Exploring Solar Signals: A Bayesian Approach to Developing a Composite Mg II Index Record
While various Mg II indices have been measured from satellite measurements of ultraviolet irradiance, they span different time-periods, platforms, and spectral resolutions. For these reasons, as well as differences in measurement uncertainty, the individual time series records do not agree. The objective of this study is to build a composite Mg II Index record from individual time series records of SORCE SOLSTICE (SOlar Radiation and Climate Experiment, SOLar STellar InterComparison Experiment), NOAA 16 SBUV (Solar Backscatter UltraViolet), and the University of Bremen Composite- which contains GOME (Global Ozone Monitoring Experiment), SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) data sets. An objective framework known as the Bayesian Positive Source Separation (BPSS) will be used to determine the most-likely probability distribution of the composite record.
A prerequisite first step in the Bayesian analysis is the definition of statistically independent signals, or “sources”. We applied the continuous wavelet transform to separate out the signals in each data set that correspond to known physical solar periods: the 24.7 day sidereal –the time it takes for the Sun's equator to complete one full rotation- period, 26.24 synodic –the time for a fixed feature on the Sun to complete one full rotation- period, the lifetime –approximately 3 months- of an active region, the 11 year Solar cycle denoted by a change between minimum and maximum periods of solar activity and appearances of magnetic features, and the 22 year Solar magnetic field reversal period. Other periodicities in the Mg II indices, not evaluated in this study, can be of solar origin or from uncorrected instrumental artifacts, including time or temperature dependencies in calibration corrections. We show results of the sum of these statistically independent components averaged over the individual records, producing a composite Mg II index that is contained within an uncertainty envelope and representative of the distribution of the signals over the three data sets. In ongoing work, the BPSS technique will be used to determine the maximally likely composite Mg II record, and future results will be compared to the derived uncertainty analysis of this work