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Identification and quantification of possible drivers of recent global temperature variability remains a challenging task. This important issue is addressed adopting a non-parametric information theory technique, the Transfer Entropy and its normalized variant. It distinctly quantifies actual information exchanged along with the directional flow of information between any two variables with no bearing on their common history or inputs, unlike correlation, mutual information etc. Measurements of greenhouse gases: $$\hbox {CO}_{2}$$ , $$\hbox {CH}_{4}$$ and $$\hbox {N}_{2}\hbox {O}$$ ; volcanic aerosols; solar activity: UV radiation, total solar irradiance ( TSI) and cosmic ray flux ( CR); El Niño Southern Oscillation ( ENSO) and Global Mean Temperature Anomaly ( GMTA) made during 1984-2005 are utilized to distinguish driving and responding signals of global temperature variability. Estimates of their relative contributions reveal that $$\hbox {CO}_{2}$$ ( $${\sim } 24 \%$$ ), $$\hbox {CH}_{4}$$ ( $${\sim } 19 \%$$ ) and volcanic aerosols ( $${\sim }23 \%$$ ) are the primary contributors to the observed variations in GMTA. While, UV ( $${\sim } 9 \%$$ ) and ENSO ( $${\sim } 12 \%$$ ) act as secondary drivers of variations in the GMTA, the remaining play a marginal role in the observed recent global temperature variability. Interestingly, ENSO and GMTA mutually drive each other at varied time lags. This study assists future modelling efforts in climate science. [ABSTRACT FROM AUTHOR]

A new model is proposed to forecast the peak sunspot activity of the upcoming solar cycle (SC) using Shannon entropy estimates related to the declining phase of the preceding SC. Daily and monthly smoothed international sunspot numbers are used in the present study. The Shannon entropy is the measure of inherent randomness in the SC and is found to vary with the phase of an SC as it progresses. In this model each SC with length Tcy is divided into five equal parts of duration Tcy/5. Each part is considered as one phase, and they are sequentially termed P1, P2, P3, P4, and P5. The Shannon entropy estimates for each of these five phases are obtained for the nth SC starting from n = 10 - 23. We find that the Shannon entropy during the ending phase (P5) of the nth SC can be efficiently used to predict the peak smoothed sunspot number of the (n + 1)th SC, i.e. Sn+1 max. The prediction equation derived in this study has a good correlation coefficient of 0.94. A noticeable decrease in entropy from 4.66 to 3.89 is encountered during P5 of SCs 22 to 23. The entropy value for P5 of the present SC 24 is not available as it has not yet ceased. However, if we assume that the fall in entropy continues for SC 24 at the same rate as that for SC 23, then we predict the peak smoothed sunspot number of 63±11.3 for SC 25. It is suggested that the upcoming SC 25 will be significantly weaker and comparable to the solar activity observed during the Dalton minimum in the past. [ABSTRACT FROM AUTHOR]