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North American storm clusters could produce 80 percent more rain

BOULDER, Colo. — Major clusters of summertime thunderstorms in North America will grow larger, more intense, and more frequent later this century in a changing climate, unleashing far more rain and posing a greater threat of flooding across wide areas, new research concludes.The study, by scientists at the National Center for Atmospheric Research (NCAR), builds on previous work showing that storms are becoming more intense as the atmosphere is warming. In addition to higher rainfall rates, the new research finds that the volume of rainfall from damaging storms known as mesoscale convective systems (MCSs) will increase by as much as 80 percent across the continent by the end of this century, deluging entire metropolitan areas or sizable portions of states."The combination of more intense rainfall and the spreading of heavy rainfall over larger areas means that we will face a higher flood risk than previously predicted," said NCAR scientist Andreas Prein, the study's lead author. "If a whole catchment area gets hammered by high rain rates, that creates a much more serious situation than a thunderstorm dropping intense rain over parts of the catchment.""This implies that the flood guidelines which are used in planning and building infrastructure are probably too conservative," he added.The research team drew on extensive computer modeling that realistically simulates MCSs and thunderstorms across North America to examine what will happen if emissions of greenhouse gases continue unabated.The study will be published Nov. 20 in the journal Nature Climate Change. It was funded by the National Science Foundation, which is NCAR's sponsor, and by the U.S. Army Corps of Engineers. Hourly rain rate averages for the 40 most extreme summertime mesoscale convective systems (MCSs) in the current (left) and future climate of the mid-Atlantic region. New research shows that MSCs will generate substantially higher maximum rain rates over larger areas by the end of the century if society continues a "business as usual" approach of emitting greenhouse gases . (©UCAR, Image by Andreas Prein, NCAR. This image is freely available for media & nonprofit use.)A warning signalThunderstorms and other heavy rainfall events are estimated to cause more than $20 billion of economic losses annually in the United States, the study notes. Particularly damaging, and often deadly, are MSCs: clusters of thunderstorms that can extend for many dozens of miles and last for hours, producing flash floods, debris flows, landslides, high winds, and/or hail. The persistent storms over Houston in the wake of Hurricane Harvey were an example of an unusually powerful and long-lived MCS.Storms have become more intense in recent decades, and a number of scientific studies have shown that this trend is likely to continue as temperatures continue to warm. The reason, in large part, is that the atmosphere can hold more water as it gets warmer, thereby generating heavier rain.A study by Prein and co-authors last year used high-resolution computer simulations of current and future weather, finding that the number of summertime storms that produce extreme downpours could increase by five times across parts of the United States by the end of the century. In the new study, Prein and his co-authors focused on MCSs, which are responsible for much of the major summertime flooding east of the Continental Divide. They investigated not only how their rainfall intensity will change in future climates, but also how their size, movement, and rainfall volume may evolve.Analyzing the same dataset of computer simulations and applying a special storm-tracking algorithm, they found that the number of severe MCSs in North America more than tripled by the end of the century. Moreover, maximum rainfall rates became 15 to 40 percent heavier, and intense rainfall reached farther from the storm's center. As a result, severe MCSs increased throughout North America, particularly in the northeastern and mid-Atlantic states, as well as parts of Canada, where they are currently uncommon.The research team also looked at the potential effect of particularly powerful MCSs on the densely populated Eastern Seaboard. They found, for example, that at the end of the century, intense MCSs over an area the size of New York City could drop 60 percent more rain than a severe present-day system. That amount is equivalent to adding six times the annual discharge of the Hudson River on top of a current extreme MCS in that area."This is a warning signal that says the floods of the future are likely to be much greater than what our current infrastructure is designed for," Prein said. "If you have a slow-moving storm system that aligns over a densely populated area, the result can be devastating, as could be seen in the impact of Hurricane Harvey on Houston."This satellite image loop shows an MCS developing over West Virginia on June 23, 2016. The resulting floods caused widespread flooding, killing more than 20 people.  MCSs are responsible for much of the major flooding east of the Continental Divide during warm weather months. (Image by NOAA National Weather Service, Aviation Weather Center.) Intensive modelingAdvances in computer modeling and more powerful supercomputing facilities are enabling climate scientists to begin examining the potential influence of a changing climate on convective storms such as thunderstorms, building on previous studies that looked more generally at regional precipitation trends.For the new study, Prein and his co-authors turned to a dataset created by running the NCAR-based Weather and Research Forecasting (WRF) model over North America at a resolution of 4 kilometers (about 2.5 miles). That is sufficiently fine-scale resolution to simulate MCSs. The intensive modeling, by NCAR scientists and study co-authors Roy Rasmussen, Changhai Liu, and Kyoko Ikeda, required a year to run on the Yellowstone system at the NCAR-Wyoming Supercomputing Center.The team used an algorithm developed at NCAR to identify and track simulated MCSs. They compared simulations of the storms at the beginning of the century, from 2000 to 2013, with observations of actual MCSs during the same period and showed that the modeled storms are statistically identical to real MCSs.The scientists then used the dataset and algorithm to examine how MCSs may change by the end of the century in a climate that is approximately 5 degrees Celsius (9 degrees Fahrenheit) warmer than in the pre-industrial era — the temperature increase expected if greenhouse gas emissions continue unabated.About the paperTitle: Increased rainfall volume from future convective storms in the USAuthors: Andreas F Prein, Changhai Liu, Kyoko Ikeda, Stanley B Trier, Roy M Rasmussen, Greg J Holland, Martyn P ClarkJournal: Nature Climate Change  

New climate forecasts for watersheds - and the water sector

Nov. 10, 2017 | Water managers and streamflow forecasters can now access bi-weekly, monthly, and seasonal precipitation and temperature forecasts that are broken down by individual watersheds, thanks to a research partnership between the National Center for Atmospheric Research (NCAR) and the University of Colorado Boulder (CU Boulder). The project is sponsored by the National Oceanic and Atmospheric Administration (NOAA) through the Modeling, Applications, Predictions, and Projections program.Operational climate forecasts for subseasonal to seasonal time scales are currently provided by the NOAA Climate Prediction Center and other sources. The forecasts usually take the form of national contour maps (example) and gridded datasets at a relatively coarse geographic resolution. Some forecast products are broken down further, based on state boundaries or on climate divisions, which average two per state; others are summarized for major cities. But river forecasters and water managers grapple with climate variability and trends in the particular watersheds within their service areas, which do not align directly with the boundaries of existing forecast areas. A forecast that directly describes predicted conditions inside an individual watershed would be extremely valuable to these users for making decisions in their management areas, such as how much water to release or store in critical reservoirs and when.To bridge this gap, the NCAR–CU Boulder research team has developed a new prototype prediction system that maps climate forecasts to watershed boundaries over the contiguous United States in real time. The system is currently running at NCAR, with real-time forecasts and analyses available on a demonstration website."We are trying to improve the accessibility and relevance of climate predictions for streamflow forecasting groups and water managers," said NCAR scientist Andy Wood, who co-leads the project. "We can’t solve all the scientific challenges of climate prediction, but we can make it easier for a person thinking about climate and water in a river basin — such as the Gunnison, or the Yakima, or the Potomac — to find and download operational climate information that has been tailored to that basin’s observed variability."The project is funded by NOAA, and the scientists plan to hand off successful components of the system for experimental operational evaluation within the NOAA National Weather Service.  Collaborators include scientists from the NOAA Climate Prediction Center and partners from the major federal water agencies: the U.S. Army Corps of Engineers and the Bureau of Reclamation.This screenshot of the S2S Climate Outlooks for Watersheds website shows forecasted temperature anomalies for watersheds across the contiguous United States. As users scroll across different watersheds, they get more precise information. In this screenshot from early November 2017, the forecast is showing that, over the next one to two weeks, the Colorado Headwaters watershed is expected to be 1.2 degrees warmer than normal. Visit the website to learn more. (©UCAR. This image is freely available for media & nonprofit use.)  Beyond the standard weather forecastPrecipitation and temperature forecasts that extend beyond the typical 7- to 10-day window can be useful to water managers making a number of important decisions about how to best regulate supplies. For instance, during a wet water year, when snowpack is high and reservoirs are more full than usual, the relative warmth or coolness of the coming spring can affect how quickly the snow melts. Good spring season forecasts allow water managers to plan in advance for how to best manage the resulting runoff.For water systems in drought, such as California's during 2012–2015, early outlooks on whether the winter rainy season will help alleviate the drought or exacerbate it can help water utilities strategize ways of meeting the year’s water demands. Historically, making these kinds of longer-term predictions accurately has been highly challenging. But in recent years, scientists have improved their skill at subseasonal and seasonal climate prediction. NOAA’s National Centers for Environmental Prediction plays a key role, both running an in-house modeling system — the Climate Forecast System, version 2 (CFSv2) — and leading an effort called the North American Multi-Model Ensemble (NMME). These model-based forecasts help inform the NOAA official climate forecasts, which also include other tools and expert judgment. NMME combines forecasts from seven different climate models based in the U.S. and Canada to form a super-ensemble of climate predictions that extend up to 10 months into the future. The combination of the different forecasts is often more accurate than the forecast from any single model. Temperature forecasts, in particular, from the combined system are notably more accurate than they were 10 years ago, Wood said, partly due to their representation of observed warming trends. Even with these new tools, however, predicting seasonal precipitation beyond the first month continues to be a major challenge. The NCAR–CU Boulder project makes use of both the CFSv2 and NMME forecasts. It generates predictions for bi-weekly periods (weeks 1-2, 2-3, and 3-4) from CFSv2 that are updated daily and longer-term forecasts derived from the NMME (months 1, 2, 3, and season 1) that are updated monthly. The scientists currently map these forecasts to 202 major watersheds in the contiguous U.S.Analyzing forecast skillThe resulting watershed-specific forecasts are available in real-time on the project's interactive website, which also provides information about their accuracy and reliability."It's important for users to be able to check on the quality of the forecasts," said Sarah Baker, a doctoral student in the Civil, Environmental, and Architectural Engineering Department at CU Boulder. "We're able to use hindcasts, which are long records of past forecasts, to analyze and describe the skill of the current forecasts. Baker, who also works for the Bureau of Reclamation, has been building the prototype system under the supervision of Wood and her academic adviser, CU Professor Balaji Rajagopalan. The researchers are also using analyses of forecast accuracy and reliability to begin correcting for systematic biases — such as consistently over-predicting springtime rains in one watershed or under-predicting summertime heat in another — in the forecasts.The project team has presented the project at a number of water-oriented meetings in the western U.S. Water managers, operators, and researchers from agencies such as the Bureau of Reclamation and utilities such as the Southern Nevada Water Authority, which manages water for Las Vegas, have expressed interest in the new forecast products."This project has great potential to provide climate outlook information that is more relevant for hydrologists and the water sector. It will be critical to connect with stakeholders or possible users of the forecasts so that their needs can continue to help shape this type of information product," said NOAA’s Andrea Ray. Ray leads an effort funded by NIDIS, the National Integrated Drought Information System, to identify tools and information such as this for a NOAA online Water Resources Monitor and Outlook that would also help connect stakeholders to climate and water information.In the coming year, the research team will implement statistical post-processing methods to improve the accuracy of the forecasts. They will also investigate the prediction of extreme climate events at the watershed scale. ContactAndy Wood, NCAR Research Applications LaboratoryWebsitehttp://hydro.rap.ucar.edu/s2sCollaboratorsCU BoulderNCARNOAAU.S. Army Corps of EngineersBureau of Reclamation FunderNOAA's Modeling, Applications, Predictions and Projections Climate Testbed program

NCAR scientists work to improve sharing, storing of hydrology data

NCAR scientists Martyn Clark and David Gochis are part of an effort funded by the National Science Foundation to improve Hydroshare. The project is being led by Utah State University, a UCAR member institution. The following is an excerpt from a USU news release.Sept. 29, 2017 | Utah State University hydrologists are revolutionizing the way scientific data is stored and shared among scientists around the globe.USU’s David Tarboton will lead a $4 million National Science Foundation-funded collaborative effort aimed at improving HydroShare – an online database system that simplifies the storage and sharing of hydrological data and models.“Hydroshare is an online system for the scientific community that allows us to easily and freely share products from our research,” said Tarboton, a professor of civil and environmental engineering and a leading hydrology expert who helped create HydroShare. “We’re interested in sharing not just the scientific publication summarizing a study, but also the data and models used to create that study.”Tarboton says sharing scientific data helps researchers collaborate and improves the quality of data and scientific knowledge. Enhancing HydroShare’s capabilities, he added, will help hydrologists and a broad community of earth-science researchers transform data sharing techniques and accelerate the pace of discovery. Improvements to HydroShare include enhancements to data sharing tools, and new features that enable its 1,000-plus users to develop their own unique apps to access HydroShare resources.Read the full news release.

NCAR|UCAR hurricane experts available to explain storm behavior, potential impacts

BOULDER, Colo. — As Hurricane Harvey takes aim at Texas, scientists at the National Center for Atmospheric Research (NCAR) and its managing organization, the University Corporation for Atmospheric Research (UCAR), are closely watching the storm and testing high-resolution computer models.Hurricane experts are available to explain issues such as:How we can better predict the possible impacts of hurricanes, including wind damage, flooding, and subsequent spread of disease-bearing mosquitoes;How people respond to hurricane forecast and warning messages and how risk communication can be improvedWhether climate change is affecting hurricanes and what we can expect in the future;The importance of improving weather models to safeguard life and property.Antonio Busalacchi, UCAR president (please contact David Hosansky for interview requests)An expert on ocean-atmosphere interactions, Busalacchi has testified before Congress on the importance of improving the nation's weather forecasting capabilities to better protect life and property, bolster the economy, and strengthen national security. He has firsthand experience with storms along the Gulf Coast as a part-time New Orleans resident, and he is a member of the Gulf Research Program Advisory Board of the National Academy of Sciences.Christopher Davis, director, NCAR Mesoscale and Microscale Meteorology Laboratory, cdavis@ucar.edu, 303-497-8990Davis studies the weather systems that lead to hurricanes and other heavy rainfall events. His expertise includes hurricane prediction and how computer models can be improved to better forecast storms. His NCAR weather lab is running experimental computer simulations of Hurricane Harvey.James Done, NCAR scientist, done@ucar.edu, 303-497-8209Done led development of the innovative Cyclone Damage Potential (CDP) index, which quantifies a hurricane's ability to cause destruction, using a scale of 1 to 10. It can also be used to examine the damage potential for cyclones in the future as the climate warms.David Gochis, NCAR scientist, gochis@ucar.edu, 303-497-2809An expert in hydrometeorology, Gochis studies the causes of floods and how to better predict them. He helped develop pioneering software that is at the core of the National Water Model. The National Oceanic and Atmospheric Administration Office of Water Prediction uses this model to provide a continuous picture of all the waterways in the contiguous United States and alert officials to potentially dangerous floods.Matthew Kelsch, UCAR hydrometeorologist, kelsch@ucar.edu, 303-497-8309Kelsch has studied some of the biggest U.S. flood events connected to hurricanes and tropical storms. He trains scientists and forecasters from around the world on emerging hydrology and weather topics.Rebecca Morse, NCAR scientist, morss@ucar.edu, 303-497-8172Morss studies the predictability of hurricane-related hazards, including storm surge and inland flooding, and hurricane and flood risk communication and evauation decision making.Kevin Trenberth, NCAR senior scientist, trenbert@ucar.edu, 303-497-1318Trenberth is an expert on the global climate system. He has been in the forefront of scientists examining the potential influence of climate change on the intensity of tropical storms and hurricanes and the increased widespread flooding that they cause.Jeff Weber, UCAR meteorologist, jweber@ucar.edu, 303-497-8676As an expert on hurricanes and severe weather in general, Weber closely monitors the behavior of individual storms and the larger atmospheric and oceanic conditions that influence them.

The Master Plan of the Shagaya Renewable Energy Park in Kuwait - Friday

Note new date: Friday, August 18

The Master Plan of the Shagaya Renewable Energy Park in Kuwait
Yousuf Al-Abdulla | Kuwait Institute for Scientific Research, Kuwait City, Kuwait

A Beginners Introduction to the Analog Ensemble Technique

A Beginners Introduction to the Analog Ensemble Technique

LAURA CLEMENTE-HARDING | THE PENNSYLVANIA STATE UNIVERSITY, UNIVERSITY PARK, PA, AND THE ENGINEER RESEARCH AND DEVELOPMENT CENTER, ALEXANDRIA, VA

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

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