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Patching Cn2 time series data holes using principal component analysis

Measurements of Cn2 time series using unattended commericial scintillometers over long time intervals inevitably lead to data drop-outs or degraded signals. We present a method using Principal Component Analysis (also known as Karhunen-Loève decomposition) that seeks to correct for these event-induced and mechanically-induced signal degradations. We report on the quality of the correction by examining the Intrinsic Mode Functions generated by Empirical Mode Decomposition.