'splain' My Detrending

There are a lot of sophisticated methods to manipulate time series to determine trends and remove trends for data series. I ain't all that sophisticated, some I am starting with baby steps. As the oceans temperature changes, the sea level should change somewhat. There are other factors involved in sea level change, but I wanted to see how well the UAH atmopsheric temperature data followed the sea level changes recorded by satellite altimetry. I downloaded the data for the NCDC site, but right now I can't find the exact link. Anywho, there is a much higher slope in the sea level change than in the mid troposphere temperature over the oceans as determined by the UAH MSU data. To better compare, I removed the slope in the seal level data, or simple removed the greater trend.

The first step was to remove the trend. In the above chart, the downloaded data is in blue. There are 665 data point, so I divided the rise by 665 and shifted each point by increasing the number of steps subtracted from the start. Nothing major, just removed the slope until the mean equaled the linear regression of the series.

After the series was detrended, I shifted the series and divided by common factor to get the series mean to equal the x-axis zero. This results in a scaled anomaly with not definite value. It is just scaled to provide a reasonable comparison of the detrended mean sea level orange and the UAH mid-troposphere oceans in blue which is in degrees C anomaly.

Since the Mean sea level data is recorded more often than the monthly UAH, I used a running mean of 5 mean sea level points to better compare the two without, hopefully, over smoothing the data. This post is just to briefly describe the detrending, if something really nifty turns up, I may get a little more detailed.