Solar Signature in Climate Indices

Abstract

The influence of solar/geomagnetic activity on climate variables still remains a fully unclarified problem, although many scientific efforts have been made to better understand it. In order to bring more information to this open problem, in the present study, we analyze the connection between solar/geomagnetic activity (predictors) and climate variables (predictands) by applying elements from information theory and wavelet transform analysis. The solar activity was highlighted by the Wolf number and geomagnetic activity was quantified by the aa index. For the climate variables, we considered seven Climate Indices (CIs) that influence atmospheric circulation on regional or global scales, such as the Greenland-Balkan Oscillation Index (GBOI), North Atlantic Oscillation Index (NAOI), Arctic Oscillation (AO), Atlantic Multidecadal Oscillation (AMO), Southern Oscillation Index (SOI), Bivariate ENSO Timeseries (BEST) and Trans-Niño Index (TNI). By using the difference between synergy and redundancy, a few cases were found where the two predictors can be considered together for CIs’ estimation. Coherence analysis through the wavelet transform for three variables, both through multiple and partial analysis, provides the time intervals and bands of periods, where the two considered predictors can be used together or separately. The results differ depending on the predictand, the season and the considered lags. Significant information is brought out by using the two predictors together, namely the summer season, for GBOI and NAOI, when the predictors were taken 2 years before, and the winter season, as AMO responds to the variations of both solar and geomagnetic activity after 4 years.

Keywords

• solar variability
• non-linear relationships
• synergy-redundancy
• wavelet analysis