We present a new approach for analyzing local power law processes and apply it to temperature measurements from the upper atmosphere. We segment the data and use the wavelet scale spectrum to estimate the parameters of the power law, the scale factor and the exponent. These parameters vary from segment to segment. Part of this variation is due to the non-stationary of the data. Another part is due to estimation errors that depend on the segmentation. In this paper show how to remove effectively these segmentation dependent variations.
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