Oscillations and teleconnections - The Global Climate System: Patterns, Processes, and Teleconnections - page 39

Finally, many recent studies have focused on potential modulations of
ENSO by global warming resulting from anthropogenic changes to the
climate system. This emphasis has been complicated further, because natural
low-frequency climate variability must be seen against a background of
global warming, which itself may influence natural variability or affect
how that variability is observed or interpreted.
2.8.2 ENSO and low-frequency ''ENSO-like'' climatic
variability in mean sea level pressure, surface
temperature, and precipitation
The strength and state of the atmospheric component of the ENSO phenom-
enon have long been monitored by the Southern Oscillion Index (SOI) (see
Allan et al. 1996 for a history of Southern Oscillation measures and indices).
In its contemporary form, the SOI is derived from the normalized difference
in monthly atmospheric pressure between Tahiti and Darwin. In Figure 2.5 ,
monthly SOI values from 1866 to 2002 are smoothed with an 11-point
running mean, which reveals that El Ni˜o and La Ni˜a events vary in
magnitude, onset and cessation times, and in duration. This characteristic is
observed in all historical indices of ENSO (e.g. El Ni˜o 3, 3.4 and 4 region
sea surface temperatures), indicating that the phenomenon encapsulates a
''family'' of events.
A more objective way to analyse the nature of ENSO is through the use of
spectral and signal detection techniques, such as multi-taper method singular
value decomposition (MTM-SVD) (Mann and Park 1999 ). Figure 2.6 shows
the joint local fractional variance (LFV) spectrum generated by an MTM-
SVD analysis of surface temperature and mean sea level pressure (MSLP).
The temperature fields are based on Hadley Centre monthly gridded sea
surface temperatures (HadSST) and the Climatic Research Unit's land sur-
face air temperatures (Jones et al. 2001 ), which together form the HadCRUT
data set. MSLP fields are based on the latest version of the Hadley Centre
HadSLP data set derived from the initial work of Basnett and Parker ( 1997 ).
The temperature data are variance-corrected (Jones et al. 2001 ), and gaps
in both sets of fields are filled using reduced space optimum interpolation
(OI) (Kaplan et al. 1997 ) to give full 658 N-358 S coverage from 1871 to
1998. The resulting surface temperature and MSLP fields are designated as
HadCRUTv(OI) and HadSLP(OI).
Figure 2.6 reveals not only QB and LF climatic signals associated with the
''classical'' interannual ENSO phenomenon over the Indo-Pacific basin, but
also the presence of significant decadal-multidecadal signals in the climate
system which could influence and modulate ENSO (White and Tourre 2003 ).
Of these low-frequency fluctuations, a quasi-decadal signal operating around