Investigating Climate Change in the US: Is it Uniform?
This week Id like for us to look at some actual temperature data from around the contiguous US so we can track how yearly average temperature has changed over the last 100 years; it is okay if the dataset goes back more than 100 years. Be sure to read the 5 prompts below before getting started.
Need to use excel.
For this activity Id like to look at five different data sets within the US.
The points you find are not going to perfectly be in line, but try to get close.
Two points at the same latitude, but one on the east coast and the other on the west coast (e.g. Seattle, WA and Portland, ME).
Two points at the same longitude, but on the southern and northern borders of the country (e.g. Houston, TX and Fargo, ND).
An additional point of your choosing (e.g. where you live, where you might want to live). This point may be outside of the US.
Go to this webpage
https://data.giss.nasa.gov/gistemp/station_data_v4_globe/
to get the data:
At the bottom of the page there is a globe which has all the data locations on it. Manipulate the globe to find a location you would like to use. You can pan and use double click to zoom in.
Once you find a location youd like to use, hover over it. That should give you a box with location information which will tell you how far back the dataset goes and give you an option to click on “Generate Plot”. At the bottom of the page that opened up download data as CSV.
When you double click on the CSV file you downloaded it should open in Excel. In Excel you will the first column is year, and the rest of the columns are looking at months. We are interested in the last column with is the yearly average temperature (in ).
You will probably notice in the dataset there are some temperatures that are 999.9 – thats really hot! What this means is that there is no data for that cell. In order to do our analysis we need to remove all of those 999.9s. To do this go to Find and Select, then click on Replace. A popup should appear, in the Find What box type 999.9, and leave the Replace With box blank – we want to remove the data and leave empty cells. Click replace all and you should be good to go.
With your cleaned data you can make a scatter plot of yearly temperature through time. Your X-axis will be time (year), and the Y-axis will be average yearly temperature (metANN). Make this graph, label all axes appropriately, give it a good title (e.g. Yearly Average Temperature in Fargo, ND). Also add a linear line of best fit, the regression, and R2 value.
If you have a hard time following these directions please ask! – I understand that we all have different technology backgrounds.
Once you have your five graphs made, Id like you to consider the following 5 prompts:
How has temperature changed over the last 100 years at each of your locations?
For locations at the same longitude, have the changes been similar or dissimilar? Why?
For locations at the same latitude, have the changes been similar or dissimilar? Why?
Does you analysis suggest that climate change is happening uniformly (or not) in the contiguous US? Defend your choice.
When we look at the global scale do we see climate change happening in the same way everywhere? Why or why not? Youll need to do some investigating on your own to figure this out.
For the document to hand in this week please include your five graphs and your answers to the prompts above. Since youll need to do some reading of outside sources to help you, youll need to include appropriate citations as well.
