A time-domain approach to the total ozone time series and a test of its predictability within a univariate framework

The present study reports a univariate predictive model for Total Ozone (TO) concentration derived from Ozone Monitoring Instrument (OMI)/Aura observations. Using the Markovian approach through proper discretization method it has been observed that the second-order Markov Chain can represent the time series of TO Concentration. Considering daily data spanning from 2015 to 2019, consisting of 1593 daily TO concentration data. Identifying second order as the most suitable Markov Chain we have considered a second-order autoregressive model for univariate prediction of the time series. Finally, the prediction of TO concentration available from satellite remote sensing has been assessed statistically for its prediction accuracy. The prediction accuracy has been assessed through Willmott's Indices and Pearson Correlation Coefficient.