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Full-Text Articles in Physical Sciences and Mathematics
A Study On Modelling Spatial-Temporal Human Mobility Patterns For Improving Personalized Weather Warning, Yue Xu
Masters Theses
Understanding human mobility patterns is important for severe weather warning since these patterns can help identify where people are in time and in space when flash floods, tornados, high winds and hurricanes are occurring or are predicted to occur. A GIS (Geographic Information Science) data model was proposed to describe the spatial-temporal human activity. Based on this model, a metric was designed to represent the spatial-temporal activity intensity of human mobility, and an index was generated to quantitatively describe the change in human activities. By analyzing high-resolution human mobility data, the paper verified that human daily mobility patterns could be …
Interannual Variations Of Snowfall In The Lower Peninsula Of Michigan And Impacts Of Local And Remote Meteorological Conditions, Nirjala Koirala
Interannual Variations Of Snowfall In The Lower Peninsula Of Michigan And Impacts Of Local And Remote Meteorological Conditions, Nirjala Koirala
Masters Theses
Inter-annual variation of snowfall and its relation to climate indices will help clarify and improve the prediction of total snowfall in the Lower Peninsula of Michigan (LPM). This study examines the trend and variability of annual snowfall (November- March) using 8 homogeneous weather stations in the LPM. The statistical relationship between snowfall and air temperature, Sea Surface Temperature (SST), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO) and Maximum Ice Coverage(MIC) of Lake Michigan is calculated. The long-term trend in the snowfall data set from 1950 to 2015 is removed before any statistical correlation analysis is conducted. My analysis suggests …