Authors: Hannah Wang*, George Washington University
Topics: Environment, Spatial Analysis & Modeling, Physical Geography
Keywords: Global cooling, metrics, global warming
Session Type: Paper
Start / End Time: 12:40 PM / 2:20 PM
Room: Mid-City, Sheraton, 8th Floor
Presentation File: No File Uploaded
We are trying to develop a more sensitive metric that measures the effect of greenhouse gases and aerosols on aerosol radiative effect across weather stations in the United States because we are interested how changes in aerosol properties can affect extreme weather phenomenon such as heatwaves. This will be accomplished by examining the relationship amongst a variety of variables such as number of days with temperature highs, cumulative days with high temperature, and aerosol radiative effects. Temperature highs are calculated by counting the number of days a station experiences temperature highs. Cumulative days with high temperature also counts the number of days with temperature highs but subtracts the number of days with temperature lows. Since we are working with hundreds of weather stations over a thirty year period, we’ll be using Python to help us calculate our values. This will then be joined to our aerosol radiative effects TIF layer for each weather station in the United States using ArcMap. Afterwards we will run an ordinary least squares regression to examine the potential spatial relationship between aerosol values in the GeoTiff and values for temperature max or cumulative days with high temperatures. We will then test for spatial autocorrelation using Moran’s I as well as other regression model techniques using ArcMap and Python.