#Gridded plan drivers#
#Gridded plan plus#

When examining deconstructed and spontaneous designs, the metaphor persists.

While navigation is perhaps more difficult, there are more alternatives, and people are therefore more motivated and able to become involved in the city’s offerings. The city’s organic growth hasn’t exactly made it the easiest place to navigate.īut in London, wonderful enclaves and interesting areas have emerged and neighborhoods with distinct flavor exist everywhere-and it can certainly be said that there aren’t just one or two central areas of cultural, community interests, but many.

#Gridded plan drivers#

I know Londoners who carry around a London A-Z guidebook to help them navigate! The city’s transportation system is so challenging that would-be cab drivers must pass a test demonstrating that they possess “ The Knowledge” in order to drive traditional black cabs. Many residents of Tucson will agree that the city lacks a vibrant center-or many unique communities-as a result, and that when those isolated spots do exist, they’re easy to get to, but people aren’t motivated to get out and find them. Furthermore, the constraints of Tucson’s grid do not encourage the emergence of alternative neighborhoods and communities. On the other hand, Tucson’s designers planned for only a certain amount of growth, and this has caused innumerable problems in maintaining the city’s ease of navigation and usability as the city grew beyond its planned limits. Residents provide directions to their homes by giving cues based on the grid: “I’m at the southwest corner of Campbell Avenue and Prince Road.” Public roadways and transportation typically run north to south or east to west, making it easy to navigate the town.

#Gridded plan plus#

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.On the plus side, Tucson certainly is easy to get around in you needn’t have much more than a basic sense of direction or a street map. 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). 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. 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. 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. 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. 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. However, their use in broad-scale, surface weather typing classifications and applications have not yet been explored. 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.

Université de soutenance : Kent State University Titre : The Development of a Gridded Weather Typing Classification Scheme