Scaling Analysis of the Flare Index Data from Kandilli Observatory
Abstract
The daily time series Flare Index (FI) data of Northern Hemisphere, Southern Hemisphere and Total Disk for Solar Cycle 21- 23 and 24 up to Dec. 2014 has been pre-processed using a 2nd order exponential smoothing algorithm to remove orthogonal noise. The smoothed data in each case is processed for scaling analysis using Rescaled-Range Analysis as well as Finite Variance Scaling Method in order to search for the Hurst exponent. As the value of H obtained from our analysis lies in between 0 and 1, so it can be said that the signal may behave like Fractional Brownian Motion. Also, it is observed that H is less than 0.5 which indicates the data is anti-persistent in nature and it has a strong negative correlation within the signal. The value of H also indicates the oscillating features of the signal which might have some fundamental periodicities in the Suns atmosphere.
- Publication:
-
Long-term Datasets for the Understanding of Solar and Stellar Magnetic Cycles
- Pub Date:
- February 2018
- DOI:
- 10.1017/S174392131800114X
- Bibcode:
- 2018IAUS..340..161R
- Keywords:
-
- Flare Index Data;
- Exponential Smoothing;
- Rescaled-Range Analysis;
- Finite Variance Scaling Method;
- Hurst Exponent;
- Short Range Dependent memory