Vol. 55, No. 2, Fall/Winter 2017


(pp. 6 - 23)

Analyse M. Gaspich

Department of Education

Kutztown University of Pennsylvania

Michael A. Davis

Department of Geography

Kutztown University of Pennsylvania

Kutztown, Pennsylvania


Over the course of 30 years there has been a change in the precipitation patterns in Pennsylvania related to multiple climatological variables. Precipitation data—consisting of total snowfall, heavy snow days, and ice data—from Pennsylvania during the winter from December 1979 to February 2010 were collected from the National Climate Data Center using weather station data. Specific humidity and surface temperature data were provided by the NCAR Reanalysis Project to provide additional moisture and temperature data. Regional analysis were performed using broad precipitation data supplied by climate division data. Furthermore, the role of elevation was analyzed in terms of changes in winter precipitation. This study was conducted during the three decadal periods consisting of the 1980-1889, 1990-1999, and 2000-2010 time periods. Impacts from El Nino-Southern Oscillation was also addressed. Trends in these key climatological variables are presented in this study. Analysis of snowfall amounts and various elevations suggest that variability during El Nino is increasing. In the early 2000s, a large range in snowfall variability between stations is observed between the individual elevation groupings. Annual snowfall total depict an increase in the total snowfall amount. Moreover, the decadal analysis during 2000-2010 of the average amount of precipitation exhibit a 0.51 inch increase in comparison to the previous two decades of the study.


(pp. 24 - 30)

Christopher A. Badurek

Department of Geography

State University of New York at Cortland

Cortland, New York


Rapid population growth has fueled suburban growth and second home developments have increased exurban development in the Southern Appalachian mountain region. To further understand the rate of housing density change and potential environmental impacts, a GIS-based model of forest loss susceptibility has been developed to forecast deforestation in Watauga County in western North Carolina. The model is derived from land cover, terrain, land value, infrastructure, and growth rate variables and implemented within GIS for running over three time intervals. Assessment of the model indicates a 30% transition of forested areas to developed low density exurban areas over a 15-year time period with significant pockets of growth primarily constrained to population centers and recreational amenity locations. Results may be used by land use planning and decision-making concerning residential economic development and managing the impacts of rural sprawl.

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