# Creating a raster map using Excel file and calculating averages

I am working on my Master's thesis and have thought about using ArcGIS to create a raster map of latitude/longitude (0 to 360 degrees) temperature data (in Excel format). This temperature data reflects the total amount of warming that has occurred per degree Celsius of global warming by location. For my purposes, my data collection process involves me upscaling regional temperature warming into a global mean temperature warming.

As such, what I am attempting to do is transform the provided Excel data into a raster map in ArcGIS. In doing this, I would be able to visually see regional temperature increases per degree Celsius of global warming. The idea is to be able to more flexibly calculate regional temperature averages per degree Celsius of global warming (such as in the NW Pacific, or the North Atlantic), so that I can upscale these averages into a global mean temperature warming. My question is, would it be possible to calculate these averages in this way? If so, what procedure can I follow?

Any assistance would be greatly appreciated!

Thanks,

~Trav.~

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It would be helpful to give an example of one row of your data. The workflow I'm envisioning is: Excel Workbook => ASCII Text => ESRI Raster –  Roy Aug 15 '12 at 17:00
Hi Roy, the rows for the Excel data are arranged in such a way that they begin with the first cell (from the left) being longitude, then latitude, followed by the average annual temperature warming for that location. For example: 0 (longitude), -87.8638 (latitude), 1.17 C (Annual average temperature). –  Travis Aug 15 '12 at 18:02
So, three columns, the first being Longitude, the second latitude, and the third is annual average temperatures. There is also a 4th and 5th displaying average temperatures for specific months. Roy, will you be notified of my posting? Thanks, ~Trav.~ –  Travis Aug 15 '12 at 18:06
You'd have to create a separate raster surface for each month's average temperature. –  Roy Aug 15 '12 at 18:52
Depending on the density of your data, interpolation may be a much better way to go. –  Roy Aug 15 '12 at 19:44