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Pacific Interdecadal Climate Variability: Linkages between the Tropics and the North
Pacific during Boreal Winter since 1900
CLARA DESER, ADAM S. PHILLIPS, AND JAMES W. HURRELL
Climate and Global Dynamics Division, NCAR, Boulder, Colorado(Manuscript received 8 August 2003, in final form 20 February 2004)
ABSTRACTThis study examines the tropical linkages to interdecadal climate fluctuations over the North Pacific during
boreal winter through a comprehensive and physically based analysis of a wide variety of observational datasets
spanning the twentieth century. Simple difference maps between epochs of high sea level pressure over the
North Pacific (1900–24 and 1947–76) and epochs of low pressure (1925–46 and 1977–97) are presented fornumerous climate variables throughout the tropical Indo-Pacific region, including rainfall, cloudiness, sea surface
temperature (SST), and sea level pressure. The results support the notion that the Tropics play a key role inNorth Pacific interdecadal climate variability. In particular, SST anomalies in the tropical Indian Ocean andsoutheast Pacific Ocean, rainfall and cloudiness anomalies in the vicinity of the South Pacific convergence zone,
stratus clouds in the eastern tropical Pacific, and sea level pressure differences between the tropical southeast
Pacific and Indian Oceans all exhibit prominent interdecadal fluctuations that are coherent with those in sea
level pressure over the North Pacific. The spatial patterns of the interdecadal tropical climate anomalies arecompared with those associated with ENSO, a predominantly interannual phenomenon; in general, the two aresimilar with some differences in relative spatial emphasis. Finally, a published 194-yr coral record in the western
tropical Indian Ocean is shown to compare favorably with the twentieth-century instrumental records, indicating
the potential for extending knowledge of tropical interdecadal climate variability to earlier time periods.

1. Introduction
Numerous studies have documented interdecadal variations in climate over the North Pacific, including Trenberth and Hurrell (1994), Mantua et al. (1997, hereafterM97), Minobe (1997), Zhang et al. (1997), Dettinger etal. (2000), Chao et al. (2000), and Mantua and Hare
(2002). These interdecadal climate fluctuations are characterized by changes in the intensity of the large-scaleatmospheric circulation over the North Pacific during
winter, with impacts upon physical and biological conditions in the North Pacific Ocean and consequences forclimate downstream over North America, including air
temperature, precipitation, streamflow, and vegetation(Cayan et al. 2001). An index of the strength of thewintertime atmospheric circulation over the North Pacific is shown in Fig. 1 for the period 1899–2003. This‘‘North Pacific Index’’ (NPI; see Trenberth and Hurrell1994) is the area-averaged sea level pressure (SLP) for
the region 308–658N, 1608–1408W. Negative values correspond to a deeper-than-normal Aleutian low pressure
system, accompanied by enhanced westerly winds
across the central North Pacific and strengthened southerly (northerly) flow over the eastern (western) North
Corresponding author address: Dr. Clara Deser, Climate and Global Dynamics Division, NCAR, P.O. Box 3000, Boulder, CO 80307.
E-mail: cdeser@ucar.edu

q 2004 American Meteorological Society

Pacific; opposite conditions obtain for positive values.
The NPI also provides a proxy record of the Pacific–
North American (PNA) teleconnection pattern evident
in the middle troposphere (Trenberth and Hurrell 1994).
A striking feature of the NPI is the occurrence of extended periods, two to three decades in duration, withpredominantly positive (1900–24 and 1947–76) or negative values (1925–46 and 1977–2003). In addition to
the interdecadal fluctuations associated with the phasetransitions in 1925, 1947, and 1977, the NPI also exhibits considerable high-frequency variability: approximately 75% of the variance of the NPI occurs at periods
shorter than 20 yr (not shown).
What are the origins of interdecadal fluctuations in
the NPI? Several hypotheses have been proposed, including coupled ocean–atmosphere interactions within
the North Pacific (Latif and Barnett 1996; Robertson
1996) and with extensions to the tropical Pacific via an
atmospheric bridge (Barnett et al. 1999); air–sea interaction within the subtropical Pacific, with atmosphericteleconnections to the North Pacific as a by-product(Knutson and Manabe 1998; Kleeman et al. 1999;
McPhaden and Zhang 2002; Nonaka et al. 2002; Vimont
et al. 2001; Liu et al. 2002); extratropical–tropical interactions via an equatorward subsurface oceanic pathway and a return atmospheric bridge (Gu and Philander
1997; Deser et al. 1996; Schneider et al. 1999); and3110

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FIG. 1. The NPI from 1900 to 2003, normalized by its std dev (2.3hPa). The NPI is defined as the winter mean (Dec–Mar) SLP anomaly
averaged over the region 308–658N, 1608–1408W. The shaded curveis the raw time series and the thick black curve is a low-pass-filteredversion using a weighted seven-point running mean.

climate noise due to the integrating effect of stochastic
atmospheric variability by the North Pacific Ocean
mixed layer (Pierce et al. 2001; Newman et al. 2003)
and the thermocline (Frankignoul et al. 2000). Note that
the Tropics play an active role in some theories but notin others.
What do observational studies indicate about the roleof the Tropics in North Pacific interdecadal climate variability? Many have shown that the 1977 climate transition in the North Pacific is evident in the tropical Pacific where it resembles the pattern associated with thewarm phase of the El Niño–Southern Oscillation(ENSO) phenomenon (e.g., Nitta and Yamada 1989;
Trenberth and Hurrell 1994; Graham et al. 1994; Houghton et al. 1996; M97; Zhang et al. 1997; Garreaud andBattisti 1999). Less is known about the tropical signature of the earlier climate transitions in 1925 and1947. Figure 2, reproduced from M97, compares the
NPI with two canonical indices of ENSO: an equatorial
Pacific sea surface temperature (SST) index (the averageof SST anomalies in the region 68N–68S, 1808–908W)
from which the global mean SST anomalies have been
subtracted and a Southern Oscillation index (SOI) [theSLP difference between the tropical Indian/western Pacific and the remaining oceanic areas (see M97 for details)]. While the 1977 transition is evident in both
ENSO records, the 1925 and 1947 shifts are not as clear.
For example, the 1925 transition is absent from the SOI(which remains predominantly positive throughout thefirst half of the twentieth century), and the 1947 shift
is absent from the SST index. Furthermore, the trend of
the SST index during the first half of the twentieth century is in the opposite sense to that of the NPI. These
discrepancies raise the question, Was the 1977 transition
unique in terms of its connection to the tropical Pacific
as measured by the canonical ENSO indices, or are there
other regions of the Tropics that exhibit a more consistent linkage to the NPI during the twentieth century?
Preliminary evidence for a robust tropical connection

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FIG. 2. The (top) inverted NPI, (middle) inverted SOI, and (bottom)
eastern equatorial Pacific SST (the CTI) during 1900–96, normalized
by their respective std devs. The dashed vertical lines denote regime
transitions identified on the basis of the NPI (1925, 1947, and 1977).
This figure is reproduced from M97.

was presented by Minobe (1997), who showed that annually averaged SST anomalies in the tropical Indian
Ocean vary coherently with the NPI on interdecadal
time scales. A more systematic investigation of the relationship between the North Pacific and the Tropics ontime scales longer than ;6 yr was presented by Zhang
et al. (1997). They used linear regression analysis to
document the annually averaged SST and SLP anomaly
patterns associated with the dominant mode of global
SST variability (a structure that resembles the 1977 climate transition) after the effects of global warming andinterannual ENSO fluctuations are removed. They characterized the patterns as ‘‘ENSO-like’’ in view of theirgeneral similarity to those associated with the ENSO
cycle. Due to the statistical nature of their approach,
Zhang et al.’s analysis provides a general description ofPacific low-frequency variability weighted toward thedata-rich post–World War II period; it does not provide
a specific description of each of the climate transitionsindividually.
In this study, we revisit the issue of tropical linkages
to North Pacific interdecadal climate variability througha comprehensive and physically based analysis of a wide
variety of observational datasets spanning the twentiethcentury. As mentioned earlier, elucidating the role of
the Tropics is important from the standpoint of providing guidance for mechanistic studies of Pacific interdecadal climate variability. We present simple difference maps between epochs of high (1900–24 and 1947–76) and low (1925–46 and 1977–97) NPI for numerous
climate variables in the tropical Indo-Pacific region, including SST, SLP, air temperature, precipitation, andcloudiness, emphasizing physical consistency among
the various climatic parameters to build confidence inthe results. Comparing the three epoch differences(1900–24 minus 1925–46; 1947–76 minus 1925–46;
and 1947–76 minus 1977–97) allows us to assess those15 AUGUST 2004

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features that are common to all three and those that are
specific to a single case. All of the analyses are for theboreal winter season, December–March, unless noted
otherwise. This choice is dictated by the season of strongest atmospheric circulation variability over the North
Pacific (cf. Trenberth and Hurrell 1994) and establishedphysical mechanisms for atmospheric teleconnections
forced by deep convection in the Tropics (cf. Trenberth
et al. 1998; Alexander et al. 2002). A suite of selected
time series for key regions and climate parameters is
also developed to further characterize and synthesize
the tropical interdecadal variability that is coherent with
the NPI. Finally, we compare the patterns of tropicalclimate anomalies on interannual (ENSO) and interdecadal time scales, as in Garreaud and Battisti (1999;
note that their analysis is limited to the post-1958 period
and considers only annual averages). As far as we areaware, our study is the first to examine, in a comprehensive and systematic manner, the tropical Indo-Pacificclimate anomalies associated with interdecadal variations in the NPI during boreal winter.
The paper is organized as follows: The datasets andanalysis procedures are described in section 2. Epochdifference maps associated with the climate transitionsin 1925, 1947, and 1977 are presented in section 3 alongwith selected regional time series. The results are summarized and discussed in section 4, including a comparison to ENSO and a 194-yr paleoclimate reconstruction based upon a tropical Indian Ocean coral record(Cole et al. 2000).
2. Data and methods
Our strategy is to examine a suite of independentclimate variables for collective evidence of coherent
low-frequency variability over the Indo-Pacific sector.
We examine the period 1900–97 for all variables, although some datasets may nominally extend further
back in time and some may be updated beyond 1997.
Our choice of 1900 as the starting year for the analysis
is based upon data coverage considerations (cf. Woodruff et al. 1987).
For SST, we make use of two archives: the Comprehensive Ocean–Atmosphere Data Set (COADS; Woodruff et al. 1987) and the Lamont-Doherty Earth Observatory analyses (Kaplan et al. 1998). The COADS archive contains monthly data assembled into 28 latitude
3 28 longitude grid squares over the global oceans dating back to 1854 with a minimum of processing (e.g.,standard quality control procedures but no filling in of
missing data). The Kaplan et al. dataset contains monthly data on a 58 latitude 3 58 longitude grid over the
global oceans dating back to 1871 with substantiallymore processing than in COADS. The input data to the
Kaplan et al. analyses are from the Met Office historical
SST dataset (Folland and Parker 1995), which are similar to the COADS except that additional corrections
have been applied to empirically account for the arti-

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ficial rise in SST around 1940 associated with thechange in measurement technique from bucket to engine-intake temperatures. In the Kaplan et al. analyses,
missing grid squares have been filled in using an (empirical orthogonal function) EOF-based technique.
While this dataset has the advantage of increased spatial
coverage and smoother fields than in the COADS, it
may also introduce climate signals into areas devoid ofobservations or with limited data coverage. We haveverified that our findings based upon the Kaplan et al.
dataset are confirmed by the COADS.
For air temperature, we use the University of East
Anglia’s Climate Research Unit (CRU) dataset (Jones
1994), archived on a 58 3 58 latitude–longitude gridbased upon land stations and ships of opportunity. For
SLP, we make use of the COADS and an updated versionof Trenberth and Paolino (1980). The latter is based
upon daily historical analyses for the Northern Hemisphere poleward of 208N on a 58 3 58 latitude–longitudegrid. For precipitation, we use the gridded dataset (2.58
latitude 3 3.758 longitude) from the University of East
Anglia’s CRU (Hulme et al. 1998) based upon land
station records. We also make use of total cloud amountfrom the COADS as a proxy for precipitation over theoceans in regions where rainfall-producing cloud systems occur. (All datasets are available online at http://
www.cgd.ucar.edu/cas/guide/.)We formed monthly anomalies by subtracting thelong-term monthly means from each calendar month’smean. Winter (December–March) means were computedfrom the monthly anomalies, requiring a minimum of
1 month to define a winter average. To improve thereadability of the maps shown for COADS variables(SLP and cloudiness) and precipitation, linear interpolation (across gaps not exceeding three points in latitudeand five points in longitude) and weighted binomial
smoothing (three points in latitude and nine points inlongitude) were applied. All regional time series are
based on the raw (uninterpolated and unsmoothed) data.
We formed epoch difference maps requiring a minimumof 20% of the years within each period to have observations. All data were detrended prior to computationof the epoch difference maps. The statistical significanceof the epoch difference values is assessed by means ofa Student’s t test taking into account serial correlation(Zwiers and von Storch 1995; maps of the Student’s tvalues may be viewed online at http://www.cgd.ucar.
edu/;cdeser/PDVsupfig.html for each epoch difference
field). When discussing the epoch difference maps, weemphasize mainly those features that are significant at
the 95% confidence level.
Simple linear correlation analysis is used to quantify
the relationship between two time series. The statisticalsignificance of the resulting correlation coefficient isassessed according to a one-tailed Student’s t test taking
into account temporal autocorrelation following Trenberth (1984). A correlation coefficient that exceeds 0.36
in absolute value is significantly different from 0 at the3112

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FIG. 3. Epoch difference maps of winter SLP (contours) and land precipitation (color shading)for high-minus-low NPI regimes (years as indicated above each panel). The contour interval for
SLP is 1 hPa and negative contours are dashed. The precipitation scale (color bar at bottom of
figure) is in units of mm day 21 .

95% confidence level for data that have been temporallysmoothed with a three-point binomial filter. All of thecorrelation coefficients cited in this study exceed thisvalue unless otherwise noted and are maximum at 0 lag.
3. Resultsa. Extratropics
Atmospheric circulation variations associated with
the NPI have important consequences for climate over
the North Pacific and adjacent continents, as discussed
in the introduction. Figure 3 shows epoch difference
maps of winter SLP and precipitation for high-minuslow NPI regimes: 1900–24 minus 1925–46; 1947–76
minus 1925–46; and 1947–76 minus 1977–97. As expected, positive SLP values extend over a broad regionof the North Pacific in all three epoch difference maps,

with maximum values ;4 hPa in the vicinity of the
Aleutian Islands. Some differences are also apparent,
particularly in the orientation of the anomalous ridgeover the eastern North Pacific, which shows a pronounced southeastward extension in the most recent epoch difference map compared to the early one. The precipitation fields are similar for the three epoch differences, with positive values along the Asian coast (Japanand the Kamchatka peninsula), negative values in southern Alaska and the southwestern United States, and positive values over the Pacific Northwest. The similarity
among the maps, particularly the first and last, whichcontain no data in common, provides support for therobustness of the precipitation patterns. The banded
structure over North America is similar to that documented in Dettinger et al. (2000) based upon station
records of precipitation and streamflow. The precipita-

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FIG. 4. Selected regional climate records over the North Pacificand adjacent continents during 1899–2002 (1899–1998 for precipitation): the inverted NPI, the winter precipitation difference between
coastal Alaska and Japan, winter surface air temperature anomalies
over northwestern Canada and Alaska, and the leading PC time seriesof monthly SST anomalies over the North Pacific from M97 averaged
for the winter–spring season (see text for precise definitions). All
records are normalized and smoothed with a three-point binomial
filter. Each tick mark on the ordinate represents 1 std dev.

tion patterns are understandable in the context of thelarge-scale atmospheric circulation changes. For example, a weak Aleutian low (anomalously high SLP) is
accompanied by reduced low-level southerly flow overthe eastern North Pacific that decreases the moisture flux
into coastal Alaska, consistent with the precipitation response. Similarly, anomalous southerly flow over thewestern North Pacific associated with a weak Aleutian
low enhances the moisture flux into coastal Asia, in
agreement with the precipitation signal there. The weak
amplitude of the precipitation anomalies over the western United States in the earliest epoch difference map
compared to the later ones may be related to the lackof an appreciable SLP signal over the eastern North
Pacific in the former.
The time series of the precipitation difference between Alaska (558–608N, 1608–1358W) and Japan(32.58–47.58N, 1308–1468E) is shown in Fig. 4 together
with the NPI. The precipitation record exhibits a highdegree of similarity to the NPI; their correlation coefficient is 0.66 based upon data smoothed with a threepoint binomial filter and is a maximum at 0 lag. Theinterdecadal regimes evident in the NPI are also apparent in the precipitation difference record, demonstrating the impact of large-scale atmospheric circulation variations upon climate on both sides of the Pacific.
Figure 5 shows epoch difference maps for winter air
temperature and SLP. Interior Alaska and northwestern
Canada are cold when the Aleutian low is weak, consistent with the results of Minobe (1997) based upon

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individual station records. The western North Pacific
Ocean, on the other hand, is relatively warm, mainly inthe region of reduced westerly wind strength, consistent
with an equilibrated response to the underlying SSTchange (Fig. 6) due to diminished upward turbulent energy fluxes at the sea surface and cold advection byanomalous Ekman currents (cf. Miller et al. 1994). The
time series of air temperature over Alaska and northwestern Canada (518–708N, 1758–1008W) is shown in
Fig. 4. Like the precipitation difference record, it exhibits strong support for the interdecadal regimes evident in the NPI; the correlation coefficient between the
air temperature record and the NPI is 0.74 based upon
data smoothed with a three-point binomial filter and ismaximum at 0 lag.
Epoch difference maps for SST based upon the extended winter season, January–May, are shown in Fig.
6. We use the extended winter season for SST in viewof the fact that the correlation between the leading principal component time series of monthly SST anomalies
over the North Pacific [termed the Pacific (inter) decadaloscillation (PDO) by M97], and the winter NPI is strongest during these months (not shown). This result is
consistent with the notion that the response time forextratropical SST anomalies to atmospheric forcing ison the order of 1 month (Frankignoul 1985; Deser andTimlin 1997) and that once created, SST anomalies persist for many months due to the thermal inertia associated with a deep winter mixed layer (cf. Deser et al.
2003). However, epoch difference maps based upon December–March look very similar to those based upon
the extended winter season (not shown). The SST epoch
differences (Fig. 6) exhibit positive values over the central and western Pacific centered along ;408N and negative values in the eastern and far northern Pacific, similar to the leading EOF of monthly SST anomalies
shown in M97. Some differences are apparent between
the first and last epoch difference maps, particularly in
the Gulf of Alaska, where negative values are found in
the early one and positive values in the later one. Notethe overall similarity between the SST and marine airtemperature patterns shown in Fig. 5.
The January–May PDO record (obtained online at
http://tao.atmos.washington.edu/pdo) is shown in Fig.
4. This time series exhibits a greater proportion of interdecadal compared to interannual variability than do
the atmospheric indices shown in the figure, consistent
with the greater thermal inertia of the ocean mixed layercompared to the atmosphere (cf. Frankignoul and Hasselmann 1977; Deser et al. 2003). With the exceptionof the first decade of the twentieth century, the SST
record is highly coherent with each of the atmosphericindices; the correlation coefficient between the PDO record and the NPI is 0.64 (maximum at zero lag; 0.78
for the period 1911–97). The origin of the discrepancy
between the SST and atmospheric records during thefirst decade of the twentieth century requires further
study; however, it is unlikely that the atmospheric re-3114

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FIG. 5. As in Fig. 3 but for winter SLP (contours) and surface air temperature (color shading).
The air temperature scale (color bar at bottom of figure) is in units of 8C.

cords are erroneous in light of their mutual consistency.
More likely, in our view, is that the SST index contains
spurious signals due to the paucity of data during thisperiod, a speculation that deserves further investigation.
The 1925 and 1947 climate transitions in the NPI appear
to be preceded by shifts in the PDO index by a coupleof years. We caution against attaching too much significance to this apparent lead of the ocean relative tothe atmosphere since 1) the 1977 transition is simultaneous and 2) the NPI and PDO correlate most strongly
at 0 lag (not shown).
b. Tropical linkages
1) SST
To identify areas in the Tropics where SSTs vary coherently with the NPI on time scales longer than interannual, we show in Fig. 7 the correlation map between

the NPI and boreal winter SST anomalies based upon
the period 1900–97 using low-pass-filtered data to emphasize fluctuations with periods greater than ;9 yr (theresults are not unduly sensitive to the low-pass filter
used, provided that the cutoff is at periods longer thana few years). The strongest positive correlations (r .
0.6) are found in the tropical Indian Ocean extending
into the far western Pacific and outside of the equatorialzone in the eastern tropical Pacific. The correlations
within the Indian Ocean reach peak values of 0.8 along;108N. Weak and insignificant correlations are foundalong the equator east of 1808.
Another view of the SST anomaly patterns associatedwith interdecadal variations in the NPI is obtained from
epoch difference maps based on Kaplan et al. (1998)
data (Fig. 8, left). Negative values are found over mostof the tropical Indo-Pacific in all three epoch differences
except for weak positive values along the equator be-15 AUGUST 2004

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FIG. 6. As in Fig. 3 but for winter SLP (contours) and winter–spring (Dec–Mar) SST (color
shading). The SST scale (color bar at bottom of figure) is in units of 8C.

FIG. 7. Correlation map between the inverted NPI and boreal winter SST anomalies in thetropical Indo-Pacific, based on 9-yr low-pass-filtered data during the period 1900–97. The colorbar shows the scale for the correlation coefficients.

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FIG. 8. Epoch difference maps of boreal winter SST from (left) the Kaplan et al. (1998) dataset and (right) COADS.
The scale (color bar at bottom of figure) is in units of 8C. Note that the COADS data are not interpolated (white areas
denote missing data). The middle panel has been omitted for COADS due to the artificial increase in SSTs between
1940 and 1941 resulting from a change in observing practice. For the same reason, the earliest epoch difference map
based upon (top right) COADS excludes data from the period 1940–46.

tween the international date line and the coast of SouthAmerica in the earliest one. Note that although the magnitudes of the SST differences in the Indian Ocean are
relatively small (;0.2 K), they are highly significant
statistically due to the relatively weak background interannual variability. The opposing sign of the equatorial east Pacific ‘‘cold tongue’’ SST anomalies between the first and last epoch differences results in weakcorrelations with the NPI for the twentieth century as
a whole (recall Fig. 7). Other seasons also exhibit weak
positive values in the eastern equatorial Pacific for theearliest epoch difference (not shown). The COADS (Fig.
8, right) confirms the results based upon Kaplan et al.
(1998), indicating that this feature is not due to the way
in which the Kaplan et al. SST data were processed(recall section 2). Further support for the credibility of
the change in sign of the SST anomalies in the equatorial
cold tongue between the first and last epoch differencesis the similar behavior of SLP anomalies at Darwin,
Australia (not shown), a reliable index of the Southern
Oscillation (cf. Wright et al. 1988; Deser and Wallace1990). Indeed, the Darwin SLP record correlates withthe cold tongue SST index (CTI; SST anomalies averaged over the region 58N–58S, 1808–1108W; see Deserand Wallace 1990) at a level of 0.87 based upon averages
for boreal winter during 1900–46 (0.85 during 1947–97), attesting to the fidelity of both records.
Figures 7 and 8 indicate that SST fluctuations in thetropical Indian Ocean and the eastern Pacific north andsouth of the equator are associated with low-frequency
variations in the NPI. The SST anomaly time series forthe tropical Indian (108S–208N, 508–1258E) and southeast tropical Pacific (58–208S, 1408–908W) are shownin Fig. 9, together with the NPI (the northeast tropical
Pacific is similar to the southeast record, but is lesshighly correlated with the NPI, and the interdecadalregimes are less pronounced; not shown). Both records
correspond well with the NPI, with correlations of 0.67
and 0.65, respectively, based upon data smoothed witha three-point binomial filter (the correlations are a maximum at 0 lag). The interdecadal regimes evident in the
NPI are apparent in the tropical SST time series except
for the early portion of the first epoch in the southeast
Pacific record.

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FIG. 9. Selected regional climate anomaly records over the tropicalIndo-Pacific for boreal winter during 1900–97: the inverted NPI(through 2000), tropical Indian Ocean SST, southeast tropical Pacific
SST, rainfall south of the SPCZ, rainfall within the SPCZ, central
Pacific cloudiness, and tropical Indian Ocean minus southeast Pacific
SLP. Regions are defined in the text and shown in Figs. 11–13. All
records are normalized and smoothed with a three-point binomial
filter. Each tick mark on the ordinate represents one std dev. The
numeral to the right of each tropical index represents its correlation
coefficient with the inverted NPI.

2) PRECIPITATION
Although SST changes over the tropical Indian andsoutheastern tropical Pacific Oceans are coherent withinterdecadal variations in the NPI, SST anomalies per
se do not force atmospheric teleconnections to higher
latitudes; the release of latent heat in precipitating deep
convection is the direct forcing mechanism. Therefore,
we examine the tropical rainfall changes associated withinterdecadal variations in the NPI using station data overland and cloudiness as a proxy over the oceans. As
background to the epoch difference maps, the long-termmean precipitation distribution during boreal winterbased upon satellite measurements (Xie and Arkin 1997)
for the period 1979–97 is shown in Fig. 10 (top). The
highest rainfall amounts occur over the southwestern
tropical Pacific within the South Pacific convergencezone (SPCZ), along ;78N within the Pacific Intertrop-

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ical convergence zone (ITCZ), and over the equatorial
Indian Ocean, with maximum values (.12 mm day 21 )near 108S, 1708E. The long-term mean cloud amount
distribution from COADS for the same period is shownin Fig. 10 (bottom). In general, the regions of high rainfall correspond to areas of high total cloud cover (values.5 octas). In addition, large cloud amounts occur westof North and South America and west of Australia, areas
dominated by shallow nonprecipitating clouds (Klein
and Hartmann 1993), and poleward of 308N.
Epoch difference maps for land station precipitation
are shown in Fig. 11. Coherent rainfall changes are evident in the Tropics where data exist. In the most recent
epoch difference, negative values are found within andequatorward of the mean axis of the SPCZ and within
the ITCZ over the central Pacific, and positive values
obtain on the poleward flanks of the SPCZ and ITCZ
(the latter extends westward to the southern tip of India).
Over South and Central America, negative values arefound between 08 and 208S, and positive values arefound between 08 and 158N. Positive values are evident
in the Hawaiian Islands. The middle epoch differenceis similar to the latest one except for the region between
southern India and the Philippines where values are nearzero. Data coverage in the earliest epoch difference isseverely limited, but positive values are still evident
over the western Pacific, in keeping with the two later
maps. However, stations from the southern tip of India
eastward to the Philippines exhibit strongly negativevalues in the earliest epoch difference, in contrast to thepositive values found in the recent epoch difference.
We formed two regional precipitation indices for thetropical western Pacific, choosing areas with consistentsignals in all three epoch difference maps (see Fig. 11
for regional outlines); these indices are shown in Fig.
9. The precipitation index for the poleward flank of the
SPCZ (‘‘SPCZ Rain S’’) is highly correlated with the
NPI (r 5 0.69) and exhibits clear evidence of regime
transitions in 1947 and 1977, while the 1925 transition
occurred a couple of years in advance (note that thisindex extends back to 1908 only). The precipitation index for the main branch of the SPCZ (‘‘SPCZ Rain’’),which extends back to 1929 only, also shows coherent
behavior with the NPI (r 5 0.43), although the 1947
transition occurred several years too early.
3) MARINE CLOUDINESSTo extend the tropical rainfall analysis to oceanic areas where direct measurements are lacking, we employ
reports of total cloudiness from COADS as qualitative
proxy records of precipitation. Figure 12 shows a sideby-side comparison of the epoch difference maps forland-based precipitation and ship-based cloudiness in
the Tropics during December–March. In regions dominated by deep convective clouds such as the convergence zones, we expect a correspondence between precipitation and cloud cover; in areas where nonprecipi-

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FIG. 10. (top) Climatological distribution of boreal winter precipitation (mm day 21 ) based upon satellite
measurements during the period 1979–97. The contour interval is 2 mm day 21 , with values exceeding 4 mm
day 21 shaded (see color bar at right). (bottom) Climatological distribution of total cloud amount (octas) over
the oceans during boreal winter based upon COADS during 1979–97. The contour interval is 0.5 (0.25)
octas for values less than (greater than) 5 octas, with values exceeding 5 octas shaded (see color bar atright).

tating (e.g., low stratiform) clouds prevail, such as off
the west coasts of South and North America, no suchcorrespondence is expected. The epoch difference mapsof marine cloudiness generally support and extend theland-based rainfall results. In particular, reduced cloudiness over the central equatorial Pacific and enhanced
cloudiness over the western equatorial Pacific and along
the poleward flank of the SPCZ in the two recent maps
corroborate the station rainfall changes. The enhanced
cloud cover over the western Pacific extends into theeastern Indian Ocean. Increased cloudiness is also foundover the eastern tropical Pacific and west of Australia,
regions dominated by low-stratiform cloudiness. Positive cloudiness values in the vicinity of the Hawaiian
Islands corroborate the land-based rainfall measurements.
The earliest epoch difference is noisier than the othertwo due to reduced data coverage. Nonetheless, manyof the same patterns are discernible, including the oppositely signed anomalies on either side of the equatorin the central Pacific, some evidence of enhanced cloud
cover over the eastern tropical Pacific, and increased
cloudiness over the equatorial Indian Ocean. Diminished cloudiness is found over Indonesia and the South
China Sea, roughly consistent with the land-based rainfall results.
The time series of the difference between cloudinessanomalies north and south of the equator in the central
Pacific (regions are outlined in Fig. 12) is shown in Fig.
9. This cloudiness index is well correlated with the NPI(r 5 0.57) and exhibits the regime transitions of 1925,
1947, and 1977. Only the first few years of the record(1903–06; data are missing before 1903) are inconsistent
with the NPI (but consistent with the southeastern tropical Pacific SST index).
4) SLP
Epoch difference maps for SLP are shown in Fig. 13.
The tropical mean anomaly (258N–258S) has been removed from each grid box to enhance the zonal asymmetries. The most recent epoch difference exhibits below-normal values over the Indian and western Pacific
Oceans, and above-normal values over the eastern twothirds of the Pacific, reminiscent of the spatial patternassociated with the Southern Oscillation (cf. Trenberthand Caron 2000). The middle epoch difference is generally similar to the later one, except over the northern
Indian Ocean and South China Sea, where positive values are found in place of negative ones. Although noisierdue to reduced data coverage, the early epoch difference
resembles the middle one with the notable exception of
the area around Australia (;108–208S, 1158–1708E),
where positive values are found in place of negative
ones. Thus, the eastern pole of the Southern Oscillation
appears to extend considerably farther west in the early
epoch difference compared to the later ones, consistent
with the Darwin (128S, 1318E) SLP record discussed
above.
Taking into account the nonstationarity of the SLP

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patterns, we formed an index of the difference in SLP
between the southeastern tropical Pacific (78–298S,
1678–898W) and south Indian (78–298S, 578–1298E)
Oceans. Note that this index differs from the canonical
SOI, conventionally defined as the SLP difference between Darwin (128S, 1318E) and Tahiti (178S, 1498W)or regional averages centered around these stations (cf.
Deser and Wallace 1990). The new SLP index, shownas the last record in Fig. 9, correlates well with the NPI(r 5 0.52) and exhibits ‘‘regime transitions’’ in 1925
and 1977 (another shift occurs in 1945, two years before
that in the NPI). However, the SLP record is positive
during 1900–06, in disagreement with the NPI and theIndian Ocean SST index but consistent with the central
Pacific cloud and southeastern tropical Pacific SST timeseries.
5) AN OPTIMAL TROPICAL INDEX
Figure 9 provides collective evidence for a robust
tropical linkage to North Pacific interdecadal climate
variations during boreal winter based upon a diverse setof independent parameters spanning a broad region of
the Indo-Pacific. To summarize the suite of tropical climate records shown in Fig. 9, we computed the leading
EOF of the six normalized time series (note that the
NPI is not included in the EOF analysis). The leading
principal component (PC) time series, which accounts
for 64% of the variance compared to 16% for the second
PC, is shown in Fig. 14 together with the NPI (the six
input time series contribute nearly equally to the leading
EOF). All three regime transitions evident in the NPI(1925, 1947, and 1977) are present in the leading PCof the tropical records. The correlation coefficient between the two time series is 0.72, based upon datasmoothed with a three-point binomial filter; that is, halfof the variance of the NPI at periods longer than ;3 yr
is coherent with the leading tropical PC time series.
Power spectra of the detrended NPI and the leading
tropical PC time series are shown in Fig. 15. Both spectra exhibit enhanced variance at the lowest frequencies(periods . ;20 yr) and a deficit of power around 8–
14 yr. The tropical PC power spectrum also exhibits anenhancement of power at interannual frequencies (;4–7 yr). The increased power at interdecadal periods inboth records is significant at the 95% confidence levelbased upon a first-order autoregressive model null hypothesis. The cross-spectrum between the two records(Fig. 15, bottom) exhibits high squared coherence(;0.8) at periods .20 yr and between 4 and 7 yr [values
exceeding 0.6 (0.75) are statistically significant at the
95% (99%) confidence level].
4. Discussion
The earliest epoch difference (1900–24 minus 1925–46) exhibits some notable distinctions from the later two(1947–76 minus 1925–46 and 1947–76 minus 1977–

FIG. 11. Epoch difference maps of boreal winter precipitation overland. The precipitation scale (color bar at bottom of figure) is in unitsof mm day 21 . The black contours denote the 7.5 and 12 mm day 21
contours from the climatology. Rectangles outline regions used forthe time series shown in Fig. 9.

97), including a change in the sign of the SST anomalies
in the equatorial Pacific cold tongue, a westward shift(;508 of longitude) of the nodal line between positive
and negative SLP anomalies such that Darwin, Australia
is no longer located within the western pole of theSouthern Oscillation, and a change in the sign of therainfall/cloudiness anomalies over Borneo, the Philippines, and the South China Sea. These differences highlight that with only three realizations of interdecadal
variability to study, it is problematic to characterize any
single case as ‘‘canonical.’’ These differences also underscore that conventional ENSO indices such as theDarwin SOI and CTI fail as robust metrics of the interdecadal variability. Specifically, neither Darwin SLP
nor the CTI exhibit regime transitions in 1925 and 1947
that characterize the NPI, although they do portray the
1977 shift (Fig. 16; note that the Darwin SOI and CTI
records in this figure differ from the versions of the SOI

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FIG. 12. As in Fig. 11 but for (left) land station precipitation and (right) marine cloudiness. The cloudiness(precipitation) color bar is in units of octas (mm day 21 ). Rectangles outline regions used for the time series shownin Fig. 9.

and CTI shown in Fig. 2 from M97). With regard to
the change in sign of the rainfall anomalies over theregion encompassing Borneo, the Philippines, and theSouth China Sea between the early and recent epoch
differences, it is interesting to note that this change coincides with an alteration of the SLP anomaly signal
over the eastern North Pacific (recall Fig. 3); whether
the two are causally related remains to be elucidated.
Given the evidence for a tropical Indo-Pacific linkage
to interdecadal climate variations over the North Pacific,
it is natural to inquire whether there are any distinctions
between these connections and those that occur in as-

FIG. 13. As in Fig. 11 but for boreal winter SLP. The SLP color
bar is in units of hPa. Rectangles outline regions used for the timeseries shown in Fig. 9.

FIG. 14. (top) The inverted NPI and (bottom) the optimal tropicalindex (see text for definition) during 1900–97. Both records havebeen normalized and smoothed with a three-point binomial filter. Eachtick mark on the ordinate represents 1 std dev. The numeral to theright of the tropical index represents its correlation coefficient with
the inverted NPI.

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FIG. 16. (top) The inverted NPI, (middle) Darwin SLP, and (bottom)
eastern equatorial Pacific SST (the CTI) records during 1900–2002(1900–97 for the CTI). All records are for boreal winter and havebeen normalized and smoothed with a three-point binomial filter. Eachtick mark on the ordinate represents one std dev.

FIG. 15. Power spectra of (top) the NPI and (middle) the optimal
tropical index based upon detrended data for the period 1900–97(thick curves). The thin curves represent the power spectrum and its
95% confidence limits for a ‘‘red noise’’ null hypothesis based upona first-order autoregressive process with the same autocorrelation as
the observed time series (0.21 for the NPI and 0.32 for the tropicalindex). (bottom) Squared coherence between the NPI and the tropicalindex (thick curve). The 95% confidence level is 0.6 (thin horizontalline).

sociation with the interannual ENSO cycle. Figure 17
shows a comparison of the ENSO and interdecadal patterns of SST and cloudiness anomalies during boreal
winter. The ENSO patterns were obtained by regressing

the anomaly fields upon the CTI during 1947–97, andthe interdecadal patterns are those associated with the1977 transition. The two SST anomaly patterns (Fig.
17, top) are broadly similar, with positive values
throughout much of the tropical Indian and Pacific
Oceans and a dipole pattern in the North Pacific withpositive values in the east and negative values in thecenter. Some differences are also apparent, however;compared to ENSO, the epoch difference is characterized by a more equal weighting of the tropical Indianand Pacific anomalies, a broader meridional extent of
the eastern equatorial Pacific anomalies, and a moreequal weighting between the North Pacific and the Tropics. These results are in agreement with the findings ofGarreaud and Battisti (1999) based upon annual averages. However, note that in the earliest epoch difference,
the SST anomalies along the equatorial upwelling zone
are opposite in sign to those associated with ENSO (recall Fig. 8).
The interdecadal and ENSO anomaly patterns of total
cloud amount (Fig. 17, bottom) are also similar, withenhanced cloud cover over the western and central equatorial Pacific and diminished cloudiness over the far
western Pacific and the far eastern Indian Ocean. Reduced cloud cover is also found in the stratus regionsof the eastern tropical Pacific in association with awarmer sea surface. We note that the stratus cloud signal
is relatively more pronounced in the epoch difference
than in the ENSO regression map; the reasons for thisrequire further study. The ENSO cloudiness regression
pattern is consistent with the results of Park and Leovy(2004).
The short duration of the instrumental records limits
our ability to assess whether the interdecadal variability
sampled during the twentieth century is indicative of apreferred time scale or is part of a continuum of lowfrequency variability. Paleoclimate proxies based uponclimatically sensitive biological indicators are better

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FIG. 17. Comparison between (left) ENSO and (right) epoch difference patterns of (top) SST and (bottom) cloudiness anomalies during
boreal winter. The ENSO patterns are based upon linear regression of the anomaly fields upon the CTI during 1947–97, and the epoch
difference maps are obtained by subtracting the period 1947–76 from the period 1977–97. The color bar scale for the SST (cloudiness)anomalies is given on the rhs of the figure in units of 8C (octas). Note that the ENSO-related anomalies are per unit std dev of the CTI.

suited for addressing the issue of time scale due to theirlonger record lengths. Recently, Cole et al. (2000) presented a 194-yr record (1804–1994) of skeletal d18O
from a coral growing in the far western tropical Indian
Ocean at Malindi Marine Park, Kenya (38S, 408E). According to Cole et al. (2000), this record primarily reflects fluctuations in SST as opposed to salinity. The
detrended d18O time series is shown together with theleading tropical PC index in Fig. 18 (top). Interdecadal
variations in d18O are present during both centuries, andthose during the twentieth century are coherent with the
instrumental record (the correlation coefficient between
the d18O and PC time series is 0.62 based upon datasmoothed with a three-point binomial filter). The power
spectrum of the d18O record (Fig. 18, bottom) exhibitsa large proportion of variance at periods longer than
;30 yr, with relatively little variance at higher frequencies. The predominantly low-frequency characterof the d18O time series is reflected in the high year-toyear autocorrelation (0.64), a value considerably larger
than that for nearby SST anomalies or the tropical PC
record (;0.3). The higher persistence in the d18O record
may be partly biological in nature and/or due to the way
in which it was decimated to annual values (see Coleet al. 2000). Despite its duration, even the 194-yr d18O
record is not sufficiently long to assess whether the enhanced variance at low frequencies is indicative of awell-defined (albeit broadband) spectral peak at interdecadal periods or whether it reflects a red noise processwith no preferred time scale.
Although the Indian Ocean coral record shows a favorable match to the instrumental time series and provides evidence that the interdecadal fluctuations continue back at least 200 yr, other proxy records such as tree
ring chronologies from North and South America are
not as consistent in their behavior during the nineteenth
century (Villalba et al. 1999). The lack of agreement
among the proxy records suggests the need for additional paleoclimate indicators at key locations of Pacificinterdecadal variability. One such location suggested byour study is the tropical Indian and western Pacific
Oceans for both SST and precipitation-sensitive proxies.
5. Summary and interpretation
The analyses presented in this study support the notion that interdecadal fluctuations in the winter NPI during the twentieth century are associated with climate
variations over the tropical Indo-Pacific, in agreementwith earlier studies (e.g., M97; Minobe 1997; Zhang etal. 1997; Garreaud and Battisti 1999). Specifically, SSTs
in the tropical Indian and southeastern Pacific Oceans,rainfall and cloudiness along the SPCZ and over thecentral equatorial Pacific, cloudiness over the eastern
tropical Pacific, and the SLP difference between thetropical southeast Pacific and Indian Oceans collectively
exhibit variability that is coherent with the NPI on interannual and interdecadal time scales. This study has
extended our knowledge of Pacific interdecadal climate
variability by considering a more comprehensive suiteof climatic parameters in the tropical Indo-Pacific thanin previous studies and by focusing upon the relationships during boreal winter when the NPI is most active
and the influence of the tropical Indo-Pacific upon theatmospheric circulation over the North Pacific is wellestablished. In addition, our case study approach has
allowed for an assessment of the similarities and differences among the three cases of interdecadal variability sampled in the twentieth-century observational
record.
Our interpretation of the results is that variations in
the winter NPI at periods ranging from interannual tointerdecadal represent, in part, a remote response to rainfall anomalies over the tropical western and central Pacific via dynamical atmospheric teleconnection processes. A similar hypothesis is implicit in the recent
study of Newman et al. (2003; see also Trenberth andHurrell 1994), although their metric of tropical forcing

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Klecman et al. 1999; Zhang and McPhaden 2002). Indeed, these feedbacks may be essential for explaining
the origin of the interdecadal climate variations within
the tropical Indo-Pacific, a question not addressed in thepresent study and one that remains outstanding.
Acknowledgments. We wish to acknowledge helpful
discussions with many colleagues, including Drs. M.
Alexander, D. Battisti. M. Newman, K. Trenberth, andJ. M. Wallace. The comments of the editor and two
anonymous reviewers helped us to improve the presentation of the results. This work was supported by a grantfrom NOAA’s Office of Global Programs to C. Deser
and J. Hurrell.
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FIG. 18. (top) Time series of the detrended inverted d18O coral
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filter to facilitate visual comparison. (bottom) Power spectrum of the
d18O coral record based upon detrended data for the period 1801–1994. The thin curves represent the power spectrum and its 95%
confidence limits for a red noise null hypothesis based upon a firstorder autoregressive process with the same autocorrelation as theobserved time series (0.64).

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