Final Project

Josh Welty

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The goal of this project was to be able to effectively display some of the basics of the phenomena that I am beginning to study. One of the foremost goals was to display the climatological differences between the El Niño year of 2009 and the La Niña year of 2010 by using primarily two variables: vertical wind shear and vorticity at the 850mb and 200mb pressure levels. While the details do not need to be discussed here, I wanted to be able to display these quantities averaged over the hurricane season (~May~November) for the two years and then compare those values by subtracting the averages of 2010-2009.
The main page can be effectively split into three realms: graphics, past observations, and present observations. All data in this study were pulled from NCEP/NCAR's NCEP/DOE Reanalysis dataset. I then used NCAR Command Language (NCL) to create some programs to make the figures on the first page exhibiting shear and vorticity for 2009, 2010, and then 2010-2009. Additionally, these programs spit out numbers (averages of shear and vorticity for 2009 subtracted from averages for 2010 at points in a 2.5x2.5 LatLon grid from {0:30}degN latitude and {80:0}degW longitude) that could then be placed in a .csv file to create some shapefiles in ArcGIS that could be displayed using Google Maps API to constitute past climatology. The conversion to shapefiles followed this basic process:
1. Connect to folder with .csv files and create feature class from XY table.
2. Set the Projected Coordinate System to WGS_World_Mercator_1984.
3. Convert to raster from point using Conversion Tools>To Raster>From Point using ArcToolbox with cellsize 2.5.
4. For the vorticity values, Spatial Analyst Tools>Map Algebra>Raster Calculator was used to get the assigned values to type integer by multiplying by ten then using RoundUp().
5. Raster datasets were then converted from raster to polygon using Conversion Tools>From Raster>To Polygon.
6. In order to only grab the polygon grid and not the whole data frame, data was exported using selected features in the attribute table that excluded the data frame polygon area outside of the grid of interest.
7. These simplified polygon blocks were assigned colors using different classes in the map file and added using Google Maps API with a legend.
Additionally, the 'past' climatology includes a link to a CartoDB .json overlaid on Google Maps displaying the tracks of hurricanes during 2009 and 2010.
The 'present' column utilizes a bunch of GetMap requests to display current ocean temps, GOES infrared satellite imagery, CONUS radar, track and category forecasts for current storms, CONUS wind speed, and TRMM (Tropical Rainfall Measuring Mission) precipitation coverage. I could not get this to display using Google Maps API, so it was simply added to NASA's 'bluemarble' layer.

Final Project