<p> Statistical analyses relating carbon monoxide (CO) pollution and precipitation enhancement have been performed to explain a potential weekly link in the United States of America&rsquo;s Northeast Megalopolis. I investigated the weekly relationship between CO and precipitation using instrumental records from 2009. I also investigated whether CO pollution generally affects precipitation levels in the Megalopolis. Finally, I briefly compared the patterns of precipitation and carbon monoxide in Megalopolis to see if weather systems remained isolated to the surroundings cities or moved sequentially up the Atlantic coast. </p><p> Results confirm that there was a statistically significant difference between weekday and weekend CO and precipitation levels in Baltimore and Philadelphia. There were weekly cycles in precipitation and CO in Baltimore and New York, and an overall precipitation enhancement in the Megalopolis because of CO pollution. The results also indicate a sequential movement of precipitation and CO up the Atlantic coast from Washington, D.C. toward Boston. Overall, weekly distribution patterns of CO and precipitation patterns did exist in some places in 2009, while prevailing wind patterns and CO&rsquo;s cloud nucleating capabilities may partially account for the sequential movement of CO and precipitation enhancement in the study area.</p>

<p> An experiment was designed to capture micrometeorological observations during a fire spread on a simple slope. Three towers equipped with a variety of instrumentation, an array of fire-sensing packages, and a Doppler lidar was deployed to measure various aspects of the fire. Pressure and temperature perturbations were analyzed for each of the grid packages to determine if the fire intensity could be observed in the covariance of the two variables. While two of the packages measured a covariance less than &ndash;15 &deg;C hPa, there was no clear trend across the grid. The fire front passage at each of the three towers on the slope yielded extreme swings in observed turbulent kinetic energy and sensible heat flux. Vertical velocity turbulence spectra showed that the high-intensity fire front passage at the bottom tower was 2 to 3 orders of magnitude larger than the low-intensity fire front passages at the top two towers. Opposing wind regimes on the slope caused a unique L-shaped pattern to form in the fire front. A vorticity estimation from the sonic anemometers showed that vorticity reached a maximum just as a fire whirl formed in the bend of the L-shaped fire front, leading to a rapid increase in fire spread.</p><p>

This document presents an approach using the maximum likelihood formulation to estimate vector velocities in real-time by a network of Doppler radars. Relationships between the estimated vector velocity, the statistics of the measured signals, the characteristics of the observing geometry, and the hardware and signal processing parameters is derived. Metrics to gauge the quality of vector velocity retrievals are presented, and their utilization for network design and operation is provided. The thesis concludes with a software architecture for real-time implementation of the vector velocity estimation and its demonstration within the framework of the CASA IP1 four node radar network.

<p> Natural disasters can be very devastating to the public during their impact phase. After a natural disaster impacts a region, the response and recovery phases begin immediately. Weather conditions may interrupt emergency response and recovery in the days following the disaster. This study analyzes the climatology of weather conditions during the response and recovery phases of hurricanes and tornadoes to understand how weather may impact both environment and societal needs. Using specific criteria, 66 tornadoes and 16 hurricane cases were defined. National Weather Service (NWS) recognized weather stations were used to provide temperature, precipitation, snowfall, relative humidity, wind speed, and wind direction data. Regional and temporal groups were defined for tornado cases, but only one group was defined for hurricanes. By applying statistical analysis to weather observations taken in the week following the disasters, a climatology was developed for the response and recovery phase. Tornado and hurricane post-disaster climate closely mimicked their synoptic climatology with cooler and drier weather prevailing in days 2-4 after a disaster until the next weather system arrived about 5 days later. Winter tornadoes trended to occur in the Southeast and were associated with more extreme temperature differences than in other regions and season. The results of this study may help governmental and non-governmental organizations prepare for weather conditions during the post-disaster phase.</p>

<p> Landslides pose a persistent threat to El Salvador's population, economy and environment. Government officials share responsibility in managing this hazard by alerting populations when and where landslides may occur as well as developing and enforcing proper land use and zoning practices. This thesis addresses gaps in current knowledge between identifying precisely when and where slope failures may initiate and outlining the extent of the potential debris inundation areas. Improvements on hazard maps are achieved by considering a series of environmental variables to determine causal factors through spatial and temporal analysis techniques in Geographic Information Systems and remote sensing. The output is a more dynamic tool that links high resolution geomorphic and hydrological factors to daily precipitation. Directly incorporable into existing decision support systems, this allows for better disaster management and is transferable to other developing countries.</p>

<p> Since their development in the 1990s, gridded reanalysis data sets have proven quite useful for a broad range of synoptic climatological analyses, especially those utilizing a map pattern classification approach. However, their use in broad-scale, surface weather typing classifications and applications have not yet been explored. This research details the development of such a gridded weather typing classification (GWTC) scheme using North American Regional Reanalysis data for 1979-2010 for the continental United States. </p><p> Utilizing eight-times daily observations of temperature, dew point, pressure, cloud cover, u-wind and v-wind components, the GWTC categorizes the daily surface weather of 2,070 locations into one of 11 discrete weather types, nine core types and two transitional types, that remain consistent throughout the domain. Due to the use of an automated deseasonalized z-score initial typing procedure, the character of each type is both geographically and seasonally relative, allowing each core weather type to occur at every location, at any time of the year. Diagnostic statistics reveal a high degree of spatial cohesion among the weather types classified at neighboring locations, along with an effective partitioning of the climate variability of individual locations (via a Variability Skill Score metric) into these 11 weather types. Daily maps of the spatial distribution of GWTC weather types across the United States correspond well to traditional surface weather maps, and comparisons of the GWTC with the Spatial Synoptic Classification are also favorable. </p><p> While the potential future utility of the classification is expected to be primarily for the resultant calendars of daily weather types at specific locations, the automation of the methodology allows the classification to be easily repeatable, and therefore, easily transportable to other locations, atmospheric levels, and data sets (including output from gridded general circulation models). Further, the enhanced spatial resolution of the GWTC may also allow for new applications of surface weather typing classifications in mountainous and rural areas not well represented by airport weather stations.</p><p> </p>