio J. Busalacchi, president of the University Corporation for Atmospheric Research. "This system is turbocharging our science."UCAR manages NCAR on behalf of the National Science Foundation (NSF).Cheyenne currently ranks as the 20th fastest supercomputer in the world and the fastest in the Mountain West, although such rankings change as new and more powerful machines begin operations. It is funded by NSF as well as by the state of Wyoming through an appropriation to the University of Wyoming.Cheyenne is housed in the NCAR-Wyoming Supercomputing Center (NWSC), one of the nation's premier supercomputing facilities for research. Since the NWSC opened in 2012, more than 2,200 scientists from more than 300 universities and federal labs have used its resources."Through our work at the NWSC, we have a better understanding of such important processes as surface and subsurface hydrology, physics of flow in reservoir rock, and weather modification and precipitation stimulation," said William Gern, vice president of research and economic development at the University of Wyoming. "Importantly, we are also introducing Wyoming’s school-age students to the significance and power of computing."The NWSC is located in Cheyenne, and the name of the new system was chosen to honor the support the center has received from the people of that city. The name also commemorates the upcoming 150th anniversary of the city, which was founded in 1867 and named for the American Indian Cheyenne Nation.Contour lines and isosurfaces provide valuable information about turbulence and aerodynamic drag in this visualization of air flow through the blades of a wind turbine, the product of a simulation on the NCAR-Wyoming Supercomputing Center's Yellowstone system. (Image courtesy Dimitri Mavriplis, University of Wyoming.) Increased power, greater efficiencyCheyenne was built by Silicon Graphics International, or SGI (now part of Hewlett Packard Enterprise Co.), with DataDirect Networks (DDN) providing centralized file system and data storage components. Cheyenne is capable of 5.34 quadrillion calculations per second (5.34 petaflops, or floating point operations per second).The new system has a peak computation rate of more than 3 billion calculations per second for every watt of energy consumed. That is three times more energy efficient than the Yellowstone supercomputer, which is also highly efficient.The data storage system for Cheyenne provides an initial capacity of 20 petabytes, expandable to 40 petabytes with the addition of extra drives.  The new DDN system also transfers data at the rate of 220 gigabytes per second, which is more than twice as fast as the previous file system’s rate of 90 gigabytes per second.Cheyenne is the latest in a long and successful history of supercomputers supported by the NSF and NCAR to advance the atmospheric and related sciences.“We’re excited to provide the research community with more supercomputing power,” said Anke Kamrath, interim director of NCAR’s Computational and Information Systems Laboratory, which oversees operations at the NWSC. “Scientists have access to increasingly large amounts of data about our planet. The enhanced capabilities of the NWSC will enable them to tackle problems that used to be out of reach and obtain results at far greater speeds than ever.”More detailed predictionsHigh-performance computers such as Cheyenne allow researchers to run increasingly detailed models that simulate complex events and predict how they might unfold in the future. With more supercomputing power, scientists can capture additional processes, run their models at a higher resolution, and conduct an ensemble of modeling runs that provide a fuller picture of the same time period."Providing next-generation supercomputing is vital to better understanding the Earth system that affects us all, " said NCAR Director James W. Hurrell. "We're delighted that this powerful resource is now available to the nation's scientists, and we're looking forward to new discoveries in climate, weather, space weather, renewable energy, and other critical areas of research."Some of the initial projects on Cheyenne include:Long-range, seasonal to decadal forecasting: Several studies led by George Mason University, the University of Miami, and NCAR aim to improve prediction of weather patterns months to years in advance. Researchers will use Cheyenne's capabilities to generate more comprehensive simulations of finer-scale processes in the ocean, atmosphere, and sea ice. This research will help scientists refine computer models for improved long-term predictions, including how year-to-year changes in Arctic sea ice extent may affect the likelihood of extreme weather events thousands of miles away.Wind energy: Projecting electricity output at a wind farm is extraordinarily challenging as it involves predicting variable gusts and complex wind eddies at the height of turbines, which are hundreds of feet above the sensors used for weather forecasting. University of Wyoming researchers will use Cheyenne to simulate wind conditions on different scales, from across the continent down to the tiny space near a wind turbine blade, as well as the vibrations within an individual turbine itself. In addition, an NCAR-led project will create high-resolution, 3-D simulations of vertical and horizontal drafts to provide more information about winds over complex terrain. This type of research is critical as utilities seek to make wind farms as efficient as possible.Space weather: Scientists are working to better understand solar disturbances that buffet Earth's atmosphere and threaten the operation of satellites, communications, and power grids. New projects led by the University of Delaware and NCAR are using Cheyenne to gain more insight into how solar activity leads to damaging geomagnetic storms. The scientists plan to develop detailed simulations of the emergence of the magnetic field from the subsurface of the Sun into its atmosphere, as well as gain a three-dimensional view of plasma turbulence and magnetic reconnection in space that lead to plasma heating.Extreme weather: One of the leading questions about climate change is how it could affect the frequency and severity of major storms and other types of severe weather. An NCAR-led project will explore how climate interacts with the land surface and hydrology over the United States, and how extreme weather events can be expected to change in the future. It will use advanced modeling approaches at high resolution (down to just a few miles) in ways that can help scientists configure future climate models to better simulate extreme events.Climate engineering: To counter the effects of heat-trapping greenhouse gases, some experts have proposed artificially cooling the planet by injecting sulfates into the stratosphere, which would mimic the effects of a major volcanic eruption. But if society ever tried to engage in such climate engineering, or geoengineering, the results could alter the world's climate in unintended ways. An NCAR-led project is using Cheyenne's computing power to run an ensemble of climate engineering simulations to show how hypothetical sulfate injections could affect regional temperatures and precipitation.Smoke and global climate: A study led by the University of Wyoming will look into emissions from wildfires and how they affect stratocumulus clouds over the southeastern Atlantic Ocean. This research is needed for a better understanding of the global climate system, as stratocumulus clouds, which cover 23 percent of Earth's surface, play a key role in reflecting sunlight back into space. The work will help reveal the extent to which particles emitted during biomass burning influence cloud processes in ways that affect global temperatures.

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Wednesday, February 1, 2017,

 12:00 p.m.-12:30 p.m.,  FL2 1001

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NCAR-based climate model joins seasonal forecasting effort

January 12, 2017 | An NCAR-based computer model known for global climate projections decades into the future recently joined a suite of other world-class models being used to forecast what may lie just a few months ahead.The Community Earth System Model has long been an invaluable tool for scientists investigating how the climate may change in the long term — decades or even centuries into the future. Last summer, CESM became the newest member of the North American Multi-Model Ensemble (NMME), an innovative effort that combines some techniques typically used in weather forecasting with those used in climate modeling to predict temperature and precipitation seasons in advance. The result is a bridge that helps span the gap between two-week forecasts and decades-long projections.The forecasted temperature anomalies (departures from average) over North America made by the entire NMME suite (top) and by CESM (middle). Observed temperature anomalies for the same period (bottom). Click to enlarge. (Images courtesy NOAA.) But NMME also builds another bridge: this one between operational forecasters, who issue the forecasts society depends on, and researchers. Now a collection of nine climate models, the NMME has proven it produces more accurate seasonal forecasts than any one model alone. It was adopted in May by the National Oceanic and Atmospheric Administration (NOAA) as one of the agency's official seasonal forecasting tools."What is so important about NMME is that it's bringing research to bear on operational forecasts," said Ben Kirtman, a professor of atmospheric sciences at the University of Miami who leads the NMME project. "The marriage between real-time prediction and research has fostered new understandings, identified new problems that we hadn't thought about before, and really opened up new lines of research."A new way to start a climate model runWeather models and climate models have a lot of things in common; for one, they both use mathematical equations to represent the physical processes going on in the atmosphere. Weather models, which are concerned with what’s likely to happen in the immediate future, depend on being fed accurate initial conditions to produce good forecasts. Even if a weather model could perfectly mimic how the atmosphere works, it would need to know what the atmosphere actually looks like now — the temperature and pressure at points across the country, for example — to determine what the atmosphere will look like tomorrow.Climate modelers, on the other hand, are often interested in broad changes over many decades, so the exact weather conditions at the beginning of a simulation are usually not as important. In fact, their impact is quickly drowned out by larger-scale trends that unfold over long time periods.In recent years, however, scientists have become interested in whether climate models — which simulate changes in ocean circulation patterns, sea surface temperatures, and other large-scale phenomena that have lingering impacts on weather patterns — could be initialized with accurate starting conditions and then used to make skillful seasonal forecasts.The NMME project is exploring this question. The global climate models that make up NMME project are all being initialized monthly to create multiple forecasts that stretch a year in advance. Along with CESM, those models include the NCAR-based Community Climate System Model, Version 4, which is being initialized by Kirtman's team at the University of Miami. (See a full list of models below.)Taken together, the individual model forecasts reveal information to forecasters about the amount of uncertainty in the seasonal forecast. If individual forecasts vary substantially, the future is less certain. If they agree, forecasters can have more confidence.The forecasted precipitation anomalies (departures from average) over North America made by the entire NMME suite (top) and by CESM (middle). Observed precipitation anomalies for the same period (bottom). Click to enlarge. (Images courtesy NOAA.)A valuable collection of dataCESM's first seasonal forecast as part of NMME, which was issued for July, August, and September 2016, was perhaps the most accurate of any in the ensemble. The forecast — which called for conditions to be warmer and drier than average across most of the United States — was issued after more than a year of work by NCAR scientists Joseph Tribbia and Julie Caron.All of the models in the NMME suite must be calibrated by running "hindcasts." By comparing the model's prediction of a historical season with what actually happened, the scientists can identify if the model is consistently off in some areas. For example, the model might generally predict that seasons will be wetter or cooler than they actually are for certain regions of the country. These tendencies can then be statistically corrected in future forecasts."We ran 10 predictions every month for a 33-year period and ran each prediction out for one year," Tribbia said. "You can learn a lot about how your model performs when you have so many runs."Once CESM was calibrated, it joined the NMME operational suite of models. But the data generated by the rigorous hindcasting process wasn't cast aside once the calibration was finished. Instead, every modeling group has saved not only monthly data, but also high-frequency daily data that are being stored at NCAR.The trove of historical predictions, along with the new predictions being generated in real-time, are an incredible resource for scientists interested in improving the techniques for initializing climate models and exploring what types of things can, and cannot, be predicted in advance."Predictability research can be a challenge. The NMME dataset allows you to check yourself in a robust way," Kirtman said. "If you think you've found a source of predictability in the hindcast mode, you can then try to do it in real time. It's really exciting — and it really holds your feet to the fire."This year, as much as 18.5 terabytes of NMME data were downloaded from NCAR monthly, according to NCAR's Eric Nienhouse, who oversees the data archive.Now that CESM is an active part of NMME, Tribbia and Caron will also be diving into the data."Now the fun begins," Caron said. "We get to start looking at the data to see how we're doing, and what we might change in the future to make our seasonal forecasts better."Models that make up NMME:NCEP CFSv2: National Centers for Environmental Prediction Climate Forecast System Version 2 (NOAA)CMC1 CanCM3: Canadian Meteorological Centre/Canadian Centre for Climate Modeling and AnalysisCMC2 CanCM4: Canadian Meteorological Centre/Canadian Centre for Climate Modeling and AnalysisGFDL FLOR: Geophysical Fluid Dynamics Laboratory Forecast-oriented Low Ocean Resolution (NOAA)GFDL CM2.1: Geophysical Fluid Dynamics Laboratory Coupled Climate Model Version 2.1 (NOAA)NCAR CCSM4: National Center for Atmospheric Research Community Climate System Model Version 4NASA GEOS5: NASA Goddard Earth Observing System Model Version 5NCAR CESM: National Center for Atmospheric Research Community Earth System ModelIMME: National Centers for Environmental Prediction International Multi-Model Ensemble (NOAA)Writer/contact:Laura Snider, Senior Science Writer  

Top stories of 2016

Zika risk estimated for U.S. citiesA multidisciplinary team of scientists studied the possible timing and location of Zika virus risk in the United States. A powerful new supercomputerThe new system for the NCAR-Wyoming Supercomputing Center is capable of more than 2.5 times the amount of scientific computing performed by its predecessor. SOARS turns 20The SOARS Program has been boosting diversity in Earth system science for two decades.Extreme downpours could quintuple At century's end, the number of summertime storms that produce extreme downpours could increase by more than 400 percent across parts of the United States.New NCAR climate exhibitThe exhibits at NCAR's Mesa Lab in Boulder provide the public with an engaging and scientifically accurate forum to learn about climate. Solar model pulls order out of chaosPushing a solar model to the highest resolution ever attempted brings order back to the Sun's magnetic tangle.Investigating air quality in KoreaNCAR scientists traveled to South Korea as part of a field campaign to investigate the region's air quality.U.S. water forecasts tap NCAR modelNOAA is using an advanced NCAR prediction system as the core of the new National Water Model.UCAR partners with AmazonUnidata has partnered with Amazon Web Services to make NEXRAD data from NOAA available in the cloud in near real time. Flights investigate Southern Ocean  The ORCAS field campaign is helping scientists better understand just how much carbon dioxide the icy waters are able to lock away.  Ocean temps predict U.S. heat wavesThe formation of a distinct pattern of sea surface temperatures in the Pacific Ocean can predict an increased chance of summertime heat waves up to 50 days in advance.3D-printed weather stations Scientists successfully installed the first wave of low-cost weather stations in Zambia with 3D-printed parts. Visualization of the year  Researchers at NCAR and the University of Miami are seeking clues about what really goes on inside a tornado using highly detailed computer simulations of wind fields.

NCAR & UCAR Scientists Highlight Advances in Weather, Water & Climate Research at AGU 2016

SAN FRANCISCO – Scientists with the National Center for Atmospheric Research (NCAR) and the University Corporation for Atmospheric Research (UCAR) will make dozens of presentations at the fall meeting of the American Geophysical Union (AGU) during the week of December 12–16.Media Q&AThe Path Forward from Paris, One Year LaterUCAR President Antonio J. Busalacchi, AGU President Margaret Leinen (Scripps Institution of Oceanography), and Carlos Nobre (Brazilian National Institute of Science & Technology for Climate Change) - related to Union Session U23ATuesday, December 13, 4 p.m. - Moscone West 3000 (Press Conference Room)Note: The Moscone West Q&A follows Union Session U23A with these participants in Moscone North Hall E from 1:40-3:40 p.m.Selected Talks MONDAY | TUESDAY | WEDNESDAY | THURSDAY | FRIDAYFull calendar, special events& exhibitsNCAR & UCAR at AGU 2016>@AtmosNewsLive | #NCARscience MONDAY, December 12Getting Space Weather Data and More From 'Noise' in GPS Signals: The COSMIC MissionsWilliam Schreiner, UCARSA11A-04: Satellite Constellations for Space Weather and Ionospheric Studies: Overview of the COSMIC and COSMIC-2 Missions8:45-9:00 a.m., Moscone West 2016Climate Change, Lyme, Zika, and Other Vector-Borne DiseasesAndrew Monaghan, NCARGC12A-02: Assessment of Climate Change and Vector-Borne Diseases in the United States10:35-10:50 a.m., Moscone West 2020Extreme Rainfall Could Increase Fivefold Across Parts of the U.S. Later This CenturyAndreas Prein, NCARGC13H-04: The Future Intensification of Hourly Precipitation Extremes2:25-2:40 p.m., Moscone West 3003Building Resilient Cities and Ecosystems: Food, Energy, and Water SecurityPatricia Romero-Lankao, NCARU13A-05: Urbanization, Extreme Climate Hazards, and Food/Energy/Water Security2:54-3:12 p.m., Moscone West 2022/2024TUESDAY, December 13Carbon Dioxide's Opposite Effects in the Upper AtmosphereStan Solomon, NCARSA21C-03: Climate Change in the Upper Atmosphere8:30-8:45 a.m., Moscone West 20163D-Printed Weather Stations Aid Forecasting in Developing NationsPaul Kucera, NCARH23F-1637: Development of Innovative Technology to Expand Precipitation Observations in Satellite Precipitation Validation in Under-developed Data-Sparse Regions1:40-6:00 p.m., Moscone South - Poster HallScenarios for Reaching the Paris Agreement TargetsBen Sanderson, NCARGC24D-02: Pathways to 1.5 Degrees: New GCM Simulations for Scenarios Which Meet the Paris Temperature Targets4:15-4:27 p.m., Moscone West 3003WEDNESDAY, December 14Seeing Into Tornadoes and Hurricanes with High-Resolution SimulationsGeorge Bryan, NCARIN31F-07: Insights into Tornadoes, Hurricanes from High-Resolution Simulations9:30-9:45 a.m., Moscone West 2000A Weather Resiliency Toolbox for Communities and BusinessesJames Done, NCARPA32A-03: Tools in Support of Planning for Weather and Climate Extremes10:58-11:11 a.m., Moscone South 304Exploring Unanswered Questions in the Evolution of Prehistoric Climate - The Emiliani LectureBette Otto-Bliesner, NCARPP32A-01: Resolving Some Puzzles of Climate Evolution Since the Last Glacial Maximum: A Melding of Paleoclimate Modeling and Data11:20 a.m.-12:20 p.m., Moscone West 2022/2024THURSDAY, December 15Novel Uses of Climate Information for Water Utility Planners David Yates, NCAR U42A-02: The Novel Use of Climate Information in Water Utility Planning 10:40-10:58 a.m., Moscone South 102What's In Wildfire Smoke? Jerome Barre, NCAR A42D-04: Quantifying Fire Emissions and Associated Aerosol Species Using Assimilation of Satellite Carbon Monoxide Retrievals 11:05-11:20 a.m., Moscone West 3004 <FRIDAY, December 16What's Causing Errors in Hurricane & Tropical Storm Forecasts? Chris Davis, NCAR A54F-06: On the Origin of Large Tropical Cyclone Track Errors 5:15-5:30 p.m., Moscone West 3012  Full calendar, special events & exhibit infoNCAR & UCAR at AGU 2016>@AtmosNewsLive | #NCARscience | #AGU16

Two NCAR scientists honored by American Geophysical Union

BOULDER, Colo. — Martyn Clark, senior scientist at the National Center for Atmospheric Research (NCAR), will be honored next week as a Fellow of the American Geophysical Union (AGU) for his exceptional contribution to Earth science.Clark is an expert in the numerical modeling and prediction of hydrologic processes. His current research includes developing new modeling methods to improve streamflow forecasts and better understand climate change impacts on regional water resources. Clark, who grew up in Christchurch, New Zealand, has authored or co-authored 135 journal articles since receiving his Ph.D. from the University of Colorado in 1998.NCAR Senior Scientist Martyn Clark (©UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.)"This well-deserved honor reflects Martyn's eminent work in the increasingly critical area of water-resource prediction and management," said NCAR Director James W. Hurrell.Clark said he was delighted to see NCAR's hydrologic modeling recognized. "Hydrology is beginning to play a much stronger role in addressing important interdisciplinary science questions about Earth System change, such as how changes in the terrestrial water cycle affect biological productivity and how groundwater can buffer water stress in ecosystems and human societies. It's exciting to advance modeling capabilities in these areas."NCAR Senior Scientist Bette Otto-Bliesner. (©UCAR. Photo by Carlye Calvin. This image is freely available for media & nonprofit use.)Clark is among 60 individuals from eight countries recognized as Fellows this year; only one in one thousand AGU members receive this recognition in any given year. Nearly 40 percent of this year's fellows are from the 110 member colleges and universities of the University Corporation for Atmospheric Research (UCAR), which manages NCAR. This year's class will be honored next Wednesday at the 2016 AGU Fall Meeting in San Francisco.NCAR Senior Scientist Bette Otto-Bliesner, who was named an AGU Fellow last year, is being honored by her peers in the Paleoceanography and Paleoclimatology Focus Group and Ocean Sciences Section by being asked to give the 2016 Emiliani Lecture. She will give the lecture next Wednesday at the AGU Fall Meeting on the topic of "Resolving Some Puzzles of Climate Evolution Since the Last Glacial Maximum: A Melding of Paleoclimate Modeling and Data."The AGU, dedicated to advancing Earth and space sciences for the benefit of society, is a not-for-profit, professional organization representing 60,000 members in more than 140 countries. 

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