Abstract:
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: CO
2, CH
4 and N
2
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 CO
2
(∼24%), CH
4 (∼19%) and volcanic aerosols (∼23%) are the
primary contributors to the observed variations in GMTA.
While, UV (∼9%) and ENSO (∼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
