Geoscience Reference
In-Depth Information
Walker and Bliss
1932
) suggested that a simpler index of the NAO could be
based on the pressure difference between Iceland and the Azores (roughly repre-
senting the climatological centers of the Icelandic Low and Azores High). The util-
ity of this simple index based on SLP at two fixed locations was confirmed by J.
Wallace and D. Gutzler (
1981
) and has been widely adopted. There are a num-
ber of variants of the station-based NAO index using different stations and tech-
niques. Most commonly it is based on the difference in standardized station SLP, the
intent of the standardization being to reduce the dominance of the Iceland station.
J. Rogers (
1984
) used Ponta Delgadas, Azores, and Akureyri, Iceland, whereas J.
Hurrell (
1995
,
1996
) used Lisbon, Purtugal, and Stykkisholmur, Iceland. By con-
trast, van Loon and Rogers (
1978
) used an index based on the east-west contrast in
SLP across the subpolar north Atlantic.
A disadvantage of an SLP-based index based on two stations is that it may not
optimally capture the negative correlation between subtropical and subpolar SLP
centers. For example, under the positive (negative) NAO mode, the Icelandic Low
and Azores High are not just stronger (weaker), but exhibit poleward (equatorward)
shifts. The centers of maximum anticorrelation also shift seasonally. In recognition,
D. Portis et al. (
2001
) developed a seasonally and geographically varying “mobile”
index of the NAO, defined as the difference between normalized SLP anomalies at
the locations of maximum negative correlation between the subtropical and sub-
polar North Atlantic SLP. They found that the subtropical center shifts westward
and northward into the central North Atlantic as the annual cycle passes through
spring and summer. When tracked with their mobile NAO index, the NAO nodal
correlations are only slightly weaker in the summer-half of the year as opposed to
the winter half. Their index also shows that the NAO is strongest in March, followed
by February and January.
Other investigations have made use of empirical orthogonal function (EOF) or
rotated principal component (PC) analyses. These approaches have been applied
variously to a North Atlantic domain or the Northern Hemisphere, using gridded
SLP or tropospheric height fields (e.g., Trenberth and Paolino,
1980
; Wallace and
Gutzler,
1981
; Barnston and Livezy,
1987
; Thompson and Wallace,
1998
,
2000
;
Hurrell et al.,
2003
). The NAO emerges very clearly as the leading mode of var-
iability in the North Atlantic study of Trenberth and Paolino (
1980
), accounting
for 34 percent of the variance in winter SLP. The first EOF from that study, repro-
duced in
Figure 4.16
, shows the dipole structure of the NAO. Similar results can be
obtained through composite analysis of SLP fields for extremes of the NAO index.
EOF or PC approaches are usually considered more robust than station-based indi-
ces in that they use information from the entire atmospheric field to extract the dom-
inant modes of variability. On the other hand, from a practical viewpoint, individual
station time series from which indices can be compiled are available for a longer
time period than are gridded fields.
NAO time series for winter (December-March) through 2002, based on three dif-
ferent approaches using SLP data (station index, PC1 of the Atlantic sector, PC1 of
the Northern Hemisphere) are presented in
Figure 4.17
. As mentioned, the advantage
