# Comparing two datasets with same variable

I am comparing a ground-sourced dataset versus a satellite-sourced dataset for weather conditions, such as temperature. Both sets are time series data (ground takes a reading every 15 minutes while satellite is every 30 minutes, so there are twice as many data points from the ground data). I want to compare the difference between these two sets at each entry, to see if my ground data fits my satellite data to a statistical significance of whatever.

For example, a few entries for temperature would look like:

Basically, I am not sure which statistical test/method to use to determine if my ground data is 'good', or close enough to my satellite data, or how 'different' they are between each other to the point of inaccurate data.

The reason I ask is that the satellite data is much more reliable versus the ground data from some of the sites I am looking at, where sensor malfunctions plague my ground data sets. In essence, I want to automate this process in mathematica so that it will tell me if a dataset is worth using or not.

• Is all of your temperature data for a single location or are there multiple locations in your dataset and you were just showing a few of the variables above? Commented Feb 26, 2016 at 23:05
• Yes all my data is from from one location over a 4 year period. I was just showing a small sample of the sat an ground data over an hour period of the same location. Commented Feb 26, 2016 at 23:08
• i think you can use a CDF for the values, i am making the same thing with data of Temperature and radiaton, i hope this work for you.. Best regards Commented Apr 21, 2019 at 5:43

If you don't have concern about the accuraccy degrading over time or don't have concerns that the time of day results in less accurate measurements then I would advocate simplicity here through the use of a paired-sample t-test. You have completely missing data for the :15 and :45 intervals, so I'd throw those measurements away as you have nothing to compare them against from Satellite measurements. Then, with the remaining data, take the differences between the satellite measurement and the ground measurements, $y_{diff}=y_{satellite}-y_{ground}$. Then do a simple t-test on $y_{diff}$ to determine if $H_0:y_{diff}=0$ can be rejected at your desired level of confidence.