To remove any background linear variation in a time series of data by first computing a linear regression (such as least squares best fit) to the data, and then subtracting it from the data. This aspect of conditioning data helps to remove red noise associated with a long-wavelength or long-period signal that is inadequately sampled because it is longer than the total data period of sampling.