<p> The Urban Heat Island (UHI) was investigated using satellite data, ground observations, and simulations with an Urban Canopy Parameterization in a numerical weather prediction model. Satellite-observed surface skin temperatures at Xi'an City and Oklahoma City (OKC) were analyzed to compare the UHI intensity for the two inland cities. A larger population density and larger building density in Xi'an City creates a stronger skin-level UHI effect. However, ground observed 2-m surface air temperature (Tair) data showed an urban cooling island (UCI) effect that occurred over an urban region in OKC during the daytime of July 19, 2003. </p><p> The sensitivity and accuracy of an Urban Canopy Model were evaluated by comparing simulation results between the urban and rural areas of OKC. The model reproduced skin temperature differences between the rural and urban area and reproduced a UCI effect in OKC. Furthermore, the Weather Research and Forecasting (WRF)/Noah/Single-Layer Urban Canopy Model (SLUCM) simulations were also compared with ground observations, including wind speeds, wind directions, and energy fluxes. Although the WRF/SLCUM model failed to simulate these variables accurately, it reproduced the diurnal variations of surface temperatures, wind speeds, wind directions and energy fluxes reasonably well.</p>

<p> A mechanistic understanding of the North American Monsoon (NAM) is suggested by incorporating local- and synoptic-scale processes. The local-scale mechanism describes the effect sea surface temperature (SST) in Gulf of California (GC) and how it contributes to the low-level moisture during the 2004 NAM. Before NAM onset, the strong low-level temperature inversion exists over the GC, but this inversion weakens with increasing GC SST and generally disappears once SSTs exceed 29.5&deg;C, allowing the moist air, trapped in the MBL, to mix with free tropospheric air. This leads to a deep, moist layer that can be transported toward the NAM regions to produce thunderstorms. The synoptic scale mechanism is based on climatologies from 1983 to 2010 and explains that the warmest SSTs moving up the coast contributes to NAM convection and atmospheric heating, and consequently advancing the position of the anticyclone and the region of descent northward. </p><p> In order to improve microphysical properties of ice clouds, this study develops self-consistent second order polynomial mass- and projected area-dimension (m-D and A-D) expressions that are valid over a much larger size range, compared to traditional power laws. Such expressions can easily be reduced to power laws for the size range of interest, in order to use in cloud and climate models. This was done by combining field measurements of individual ice particle m and D with airborne optical probe measurements of D, A and estimates of m. The resulting m-D and A-D expressions are functions of temperature and cloud type (synoptic vs. anvil), and are in good agreement with m-D power laws developed from recent field studies. These expressions also appear representative for heavily rimed dendrites occurring over the Sierra Nevada Mountains. By using the m-D field measurements of rimed and unrimed particles, and by developing theoretical methods, an approach was suggested for calculating rimed m and A, which has the benefit of accounting for the degree of riming, and therefore it produces a gradual and continuous growth from unrimed ice particles to graupel. The treatment for riming includes a parameterization for collision efficiency as a function of droplet size and ice particle size using the available numerical studies. </p><p> A rimed snow growth model (RSGM) was developed based on the growth processes of vapor diffusion, aggregation, and riming. The RSGM uses a measured radar reflectivity at cloud top for initialization, and then predicts the vertical evolution of size spectra. The RSGM is based on the zeroth- and second- moment conservation equations with respect to mass, and thus conserves the number concentration and radar reflectivity, respectively. The size spectra predicted by the RSGM are in good agreement with observed spectra during Lagrangian spiral descents through frontal clouds. The snowfall rate with the inclusion of riming is significantly greater than that produced by the vapor deposition and aggregation alone. Snowfall rates are found to be sensitive to the cloud drop size distribution.</p>

<p> Low coastal stratiform clouds (stratus, stratocumulus, and fog), referred to here as coastal low cloudiness (CLC), are a persistent seasonal feature of continental west coasts, including California. The importance of CLC ranges across fields, with applications ranging from solar resource forecasting, growth of endemic species, and heat wave expression and related health impacts. This dissertation improves our understanding of California&rsquo;s summertime CLC by describing its variability and influences on a range of scales from multidecadal to daily and continental to local. A novel achievement is the development of a new 19-year satellite-derived low cloud record. Trained on airport observations, this high resolution record plays a critical role in the description of CLC at finer spatial and shorter timescales. </p><p> Observations at coastal airports from Alaska to southern California reveal coherent interannual to interdecadal variation of CLC. The leading mode of CLC variability, accounting for nearly 40% of the total variance, and the majority of individual airports, exhibit decreasing low cloudiness from 1950 to 2012. The coherent patterns of CLC variability are organized by North Pacific Sea Surface Temperature (SST) anomalies, linked to the Pacific Decadal Oscillation (PDO). </p><p> The new satellite-derived low cloud retrieval reveals, in rich spatial texture, considerable variability in CLC within May-September. The average maximum cloudiness moves northward along the coast, from northern Baja, Mexico to northern California, from May to early August. Both component parts of lower tropospheric stability (LTS), SST and free-troposphere temperature, control this seasonal movement. The peak timing of cloudiness and daytime maximum temperatures are most closely aligned in northern California. </p><p> On weather timescales, daily CLC anomalies are most strongly related to stability anomalies to the north (climatologically upwind) of the CLC region. CLC is strongly linked to stability in northern (southern) California throughout (only in early) summer. Atmospheric rather than oceanic processes are responsible for the cloud dependence on stability at daily timescales. The spatial offset of the LTS-CLC relationship reveals the roles of advective processes, subsidence, and boundary layer characteristics. Free-tropospheric moisture additionally impacts CLC, implicating the North American monsoon as a factor affecting southern California&rsquo;s coastal climate in late summer.</p>

<p> College football stadiums host anywhere from 15,000 to 115,000 people each Saturday from late summer to early winter and leave fans exposed to ambient conditions. Amplified heat from stadium infrastructure substantially impact attendants&rsquo; thermal comfort. In order to assess personal heat exposure and mitigate exposure misclassification, temperature and relative humidity sensors (iButtons) were placed throughout Mississippi State University&rsquo;s Davis Wade Stadium during the 2016 Football Season. iButton measurements established a micro-climate and compared its readings to the Soil Climate Analysis Network site 1.2 miles north of the stadium. The program RayMan Pro modeled a Physiological Equivalent Temperature (PET) micro-climate to create an individualized heat metric. The results of this study assess stadium occupants&rsquo; thermal comfort through Heat Index and PET. Heat-related health outcomes were examined regarding thermal comfort and the stadium micro-climate using data from the stadium&rsquo;s EMS calls and First Aid stations during game days. </p><p>

A unique methodology for forecasting weather based on geocentric planetary alignments originated in ancient Mesopotamia. The method, called astrometeorology, was further developed by Greek, Arab, and Renaissance scientists including Ptolemy, Al-Kindi, Tycho Brahe and Joannes Kepler. A major 17th century effort to test the method in a Baconian fashion was made by John Goad. Building on the ideas of Kepler and Goad, I test an isolated component of the method, specifically a correlation between geocentric Sun-Saturn alignments and cold temperatures, using modern daily temperature data from New England, Central England, Prague and other locations. My hypothesis states there is a correlation, shown in daily temperature records, between cooling trends in specific regions and the geocentric alignments of the Sun and the planet Saturn. The hypothesis is supported by a number of tests that show lower temperatures on days when Sun-Saturn alignments occur, especially when near the equinoxes. The astronomy of this positioning suggests that tidal forces on the atmosphere may be part of a mechanism that would explain the apparent effect. The abandonment of planetary weather forecasting by the intellectual elite in 16th and 17th century Europe is next organized as a history and discussion. In the final section, applications of the methodology to climate cycles is explored, particularly in regard to a 1536-year recurring cycle of outer planets and a cycle of similar length found in climate records. In addition, an account of biological processes that are structured around astronomical cycles is presented.

<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> 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>