Browsing by Author "Carroll, David F."

Now showing 1 - 13 of 13
  • Thumbnail Image
    Analysis of Extreme Reversals in Seasonal and Annual Precipitation Anomalies Across the United States, 1895-2014
    Marston, Michael Lee (Virginia Tech, 2016-07-01)
    As population and urbanization increase across the United States, the effects of natural hazards may well increase, as extreme events would increasingly affect concentrated populations and the infrastructure upon which they rely. Extreme precipitation is one natural hazard that could stress concentrated populations, and climate change research is engaging heavy precipitation frequency and its impacts. This research focuses on the less-studied phenomenon of an extreme precipitation reversal - defined as an unusually wet (dry) period that is preceded by an unusually dry (wet) period. The magnitude is expressed as the difference in the percentiles of the consecutive periods analyzed. This concept has been documented only once before in a study that analyzed extreme precipitation reversals for a region within the southwestern United States. That study found that large differences in precipitation from consecutive winters, a hydrologically critical season for the region, occurred more frequently than what would be expected from random chance, and that extreme precipitation reversals have increased significantly since 1960. This research expands upon the previous work by extending the analysis to the entire continental United States and by including multiple temporal resolutions. Climate division data were used to determine seasonal and annual precipitation for each of nine climate regions of the continental United States from 1895-2014. Precipitation values were then ranked and given percentiles for seasonal and annual data. The season-to-season analysis was performed in two ways. The first examined consecutive seasons (e.g., winter–spring, spring–summer) while the second analyzed the seasonal data from consecutive years (e.g., spring 2014–spring 2015). The annual data represented precipitation for the period October 1–September 30, or the 'water year' used by water resource managers. Following the approach of the previous study, a secondary objective of the research was to examine large-scale climate teleconnections for historical relationships with the occurrence of precipitation reversals. The El Nino-Southern Oscillation was chosen for analysis due to its well-known relationships with precipitation patterns across the United States. Results indicate regional expressions of a propensity for extreme precipitation reversals and relationships with teleconnections that may afford stakeholders guidance for proactive management. Precipitation reversal (PR) and extreme precipitation reversal (EPR) values were significantly larger for the second half of the study period for the western United States for the winter-to-winter, spring-to-spring, and year-to-year analyses. The fall-to-fall analysis also revealed changes in PR/EPR values for several regions, including the northwest, the Northern Rockies and Plains, and the Ohio Valley. Relationships between the winter-to-winter PR time series and an index representing the El Nino-Southern Oscillation (ENSO) phenomenon were examined. The winter-to-winter PR time series of the Northern Rockies and Plains region and the South exhibited significant relationships with the time series of Niño 3.4 values. El Niño (La Niña) coincided with more wet-to-dry (dry-to-wet) PR/EPR values for the Northern Rockies and Plains, while El Niño (La Niña) coincided with more dry-to-wet (wet-to-dry) PR/EPR values for the South.
  • Thumbnail Image
    Assessing Urban Landscape Variables’ Contributions to Microclimates
    Parece, Tammy E.; Li, Jie; Campbell, James B. Jr.; Carroll, David F. (Hindawi, 2015-12-24)
    The well-known urban heat island (UHI) effect recognizes prevailing patterns of warmer urban temperatures relative to surrounding rural landscapes. Although UHIs are often visualized as single features, internal variations within urban landscapes create distinctive microclimates. Evaluating intraurban microclimate variability presents an opportunity to assess spatial dimensions of urban environments and identify locations that heat or cool faster than other locales. Our study employs mobile weather units and fixed weather stations to collect air temperatures across Roanoke, Virginia, USA, on selected dates over a two-year interval. Using this temperature data, together with six landscape variables, we interpolated (using Kriging and Random Forest) air temperatures across the city for each collection period. Our results estimated temperatures with small mean square errors (ranging from 0.03 to 0.14); landscape metrics explained between 60 and 91% of temperature variations (higher when the previous day’s average temperatures were included as a variable). For all days, similar spatial patterns appeared for cooler and warmer areas in mornings, with distinctive patterns as landscapes warmed during the day and over successive days. Our results revealed that the most potent landscape variables vary according to season and time of day. Our analysis contributes new dimensions and new levels of spatial and temporal detail to urban microclimate research.
  • Thumbnail Image
    Assessment of Model Forecast Temperature Bias During Cold Air Damming in the Central Appalachian Mountains
    Lindeman, Suzanna Alison (Virginia Tech, 2018-06-06)
    Cold-air damming (CAD) is a prevalent Mid-Atlantic United States weather phenomenon that occurs when cold, dense air is dammed alongside the eastern slopes of the Appalachian Mountains. Lower-than-normal maximum temperatures, increased and prolonged cloud cover, and precipitation that produces hazardous impacts are common features of this weather event, which are well known for presenting difficulties to both human forecasters and weather prediction models. This study explores CAD events between 2007 and 2016 archived in a Blacksburg National Weather Service ‘bust’ database – instances when forecasters erred by at least 8°F (4.4°C) on either maximum or minimum daily air temperature. The database includes the temperature error within Model Output Statistics (MOS) guidance in association with these forecast ‘busts.’ During the 10-year study period, MOS guidance produced warm-biased maximum temperatures and cold-biased minimum temperatures for most of the problematic CAD events, suggesting MOS guidance tended to underestimate the strength of CAD in these cases, seeming to struggle with weaker CAD events. During CAD erosion, MOS tended to prematurely erode CAD scenarios at night and predicted them to persist for too long during the day. Hourly surface meteorological and synoptic atmosphere composites during these ‘busted’ CAD events failed to reveal obvious differences from what is expected for central Appalachian CAD. However, a comparison to well-forecast classic cold-season CAD events suggest that busted cases of this same type of CAD may be drier than is typical. As the atmospheric patterns associated with busted CAD events are typical of the phenomenon, but a bit weaker or more marginal, forecast errors appear to stem from subtle model errors rather than forecaster error. It is possible that the models may inadequately characterize low-level moisture, but further research is needed to isolate the source of model forecast error. Nonetheless, the results of this research serve as guidance for operational forecasters as they consider model guidance during weak CAD events.
  • Thumbnail Image
    Biotic and Abiotic Factors of Picea rubens (Red Spruce) Seedling Regeneration in Disturbed Heathland Barrens of the Central Appalachians
    White, Helen M. (Virginia Tech, 2019-06-20)
    During the late 19th and early 20th centuries, extensive logging reduced the forests of red spruce (Picea rubens) by nearly 99% through portions of West Virginia. In the wake of this disturbance, red spruce has begun regenerating on the ridge and mountaintop areas of Canaan Valley, West Virginia, where heath and grassland communities have both persisted in natural barrens and expanded into formerly forested areas. To understand abiotic and biotic conditions guiding the advance of the red spruce stand, I conducted a broad-scale assessment of thirty-one demographics plots spread across two sites (north Cabin Mountain and Bear Rocks/Dolly Sods), and a more focused assessment of red spruce species associations within thirty-two paired plots at Cabin Mountain. At the 15m x 15m demographics plots, I conducted a count of all P. rubens present, measured specimen height, DBH or diameter at ground level (DGL) for specimens < 1.37m tall, and assessed the relative percent cover of rock, shrub, herbaceous, and tree cover. These data, along with additional abiotic components derived from a DEM, formed the basis of my assessment using a generalized linear mixed model (GLMM) to identify the most significant biophysical variables related to P. rubens count. In the paired plots, I used the relative interactions index (RII) to compare the total cover of each present non-graminoid vascular species and the grouped cover types Rock, Graminoid, Lichen, Litter, and Moss in one 45cm-radius plot with a < 1.37m P. rubens specimen, and one paired 45cm-radius plot in open heath. The significance of differences in total cover were assessed with the Wilcoxon test and Tukey HSD. The GLMM identified percent rock cover and distance from the nearest P. rubens stand to be important correlates of P. rubens count at the demographic plots. Graminoid cover was found to be higher in P. rubens 45cm-radius plots than in paired heath plots, and Vaccinium angustifolium cover was found to be concentrated in 45cm radius plots beyond the first 15cm from the P. rubens stem. These findings reinforce a complex interplay between both the biotic and abiotic characteristics of a microsite and the successful germination and regeneration of a red spruce seedling in the heathland.
  • Thumbnail Image
    Characteristics of Red Spruce (Picea rubens Sarg.) Encroachment at Two Central Appalachian Heathland Study Areas
    White, Helen M.; Resler, Lynn M.; Carroll, David F. (IGI Global, 2021)
    During the late 19th and early 20th centuries, intensive land use nearly eliminated red spruce (Picea rubens Sarg.) throughout portions of West Virginia (WV). Red spruce has been slow to regenerate on mountaintop heathland barrens surrounding Canaan Valley, West Virginia (WV), and little is known about the nature of encroachment. Using field surveys, geospatial data, and statistical modelling, the objectives were to 1) characterize and compare red spruce encroachment at two upland heath study areas in West Virginia (Bear Rocks and Cabin Mountain), 2) characterize percent cover of major ground cover types associated with red spruce regeneration sites in order to elucidate biotic interactions, and 3) model the biophysical correlates of red spruce encroachment using geospatial data and statistical modelling. Red spruce count was similar at both study areas, but there were substantially more seedlings and saplings at Cabin Mountain. Modelling revealed a positive relationship between red spruce count and rock cover and a negative relationship between red spruce and stand distance.
  • Thumbnail Image
    Dual-Doppler Derived Vorticity as a Predictor of Hail Size in Severe Thunderstorms
    White, Trevor Stewart (Virginia Tech, 2017-02-03)
    One of the primary missions of the National Weather Service (NWS) is to use a network of more than 150 NEXRAD radar installations to monitor weather for threats to life and property. Large hail produced by severe thunderstorms is a major focus of this mission. An algorithm known as the Maximum Estimated Size of Hail (MESH) algorithm is in operational use to diagnose the presence and size of hail. This study aims to use dual-Doppler observations as well as the MESH algorithm to test the idea that storms that rotate produce larger hail. Previous studies have used polarimetric radar products to detect the presence of large hail and dual-Doppler methods have been used to study embryonic hail, but no research has tested the theory of hail and rotating storms with observational evidence. A set of 59 case studies was gathered; each included a hail report submitted by a trained weather spotter or NWS employee and complete radar observations through the depth of a storm from two radars. The radar observations were resampled to a three-dimensional Cartesian grid and a dual-Doppler analysis was run on each case study. A strong correlation (stronger even than the MESH algorithm) was found between measured vorticity and hail size, lending credence to the idea that rotating storms do indeed have a higher ceiling for hail production. However, no correlation was found between MESH error and rotation. Further research will be required to evaluate whether or not this relationship can be used to augment the MESH algorithm so as to improve its skill.
  • Thumbnail Image
    Impacts of Synoptic Weather on the Ice Phenology of Maine Lakes, 1955-2005
    Greene, Timothy Robert (Virginia Tech, 2018-06-05)
    The cryosphere has been shown to be particularly adept as a proxy for climate change by various studies. Accordingly, historical records from the field of ice phenology have been harvested by climate scientists for the express purpose of studying the temporal variation of ice phenomena, namely freeze-up and ice-out. Ice-out records from 20 lakes in Maine, U.S.A. were collected and clustered by z-score for this thesis. Rather than attempt to relate ice-out to spring air temperature or global teleconnections/oscillations, the Spatial Synoptic Classification (SSC) method was used to encapsulate several meteorological variables that could have a bearing on ice-out variation. The balance between occurrence of relatively cool Moist Polar (MP) and relatively warm Dry Moderate (DM) weather-types during the winter-spring "superseason" was found to be a synoptic barometer of whether ice-out would occur seasonably early or late. The significance of this is predicated upon the finding that quantity of DM days has steadily risen at the expense of MP days during the latter-half of the twentieth-century, in accordance with observed climatic warming during the same period. The remaining SSC weather-types, most notably omnipresent Dry Polar (DP), remained generally stable during the historical record in Maine, further undergirding the significance of the DM-MP relationship.
  • Thumbnail Image
    Landscape pattern and blister rust infection in whitebark pine (Pinus albicaulis) at alpine treeline, Northern Rocky Mountains, U.S.A.
    Franklin, Lauren Nicole (Virginia Tech, 2011-06-15)
    Whitebark pine (Pinus albicaulis) is a foundation and keystone species at alpine treelines of the northern Rocky Mountains and is threatened by the fungus white pine blister rust (Cronartium ribicola). This disease affects all five-needled white pines, but has caused particularly widespread mortality in whitebark pine. Objectives of this research were: 1) to characterize the landscape structure of the treeline study sites at Divide Mountain in Glacier National Park and at Wyoming Creek in the Beartooth Mountains of Montana using landscape metrics and fieldwork; 2) to determine the frequency of blister rust infection of whitebark pine trees and determine if landscape pattern is correlated with higher infection rates; and 3) to characterize the climate at alpine treeline. I used both field surveys and subsequent statistical analysis to meet these objectives. Field data collection included detailed surveys of blister rust infection of treeline whitebark pine and characterization of landscape cover type in a combined total of 60 quadrats, positioned at the study sites using a random sampling scheme stratified by aspect. Landscape analysis of metrics such as patch area, proximity and contagion were generated in FRAGSTATS software and ArcGIS. Spearman's rank correlation analysis found significant correlations between tree island patch size, patch perimeter, and percent of landscape and blister rust infection intensity at both study sites. These findings support previous research involving the relationship between patch area and blister rust infection rates and contribute to the field of landscape ecology by understanding what other landscape metrics are significant in invasive disease infection patterns.
  • Thumbnail Image
    Long-term Changes in Synoptic-Scale Air Mass Persistence Across the United States
    Suggs, Jessica Marie (Virginia Tech, 2017-08-15)
    From a climate dynamics perspective, air mass persistence reflects variability in the dynamic nature of the atmosphere. In this study, a historical analysis of synoptic air mass persistence across the continental United States is presented to portray spatial and temporal variability and trends in air mass residence times. Historical daily air mass calendars for 140 locations across the United States for the 60-year period 1955 through 2015 were extracted from the Spatial Synoptic Classification database. The data were stratified by season, and a historical climatology of seasonal air mass occurrence was created for each location. The historical daily air mass data were then translated into a record of residence time, or the length of consecutive days that a synoptic air mass type was in place at a location. Each historical record of seasonal air mass residence times, or persistence, was then analyzed for spatial variability across the United States and for temporal variability and trends. Results reveal a statistically significant increase in air mass persistence for many areas of the country during three seasons, but most commonly across the southern United States during the summer season (June-August). However, this pattern was reversed for the winter season (December-February), the analyses revealed a general pattern of decreasing cool-season air mass persistence across the continental United States. The seasonally-dependent change in air mass persistence across the United States may be indicative of changed or changing mid-latitude atmospheric dynamics in the form of a previously suggested northward migration of the polar jet stream.
  • Thumbnail Image
    Regional Differences in the Spatial Patterns of Precipitation Bands in Hurricanes Through Landfall along the Gulf of Mexico and Atlantic Coasts of the United States
    Kirkland, Jessica Lynn (Virginia Tech, 2018-08-03)
    Evolutionary periods of precipitation distribution in tropical cyclones (TCs) are sometimes misrepresented in numerical weather prediction models due to the rapid nature of TC structure changes that accompany intensity change. To better understand quantitative changes in TC rainband structure around landfall, I quantify the spatial distribution of precipitation in 62 landfalling TCs along the Gulf of Mexico and Atlantic coasts of the U.S. between 1998 and 2014. The Tropical Rainfall Measuring Mission (TRMM) 3B42 product is utilized to assess three spatial measures of precipitation: 1) area, 2) closure, and 3) dispersion. Calculations are made using two rain rate thresholds, 0.254mm/hr and 5mm/hr, to capture and compare changes in light and heavy precipitation, respectively. Changes in TC precipitation are statistically different based on landfall location along the Atlantic vs. Gulf. Overall, dispersion (measure of centrality) is the most dissimilar metric due to variability between 0.254mm/hr and 5mm/hr results. Lighter precipitation decreases in area and expands away from the TC center, while heavier precipitation contracts rather than disperses in Gulf landfalling storms. A k-means clustering produces six landfall regions and reinforces the result of heavier precipitation becoming more central along the Gulf, while Atlantic landfalling storms exhibit decreased centrality. Significant differences were not found in storms that undergo extratropical transition or dissipate later in lifecycle. The holistic approach exhibited by this study reveals wide variability among a large dataset of storms making landfall; therefore, sub-setting techniques are helpful to hurricane forecasters in understanding the role of landfall location.
  • Thumbnail Image
    Terrain and Landcover Effects of the Southern Appalachian Mountains on the Low-Level Rotational Wind Fields of Supercell Thunderstorms
    Prociv, Kathryn A. (Virginia Tech, 2012-04-30)
    That tornadoes cannot occur in mountains due to disruptive influences of the complex terrain is a common misperception. Multiple tornadoes occur each year in mountainous environments, including the Appalachian Mountains. Copious research examines the influences of complex terrain on large severe weather systems such as multicell convective systems and squall lines, but research is lacking investigating this same relationship for smaller-scale severe weather phenomena like supercells and tornadoes. This study examines how complex terrain may have influenced the rotational low-level wind fields of fourteen supercell thunderstorms in the Appalachians. The terrain variables include elevation, land cover, slope, and aspect. Using GIS mapping techniques, the individual storm tracks were overlaid onto elevation, land cover, slope, and aspect layers; points along the storm tracks were measured to correlate storm intensities with the underlying terrain. Hypotheses predict that lower elevations, areas of shallower slopes, agricultural land covers, and terrain features with a southeasterly orientation represent terrain variables that would enhance low-level rotation in the lower levels. Results indicate that elevation has a significant impact on storm rotational intensity, especially in mountainous regions. Lower and flatter elevations augment storm rotational intensity, and higher elevations decrease storm rotational intensity. Additionally, northern and western facing slopes exhibited a negative relationship to storm intensity. A qualitative examination revealed vorticity stretching to be evident in eight of the fourteen storms; with vorticity stretching evident on both southeasterly and northwesterly slopes. Future research on appropriate scale for storm-terrain interactions could reveal even stronger relationships between topography and supercell thunderstorms.
  • Thumbnail Image
    The Utility of Total Lightning in Diagnosing Single-cell Thunderstorm Severity in the Central Appalachian Mountains Region
    Miller, Paul Wesley (Virginia Tech, 2014-05-04)
    Recent severe weather research has examined the potential role of total lightning patterns in the severe thunderstorm warning-decision process although none to-date have examined these patterns in explicitly weak-shear environments. Total lightning flashes detected by the Earth Networks Total Lightning Network (ENTLN) during the 2012-13 convective seasons (1 May – 31 August) over a region of the Central Appalachian Mountains were clustered into likely discrete thunderstorms and subsequently classified as either single-cell or multicell/supercell storm modes. The classification of storms was determined using a storm index (SI) which was informed by current National Weather Service (NWS) identification techniques. The 36 days meeting the minimum threshold of lightning activity were divided into 24 lightning-defined (LD) single-cell thunderstorm days and 12 LD multicell/supercell days. LD single-cell days possessed statistically significant lower 0000 UTC 0-6 km wind shear (13.8 knots) than LD multicell/supercell days (26.5 knots) consistent with traditional expectations of single-cell and multicell/supercell environments respectively. The popular 2σ total lightning jump algorithm was applied to all flashes associated with 470 individual LD thunderstorms. The frequencies of the storms’ total lightning jumps were then compared against any associated severe weather reports as an accuracy assessment. The overall performance of the algorithm among both categories was much poorer than in previous studies. While probability of detections (POD) of the 2σ algorithm were comparable to previous research, false alarm rates (FAR) were much greater than previously documented. Given these results, the 2σ algorithm does not appear fit for operational use in a weak shear environment.
  • Thumbnail Image
    Verification of Satellite Derived Precipitation Estimates Over Complex Terrain: A Ground Truth Analysis for Nepal
    Athey, Ashley Taylor (Virginia Tech, 2015-06-05)
    Precipitation estimates from the satellite-based Tropical Rainfall Measuring Mission (TRMM) instrumentation play a key role in flood analysis and water resource management across many regions of the world where rain gauge data are sparsely available. Previous studies have produced conflicting results regarding the accuracy of satellite-derived precipitation products, and several authors have called for further examination of their utility, specifically across the Himalaya Mountains region of southern Asia. In this study, daily precipitation estimates generated by TRMM were compared to daily precipitation measurements from a rain gauge network across the country of Nepal. TRMM data were statistically analyzed to quantify their representation of the gauge data during the four precipitation-defined seasons of Nepal. A detailed case study was assembled for the TRMM grid cell characterized by the greatest precipitation gauge density to develop a deeper understanding of local precipitation variability that the coarse resolution TRMM product cannot capture. The results illustrate that TRMM performs relatively well across all seasons, though the performance of TRMM during frozen precipitation events is not clear. In general, TRMM underestimates daily precipitation during the monsoon and pre-monsoon seasons, and overestimates during the winter and post-monsoon season. The case study analysis revealed a threshold for TRMM bias of 10-20mm of daily precipitation, overestimating lighter precipitation events while underestimating heavier precipitation events. Still, TRMM data compare favorably to gauge data, which contributes to the confidence with which they and other satellite-derived data products are used.