Search Results

You are looking at 21 - 30 of 46 items for

  • Author or Editor: David Williams x
  • Refine by Access: All Content x
Clear All Modify Search
Jason Ching, Michael Brown, Steven Burian, Fei Chen, Ron Cionco, Adel Hanna, Torrin Hultgren, Timothy McPherson, David Sailor, Haider Taha, and David Williams

Based on the need for advanced treatments of high-resolution urban morphological features (e.g., buildings and trees) in meteorological, dispersion, air quality, and human-exposure modeling systems for future urban applications, a new project was launched called the National Urban Database and Access Portal Tool (NUDAPT). NUDAPT is sponsored by the U.S. Environmental Protection Agency (U.S. EPA) and involves collaborations and contributions from many groups, including federal and state agencies, and from private and academic institutions here and in other countries. It is designed to produce and provide gridded fields of urban canopy parameters for various new and advanced descriptions of model physics to improve urban simulations, given the availability of new high-resolution data of buildings, vegetation, and land use. Additional information, including gridded anthropogenic heating (AH) and population data, is incorporated to further improve urban simulations and to encourage and facilitate decision support and application linkages to human exposure models. An important core-design feature is the utilization of Web portal technology to enable NUDAPT to be a “community” based system. This Web-based portal technology will facilitate the customizing of data handling and retrievals (www.nudapt.org). This article provides an overview of NUDAPT and several example applications.

Full access
James M. Kurdzo, Earle R. Williams, David J. Smalley, Betty J. Bennett, David C. Patterson, Mark S. Veillette, and Michael F. Donovan

Abstract

Chaff is a radar countermeasure typically used by military branches in training exercises around the United States. Chaff within view of the S-band WSR-88D beam can appear prominently on radar users’ displays. Knowledge of chaff characteristics is useful for radar users to discriminate between chaff and weather echoes and for automated algorithms to do the same. The WSR-88D network provides dual-polarimetric capabilities across the United States, leading to the collection of a large database of chaff cases. This database is analyzed to determine the characteristics of chaff in terms of the reflectivity factor and polarimetric variables on large scales. Particular focus is given to the dynamics of differential reflectivity Z DR in chaff and its dependence on height. In contrast to radar observations of chaff for a single event, this study is able to reveal a repeatable and new pattern of radar chaff observations. A discussion about the observed characteristics is presented, and hypotheses for the observed Z DR dynamics are put forth.

Full access
Amy McGovern, Kimberly L. Elmore, David John Gagne II, Sue Ellen Haupt, Christopher D. Karstens, Ryan Lagerquist, Travis Smith, and John K. Williams

Abstract

High-impact weather events, such as severe thunderstorms, tornadoes, and hurricanes, cause significant disruptions to infrastructure, property loss, and even fatalities. High-impact events can also positively impact society, such as the impact on savings through renewable energy. Prediction of these events has improved substantially with greater observational capabilities, increased computing power, and better model physics, but there is still significant room for improvement. Artificial intelligence (AI) and data science technologies, specifically machine learning and data mining, bridge the gap between numerical model prediction and real-time guidance by improving accuracy. AI techniques also extract otherwise unavailable information from forecast models by fusing model output with observations to provide additional decision support for forecasters and users. In this work, we demonstrate that applying AI techniques along with a physical understanding of the environment can significantly improve the prediction skill for multiple types of high-impact weather. The AI approach is also a contribution to the growing field of computational sustainability. The authors specifically discuss the prediction of storm duration, severe wind, severe hail, precipitation classification, forecasting for renewable energy, and aviation turbulence. They also discuss how AI techniques can process “big data,” provide insights into high-impact weather phenomena, and improve our understanding of high-impact weather.

Open access
Xiaoyan Jiang, Sara A. Rauscher, Todd D. Ringler, David M. Lawrence, A. Park Williams, Craig D. Allen, Allison L. Steiner, D. Michael Cai, and Nate G. McDowell

Abstract

Rapid and broad-scale forest mortality associated with recent droughts, rising temperature, and insect outbreaks has been observed over western North America (NA). Climate models project additional future warming and increasing drought and water stress for this region. To assess future potential changes in vegetation distributions in western NA, the Community Earth System Model (CESM) coupled with its Dynamic Global Vegetation Model (DGVM) was used under the future A2 emissions scenario. To better span uncertainties in future climate, eight sea surface temperature (SST) projections provided by phase 3 of the Coupled Model Intercomparison Project (CMIP3) were employed as boundary conditions. There is a broad consensus among the simulations, despite differences in the simulated climate trajectories across the ensemble, that about half of the needleleaf evergreen tree coverage (from 24% to 11%) will disappear, coincident with a 14% (from 11% to 25%) increase in shrubs and grasses by the end of the twenty-first century in western NA, with most of the change occurring over the latter half of the twenty-first century. The net impact is a ~6 GtC or about 50% decrease in projected ecosystem carbon storage in this region. The findings suggest a potential for a widespread shift from tree-dominated landscapes to shrub and grass-dominated landscapes in western NA because of future warming and consequent increases in water deficits. These results highlight the need for improved process-based understanding of vegetation dynamics, particularly including mortality and the subsequent incorporation of these mechanisms into earth system models to better quantify the vulnerability of western NA forests under climate change.

Full access
Jeffrey Beck, John Brown, Jimy Dudhia, David Gill, Tracy Hertneky, Joseph Klemp, Wei Wang, Christopher Williams, Ming Hu, Eric James, Jaymes Kenyon, Tanya Smirnova, and Jung-Hoon Kim

Abstract

A new hybrid, sigma-pressure vertical coordinate was recently added to the Weather Research and Forecasting (WRF) Model in an effort to reduce numerical noise in the model equations near complex terrain. Testing of this hybrid, terrain-following coordinate was undertaken in the WRF-based Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) models to assess impacts on retrospective and real-time simulations. Initial cold-start simulations indicated that the majority of differences between the hybrid and traditional sigma coordinate were confined to regions downstream of mountainous terrain and focused in the upper levels. Week-long retrospective simulations generally resulted in small improvements for the RAP, and a neutral impact in the HRRR when the hybrid coordinate was used. However, one possibility is that the inclusion of data assimilation in the experiments may have minimized differences between the vertical coordinates. Finally, analysis of turbulence forecasts with the new hybrid coordinate indicate a significant reduction in spurious vertical motion over the full length of the Rocky Mountains. Overall, the results indicate a potential to improve forecast metrics through implementation of the hybrid coordinate, particularly at upper levels, and downstream of complex terrain.

Free access
Deborah A. McGrath, Jonathan P. Evans, C. Ken Smith, David G. Haskell, Neil W. Pelkey, Robert R. Gottfried, Charles D. Brockett, Matthew D. Lane, and E. Douglass Williams

Abstract

Over the past two decades, forests in the southeastern United States have undergone dramatic changes as the result of urban sprawl and conversion to intensively managed pine plantations. The Cumberland Plateau, an important ecoregion in the southeastern United States, contains some of the largest remaining tracts of privately owned, native hardwood forest in North America. These ecologically important forests have been undergoing increasingly rapid rates of hardwood-to-pine conversion, much of which has gone undetected by large-scale statewide inventories. Forest conversion in Tennessee's southern Cumberland Plateau provides a case study highlighting the need for interdisciplinary and spatially explicit assessments of the impact and drivers of land-use change at smaller scales. Aerial and satellite imagery were used to create computer-generated maps of land use and forest cover for a 243 000 ha study area within a seven-county region of the southern Cumberland Plateau in Tennessee to track and document patterns of forest change and conversion between 1981 and 2000. The ecological impact of forest harvesting and hardwood-to-pine conversion was evaluated by (i) monitoring aquatic macroinvertebrate diversity, (ii) tracking breeding-bird populations, and (iii) comparing calcium (Ca) stores and cycling in a chronosequence of hardwood to first- and second-rotation loblolly pine (Pinus taeda) plantations. It was found that 14% of native forest cover had been lost since 1981, 74% of which resulted from hardwood-to-pine conversion. It was also found that the rate of conversion to pine doubled from 1997 to 2000. Water quality in streams, as measured by the abundance of critical macroinvertebrates, was significantly lower in recently logged sites than in undisturbed native forest. Surveys of breeding-bird populations showed that pine plantations of several age classes had lower species richness and evenness than did native oak–hickory forests. Despite similar soil concentrations of Ca in native hardwood, mature first-rotation, and early second-rotation pine, changes were found in aboveground Ca storage that suggest substantial system Ca losses that may limit productivity of second-rotation pine or regrowth of oak–hickory forest. As part of the ongoing research on the socioeconomic drivers of land-use change on the Cumberland Plateau, it was found that Tennessee's major forest conservation incentive program only delays forest conversion for a few years while subsidizing landowners who would not have converted their land in the absence of the program. These results demonstrate the need for more detailed and multidisciplinary research conducted at smaller scales so as to enhance the understanding of the impact and drivers of land-use change at larger scales.

Full access
Stephen D. Eckermann, Dave Broutman, Jun Ma, James D. Doyle, Pierre-Dominique Pautet, Michael J. Taylor, Katrina Bossert, Bifford P. Williams, David C. Fritts, and Ronald B. Smith

Abstract

On 14 July 2014 during the Deep Propagating Gravity Wave Experiment (DEEPWAVE), aircraft remote sensing instruments detected large-amplitude gravity wave oscillations within mesospheric airglow and sodium layers at altitudes z ~ 78–83 km downstream of the Auckland Islands, located ~1000 km south of Christchurch, New Zealand. A high-altitude reanalysis and a three-dimensional Fourier gravity wave model are used to investigate the dynamics of this event. At 0700 UTC when the first observations were made, surface flow across the islands’ terrain generated linear three-dimensional wave fields that propagated rapidly to z ~ 78 km, where intense breaking occurred in a narrow layer beneath a zero-wind region at z ~ 83 km. In the following hours, the altitude of weak winds descended under the influence of a large-amplitude migrating semidiurnal tide, leading to intense breaking of these wave fields in subsequent observations starting at 1000 UTC. The linear Fourier model constrained by upstream reanalysis reproduces the salient aspects of observed wave fields, including horizontal wavelengths, phase orientations, temperature and vertical displacement amplitudes, heights and locations of incipient wave breaking, and momentum fluxes. Wave breaking has huge effects on local circulations, with inferred layer-averaged westward flow accelerations of ~350 m s−1 h−1 and dynamical heating rates of ~8 K h−1, supporting recent speculation of important impacts of orographic gravity waves from subantarctic islands on the mean circulation and climate of the middle atmosphere during austral winter.

Full access
Russell S. Vose, Derek Arndt, Viva F. Banzon, David R. Easterling, Byron Gleason, Boyin Huang, Ed Kearns, Jay H. Lawrimore, Matthew J. Menne, Thomas C. Peterson, Richard W. Reynolds, Thomas M. Smith, Claude N. Williams Jr., and David B. Wuertz

This paper describes the new release of the Merged Land–Ocean Surface Temperature analysis (MLOST version 3.5), which is used in operational monitoring and climate assessment activities by the NOAA National Climatic Data Center. The primary motivation for the latest version is the inclusion of a new land dataset that has several major improvements, including a more elaborate approach for addressing changes in station location, instrumentation, and siting conditions. The new version is broadly consistent with previous global analyses, exhibiting a trend of 0.076°C decade−1 since 1901, 0.162°C decade−1 since 1979, and widespread warming in both time periods. In general, the new release exhibits only modest differences with its predecessor, the most obvious being very slightly more warming at the global scale (0.004°C decade−1 since 1901) and slightly different trend patterns over the terrestrial surface.

Full access
David W. Stahle, Edward R. Cook, Dorian J. Burnette, Max C. A. Torbenson, Ian M. Howard, Daniel Griffin, Jose Villanueva Diaz, Benjamin I. Cook, A. Park Williams, Emma Watson, David J. Sauchyn, Neil Pederson, Connie A. Woodhouse, Gregory T. Pederson, David Meko, Bethany Coulthard, and Christopher J. Crawford

Abstract

Cool- and warm-season precipitation totals have been reconstructed on a gridded basis for North America using 439 tree-ring chronologies correlated with December–April totals and 547 different chronologies correlated with May–July totals. These discrete seasonal chronologies are not significantly correlated with the alternate season; the December–April reconstructions are skillful over most of the southern and western United States and north-central Mexico, and the May–July estimates have skill over most of the United States, southwestern Canada, and northeastern Mexico. Both the strong continent-wide El Niño–Southern Oscillation (ENSO) signal embedded in the cool-season reconstructions and the Arctic Oscillation signal registered by the warm-season estimates faithfully reproduce the sign, intensity, and spatial patterns of these ocean–atmospheric influences on North American precipitation as recorded with instrumental data. The reconstructions are included in the North American Seasonal Precipitation Atlas (NASPA) and provide insight into decadal droughts and pluvials. They indicate that the sixteenth-century megadrought, the most severe and sustained North American drought of the past 500 years, was the combined result of three distinct seasonal droughts, each bearing unique spatial patterns potentially associated with seasonal forcing from ENSO, the Arctic Oscillation, and the Atlantic multidecadal oscillation. Significant 200–500-yr-long trends toward increased precipitation have been detected in the cool- and warm-season reconstructions for eastern North America. These seasonal precipitation changes appear to be part of the positive moisture trend measured in other paleoclimate proxies for the eastern area that began as a result of natural forcing before the industrial revolution and may have recently been enhanced by anthropogenic climate change.

Free access
John R. Mecikalski, Wayne F. Feltz, John J. Murray, David B. Johnson, Kristopher M. Bedka, Sarah T. Bedka, Anthony J. Wimmers, Michael Pavolonis, Todd A. Berendes, Julie Haggerty, Pat Minnis, Ben Bernstein, and Earle Williams

Advanced Satellite Aviation Weather Products (ASAP) was jointly initiated by the NASA Applied Sciences Program and the NASA Aviation Safety and Security Program in 2002. The initiative provides a valuable bridge for transitioning new and existing satellite information and products into Federal Aviation Administration (FAA) Aviation Weather Research Program (AWRP) efforts to increase the safety and efficiency of project addresses hazards such as convective weather, turbulence (clear air and cloud induced), icing, and volcanic ash, and is particularly applicable in extending the monitoring of weather over data-sparse areas, such as the oceans and other observationally remote locations.

ASAP research is conducted by scientists from NASA, the FAA AWRP's Product Development Teams (PDT), NOAA, and the academic research community. In this paper we provide a summary of activities since the inception of ASAP that emphasize the use of current-generation satellite technologies toward observing and mitigating specified aviation hazards. A brief overview of future ASAP goals is also provided in light of the next generation of satellite sensors (e.g., hyperspectral; high spatial resolution) to become operational in the 2007–18 time frame.

Full access