<p> With more than half of the world's population living in urban areas, it is important that the relationships between the urban environment and climate are better understood. The current research aims to continue the effort in assessing and understanding the urban environment through the use of a global climate model (GCM). Given the relative newness of the presence of an urban land type and model in a GCM, there are many more facets of the urban-climate relationship to be investigated. By comparing thirty-year ensembles of CAM4 coupled with CLM4 both with (U) and without (U_n) the inclusion of the urban land type, the sensitivity of the atmospheric model to urban land cover is assessed. As expected, largest differences tend to be in the Northern Hemisphere due to the location of most of the globe's densest and expansive cities. Significant differences in the basic climate variables of temperature and precipitation are present at annual, seasonal, and monthly scales in some regions. Seasonality to the urban influence also exists with the transition months of Spring and Fall having the largest difference in temperatures. Of the eleven regions defined by Oleson (2012), three were most impacted by the presence of urban land cover in the model&mdash;Europe, Central Asia, and East Asia. </p><p> Since urban attributes can vary greatly within one world continent, the sensitivity of regional climates to the urban type parameters is also explored. By setting all urban land cover to only one urban density type, the importance of city composition on climate, even within the same city, is highlighted. While preserving the distinct urban regional characteristics and the geographical distribution of urbanized areas, the model is run with homogeneous urban types: high density and tall building district. As with the default urban and excluded urban runs, a strong seasonality to the differences between the solo-high-density simulation and default urban (U_HD &ndash; U) and solo-tall-building-district-density simulation and default urban (U_TBD &ndash; U) exists. Overall, the transition and winter months are most sensitive to changes in urban density type.</p>

<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>