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Tropical–North Pacific Climate Linkages over the Past Four Centuries*
ROSANNE D’ARRIGO,⫹ ROB WILSON,# CLARA DESER,@ GREGORY WILES,& EDWARD COOK,⫹RICARDO VILLALBA,** ALEXANDER TUDHOPE,# JULIA COLE,⫹⫹ AND BRADDOCK LINSLEY##⫹ Tree-Ring Laboratory, Lamont-Doherty Earth Observatory, Palisades, New York# School of GeoSciences, Grant Institute, Edinburgh University, Edinburgh, United Kingdom@ NCAR, Boulder, Colorado& The College of Wooster, Wooster, Ohio** IANIGLA, Mendoza, Argentina⫹⫹ Department of Geosciences, The University of Arizona, Tucson Arizona## Program in Geological Sciences, Department of Earth and Atmospheric Sciences, The University at Albany,
State University of New York, Albany, New York
(Manuscript received 2 December 2004, in final form 6 May 2005)
ABSTRACT
Analyses of instrumental data demonstrate robust linkages between decadal-scale North Pacific andtropical Indo-Pacific climatic variability. These linkages encompass common regime shifts, including thenoteworthy 1976 transition in Pacific climate. However, information on Pacific decadal variability and thetropical high-latitude climate connection is limited prior to the twentieth century. Herein tree-ring analysis
is employed to extend the understanding of North Pacific climatic variability and related tropical linkages
over the past four centuries. To this end, a tree-ring reconstruction of the December–May North Pacificindex (NPI)—an index of the atmospheric circulation related to the Aleutian low pressure cell—is presented (1600–1983). The NPI reconstruction shows evidence for the three regime shifts seen in the instrumental NPI data, and for seven events in prior centuries. It correlates significantly with both instrumental
tropical climate indices and a coral-based reconstruction of an optimal tropical Indo-Pacific climate index,
supporting evidence for a tropical–North Pacific link extending as far west as the western Indian Ocean. The
coral-based reconstruction (1781–1993) shows the twentieth-century regime shifts evident in the instrumental NPI and instrumental tropical Indo-Pacific climate index, and three previous shifts. Changes in thestrength of correlation between the reconstructions over time, and the different identified shifts in both
series prior to the twentieth century, suggest a varying tropical influence on North Pacific climate, withgreater influence in the twentieth century. One likely mechanism is the low-frequency variability of the El
Niño–Southern Oscillation (ENSO) and its varying impact on Indo-Pacific climate.

1. Introduction
The existence of North Pacific interdecadal climatic
variability is well documented over the past century
from analyses of instrumental data (e.g., Mantua et al.
1997; Mantua and Hare 2001; Labeyrie et al. 2003). One
possible mechanism for this variability is internal forcing of the northern North Pacific climate system (e.g.,* Lamont-Doherty Earth Observatory Contribution Number
6799.
Corresponding author address: Rosanne D’Arrigo, Tree-Ring
Laboratory, Lamont-Doherty Earth Observatory, 61 Rte. 9W,
Palisades, NY 10964.
E-mail: rdd@ldeo.columbia.edu© 2005 American Meteorological Society

Nakamura et al. 1997). Alternatively, an increasing
number of analyses also indicate coherent relationships
between indices of higher-latitude Pacific and tropicalclimate (Trenberth and Hurrell 1994; Minobe 1997;
Zhang et al. 1998), leading some to conclude that Pacific decadal variability (PDV) is a basinwide phenomenon that originates in the Tropics (Garreaud and Battisti 1999). Recently, Deser et al. (2004) found further
support for the concept that the Tropics play a key rolein North Pacific interdecadal climatic variability using acomprehensive, physically based analysis of twentiethcentury observational datasets [including tropical IndoPacific sea surface temperatures (SSTs), rainfall,cloudiness, and sea level pressure (SLP)]. This evidence
includes identification of robust linkages between interdecadal fluctuations (e.g., twentieth-century regime
shifts) in the North Pacific index (NPI; Trenberth and5254

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Hurrell 1994) and several key tropical climate indices inboreal winter.
The dominant mode of wintertime atmospheric circulation variability over the North Pacific is characterized by changes in the strength of the Aleutian low
pressure cell. The NPI is a robust index of this mode,
which is used to track the state of cool season North
Pacific SLP variability. It is defined as the areaaveraged SLP over the region 30°–65°N, 160°E–140°W(Trenberth and Hurrell 1994). The NPI is closely associated with the Pacific–North America (PNA) teleconnection pattern, the dominant pattern of midtropospheric circulation variability, which extends from theNorth Pacific downstream over North America (Trenberth and Hurrell 1994). Negative (positive) NPI values
correspond to a deeper-than-normal (less intense)
Aleutian low, strengthened southerly (northerly) flow
over the eastern Pacific, and warmer (cooler) temperatures along the western coast of North America (Trenberth and Hurrell 1994). The NPI shows clear evidence
for multidecadal climate regimes, with primarily positive values from 1900–24 and 1947–76, and primarily
negative values from 1925–46 and 1977–2003. These regimes are also evident in the Pacific decadal oscillation(PDO), the dominant mode of Pacific SST variability
north of 20°N (Mantua et al. 1997). Particularly noteworthy is the pronounced 1976 regime shift (Ebbesmeyer et al. 1991; Graham 1994), which has also been
identified in tropical Pacific climate and ENSO-related
data. Other twentieth-century regime shifts are not asclearly related to ENSO (Deser et al. 2004).
Limitations in our understanding of the behavior of
PDV result, in part, from the shortness of the instrumental record, while similar limitations in understanding of the causes and mechanisms of PDV are related toa broader suite of process issues (e.g., tropical versus
extratropical air–sea interactions, lagged dynamic
ocean responses to atmospheric forcing, etc.). There
are not sufficient instrumental data to support any of
the hypothetical models proposed to explain PDV, nor
to determine how representative the twentieth-century
changes are relative to long-term behavior unforced bygreenhouse gases. Additional paleoclimate indices forcertain key data-sparse locations (e.g., the tropicalIndo-Pacific and western equatorial Pacific regions) are
therefore needed for studies of PDV and identificationof North Pacific–tropical linkages (Deser et al. 2004). A
significant relationship between a 194-yr ␦18O coral record for the far western Indian Ocean [1801–1994, Malindi Marine Park, 3°S, 40°E (Cole et al. 2000); seebelow], and an optimal tropical climate index [the leading principal component of six normalized tropical cli-

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mate series, explaining 64% of the overall variance(Deser et al. 2004)] suggested the potential for extending available information on tropical–North Pacificlinkages into the past.
Herein we use tree-ring records from the land areas
surrounding the North Pacific as well as coral dataspanning the tropical Indo-Pacific region to extend ourknowledge of tropical–North Pacific interdecadal climate linkages prior to the instrumental period. Recent
efforts have substantially improved the spatial and temporal coverage of well-dated, high-resolution proxyrecords (tree rings and corals) for these regions [e.g.,
for the North Pacific: Davi et al. (2002), D’Arrigo et al.
(2004), and Jacoby et al. (2004); e.g., for the Tropics:
D’Arrigo et al. (1994), Charles et al. (1997), Isdale et al.
(1998), Guilderson and Schrag (1999), Cole et al.
(2000), Linsley et al. (2000), Urban et al. (2000), Cobb
et al. (2001), Tudhope et al. (2001), Charles et al.
(2003), and Linsley et al. (2004); also see Labeyrie et al.
(2003)]. Yet, coverage is still very limited for vast areas,
particularly for the Tropics where the existing tree-ringdata network is sparse but expanding (more information available online at http://www.ldeo.columbia.edu/
res/fac/trl.). Regardless, the presently available data
coverage allows initial evaluation of large-scale atmosphere–ocean circulation changes across much of the
Indo-Pacific region over the past several centuries.
Tree rings have been used previously to reconstruct
features of North Pacific decadal climate variability,
including SSTs (D’Arrigo et al. 1999), coastal air temperatures (Wiles et al. 1998), and the PDO (Biondi etal. 2001; D’Arrigo et al. 2001; Gedalof and Smith 2001;
Cook 2003). Yet, there have been few attempts to describe long-term relationships between North Pacificvariations and aspects of tropical climate prior to the
instrumental period. Such efforts have the potential toyield insights of much value for the modeling and prediction of Pacific decadal variability (e.g., Percival et al.
2001). In perhaps the first such studies, Villalba et al.
(2001, 2003) demonstrated correlations between treering records from western North and South America,
and related these records to Pacific basin SSTs. Evanset al. (2001) observed coherency between tree-ringrecords from the western Americas and a coral Sr/Ca
record from Rarotonga in the equatorial Pacific, andGraham (2004) related tropical South American proxies to those from the southwestern United States. Gedalof et al. (2002), by combining five proxy records(coral and tree-ring based) of North Pacific climate
variability, found evidence for basin-scale coherence in
PDV and also for a robust tropical–extratropical link.
In this paper we continue the examination of the North

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FIG. 1. Map of the North Pacific region showing locations of tree-ring sites (yellow) used as candidate predictors of the NPI. Sites
in red are those included in the regression model used to reconstruct the NPI. Some dots represent more than one site.

Pacific–tropical climate connection using an extended
tree-ring-based time series of North Pacific atmospheric circulation and a large-scale coral dataset fromacross the low-latitude Indo-Pacific region. In so doing,
we further explore the large-scale linkages of decadal
variability prior to the twentieth century.

2. NPI tree-ring reconstruction
To develop an extended record of North Pacific decadal-scale atmospheric circulation changes that could
readily be compared to tropical climate indices, we reconstructed the NPI of Trenberth and Hurrell (1994)
using tree-ring data. To this end, 67 chronologies fromthe land areas surrounding the North Pacific rim (Fig.
1) were used as candidate predictors in principal component (PC) regression analysis (Cook et al. 1999). The
chronologies selected for modeling of the NPI are all
mainly temperature-sensitive records of coniferous tree
species from the northeastern North Pacific, primarily
from the Gulf of Alaska and Pacific Northwest regions.
Some of these records were used previously to reconstruct the PDO (D’Arrigo et al. 2001; Cook 2003).
Tree-ring records from precipitation-sensitive lowerlatitude western North American sites, also used to reconstruct the PDO (D’Arrigo et al. 2001; Cook 2003),
were not included in the NPI modeling as we wereprimarily interested in identifying distinct linkages between North Pacific and tropical climate. Using the
1900–83 common period, correlations were calculated
between the chronologies and the monthly NPI over an
18-month interval beginning in May of the year prior to
growth and ending in October of the current growthyear (Fritts 1976). Of the 67 chronologies, 18 (red dots
in Fig. 1) correlated significantly at or above the 90%

significance level for the winter/spring months of the
NPI and were thus retained for further analysis. From a
principal component analysis (PCA), only those eigenvectors showing eigenvalues ⬎1 were retained for regression (Cook and Kairiukstis 1990).
To develop the longest possible reconstruction, weused a nested approach (e.g., Meko 1997; Cook et al.
2002) in which the number of available chronologies
declines back in time (Fig. 2). For this purpose, a PC
regression model was first developed using all of theavailable data, resulting in the most robust reconstruction. A second nest is based on the next common periodof all series with the shortest series removed, and so on.
For each nested subset of variables, a reconstruction isdeveloped and separate calibration and verification statistics are made for both early (1900–40) and late(1941–83) periods of calibration. This allows for a goodmeasure of the loss in signal fidelity in the reconstruction back in time. To create the final reconstructed timeseries, the relevant “sections” from each full-period(1900–83) calibrated nested model are spliced together.
This is done after the mean and variance of each nested
time series are adjusted to that of the fully replicatednested reconstruction so that there are no changes invariance in the time series due to weakening in themodeled signal. For this study, three nested subsets
were used to generate the NPI tree-ring reconstruction(starting from 1600, 1629, and 1762, respectively). Due
to lower levels of statistical validation, the earlier partof the reconstruction, based on less data from the least
replicated nest, should thus be viewed with greater uncertainty. The best regression model was found for the
December–May season (Fig. 2a), which accounts for
41% of the variance in the instrumental NPI for themost replicated nest. Most of the variance in the NPI is

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FIG. 2. Tree-ring based NPI reconstruction. (a) Actual and estimated Dec–May NPI for the 1900–83 calibration period: Adf ⫽adjusted degrees of freedom. The degrees of freedom were adjusted to account for the autocorrelation in the data so that significanceof the correlations could be assessed (Trenberth 1984). (b) Reconstruction of the Dec–May NPI from A.D. 1600–1983 based on North
Pacific tree-ring data. The highlighted phase shifts were identified using intervention analysis (significant at the 90% confidence limit).
Asterisk (*) indicates the 1976 shift was identified in the actual Dec–May NPI series as there are too few observations after 1976 to
identify a significant shift in the reconstruction. (c) Nested calibration (1900–83 ar 2) and RE results through time. The ar 2 is the levelof explained variance after adjustment for degrees of freedom. The RE is a measure of the common variance between the actual series
and the tree-ring estimates, for which a positive value indicates skill in the regression. RE1 (RE2) shows the RE value for the 1941–83(1900–40) verification period after calibration on the 1900–40 (1941–83) period, calculated for each nest. (d) The sign test (ST) ratio(positive agreements divided by negative agreements) verification results through time. The ST, which measures how well the reconstructed estimates track the year to year variations in the instrumental data (Fritts 1976; Cook and Kairiukstis 1990), shows that all
nested models pass verification.

in the colder months, and this selected season includes
the December–March period of strongest atmosphericcirculation variability in the North Pacific (Trenberthand Hurrell 1994). The correlation between the December–May and December–March seasons is 0.95
over the 1900–2002 period.
Calibration and verification tests (Cook and Kairiukstis 1990) indicate that the reconstruction model provides reasonably valid estimates of past NPI variability(Figs. 2c and 2d). Cross-validation tests include positive
reduction of error (RE) statistics, which indicate pre-dictive skill in the reconstruction (Gordon and LeDuc1981) and significant sign test (ST; Fritts 1976) results,
that indicate that the tree-ring estimates successfully
capture the interannual variability present in the instrumental NPI data. The tree-ring based December–May
NPI reconstruction (TR NPI), dating from A.D. 1600–
1983, is presented in Fig. 2b. An intervention analysis(Box and Tiao 1975), which is essentially a two-sample
t test that can be applied to autocorrelated data, wasapplied to the NPI reconstruction to identify significant
shifts in the series. This analysis was made by compar-

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D’ARRIGO ET AL.

ing the mean values of 15-yr periods on either side ofeach year throughout the series. While interventions
can take many forms, we tested only for step interventions. This method is similar to that used by Mantua etal. (1997) and Gedalof and Smith (2001) for identifying
shifts in the PDO.
The NPI reconstruction successfully tracks the
known regime shifts (1924/25, 1946/47, and 1976/77)
seen in the instrumental NPI during the twentieth century (Trenberth and Hurrell 1994; Deser et al. 2004),
although the mid-1920s shift appears to predate the instrumental record by 2 yr. Although the quality of the
TR NPI decreases back in time (Fig. 2c), it indicatesthat prior to the instrumental period there are decadalscale variations that may also represent regime shifts.
Significant “shifts” (at the 90% confidence limit) are
identified in 1627, 1695, 1762, 1806, 1833, 1853, and1891. Comparison of the three nested time series (notshown) indicates that the identified 1627 and 1762
shifts, which roughly equate to the start of the two recent nests, are not artifacts of the nesting procedure.
To help assess the relationship between the TR NPI
reconstruction and Indo-Pacific climate, Figs. 3a and 3b
present maps that compare the spatial correlations ofDecember–May SST anomalies (Kaplan et al. 1998)
with the tree-ring reconstructed and instrumental NPI
records for the common interval 1900–83. The correlations are based on 9-yr low-pass-filtered data to emphasize the relationships on decadal time scales. The maps
show similar patterns of December–May SST anomalies, indicating that the reconstruction captures thedominant spatial features of the North Pacific–tropicalclimate relationship during this period.

3. Coral-based Indo-Pacific Ocean tropical index
reconstruction
As a logical extension of the analysis made by Deseret al. (2004), we next compared the TR NPI reconstruction to tropical climate proxy data to extend our information on tropical–North Pacific linkages prior to thetwentieth century. As noted, Deser et al. (2004) presented significant correlations between an ␦18O coral
record from the western Indian Ocean [Malindi Marine
Park, 3°S, 40°E (Cole et al. 2000)] and an optimal tropical climate index (OTI) based on instrumental Pacificand Indian Ocean SST, rainfall in the South Pacificconvergence zone, cloud cover in the central equatorial
Pacific, and SLP in the Pacific and Indian Oceans.
Herein, we expand upon this analysis and identify 12
coral proxy records from the Pacific and Indian Oceansthat correlate significantly with this index. We then develop an independent large-scale reconstruction of the
OTI from these records for comparative analysis.

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From the National Oceanic and Atmospheric Administration (NOAA) Paleoclimatology Program andunpublished sources, there are more than 50 annually
to monthly resolved coral records that are ⱖ100 yr inlength, representing a variety of coral proxy types (e.g.,
calcification, ␦18O, Sr/Ca, U/Ca, Ba/Ca, and fluorescence data). Correlation analysis of annual (January–
December) time series identifies 12 coral records thatcovary with the OTI at or above the 95% significancelevel (Fig. 3c). Eleven of these coral time series arerecords of skeletal ␦18O (a proxy that records the combined effects of temperature and salinity changes during the growth of the coral). The other coral time series(HVI) is a record of skeletal fluorescence, which in thiscase is viewed as a rainfall and river runoff proxy. Despite the potential additional influence of salinitychanges on coral skeletal ␦18O, most of these records
are reported to portray significant correlations with local SSTs (although there are also salinity effects). All
are also noted to show strong synoptic-scale climate
signal relationships with either ENSO or its teleconnections (Allan 2000). It is therefore not surprising, due tothe noted large-scale coherence of decadal-scale variability across the Indo-Pacific region (e.g., Trenberthand Hurrell 1994; Mantua et al. 1997; Deser et al. 2004),
that these records correlate well (based on unfiltereddata) with the OTI. The locations of these 12 coral
series clearly fall within the regions where SST anomalies are well correlated (positively) with the OTI; notealso that the sign (negative) of the coral record correlations with the OTI (Fig. 3) is consistent with those of
the inverse relationship between coral ␦18O and SST.
Following the same method utilized for the development of the TR NPI reconstruction, nested principal
component regression was used to develop an independent coral-based OTI reconstruction. The coral OTI
reconstruction is compared with the actual OTI series
in Fig. 4a. Fifty-six percent of the OTI variance is explained by the most replicated nest, which decreases to
33% for the 1781–1800 three-series model (Fig. 4c).
Split-period calibration–verification of each nested
model [calibration made over the 1900–43 (1944–86)
period and verified over 1944–86 (1900–43)] indicatesmodel skill with positive RE values for all nests back to1801 (Fig. 4c). The sign test marginally fails for the
1900–43 period for the nests prior to 1881. It is likelythat the failure of the reconstruction prior to 1801 reflects the fact that the Malindi (MAL) record, from thefar western Indian Ocean (Fig. 3c), is not in the input
matrix prior to this period. The earliest three-series
nest did not utilize PC regression as the use of PCA on
so few records is not a valid approach. Rather, the se-5258

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FIG. 3. Spatial correlation plots. (a) Reconstructed and (b) actual NPI (inverted sign) compared to
Dec–May Pacific and Indian Ocean SST fields (Kaplan et al. 1998) for 1900–83. (c) OTI (Deser et al. 2004)
compared to annual SST anomalies over the period 1900–97. The contour interval is 0.2. The contoured
correlations only provide a guide to indicate that we are capturing the large-scale signal. All spatial
correlations were made using low-pass-filtered (9 yr) data. Coral records are shown that correlate significantly (95% confidence limit), using unfiltered data, after taking into account autocorrelation in the nonfiltered time series (Trenberth 1984). Correlations for the 1900–86 period are shown in parentheses: MAL,
Malindi (1801–1992; Cole et al. 2000); MAH, Mahe, Seychelles (1846–1995; Charles et al. 1997); HVI,
Havannah Island (1644–1986, Isdale et al. 1998); NAI, Nauru Island (1897–1994; Guilderson and Schrag1999); MAI, Maiana (1840–1994; Urban et al. 2000); TAR, Tarawa (1894–1988; Cole and Fairbanks 1990;
Cole et al. 1993); PAL, Palmyra Island (1886–1996; Cobb et al. 2001); FIJ, Fiji (1781–1996; Linsley et al.
2004); RAR, Rarotonga (1726–1996; Linsley et al. 2004); JAR, Jarvis (1850–1998; A. W. Tudhope et al.
2005, unpublished manuscript); SUW, Suwarrow Atoll (1881–1998; A. W. Tudhope et al. 2005, unpublishedmanuscript); and CLP, Clipperton Atoll (Linsley et al. 2000). All coral records are ␦18O except HVI, whichis fluorescence.

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FIG. 4. Coral-based reconstruction of the Deser et al. (2004) OTI. (a) Actual and estimated OTI series for the 12 coral series nested
PC regression model; adf is the adjusted degrees of freedom. The degrees of freedom were adjusted to account for the autocorrelationin the data so that significance of the correlations could be assessed (Trenberth 1984). (b) The full coral OTI reconstruction. The
highlighted phase shifts were identified using an intervention analysis (significant at the 90% confidence limit). (c), (d) As in Fig. 2
except full calibration is over the 1900–86 period and split-period calibration–verification are made over the 1900–43 and 1944–86
periods. The reconstruction is well calibrated and verified back to 1801, except that the ST ratio is slightly below the 95% confidence
limit for the 1900–43 verification period prior to 1881. The earliest three-series nest did not utilize PC regression. Rather, the series wereentered into the regression model using a stepwise process.

ries were entered into the regression model using a
stepwise process.
Intervention analysis of the OTI reconstruction successfully identifies the three climatic shifts of the twentieth century (Trenberth and Hurrell 1994; Deser et al.
2004), although it should be noted that the significanceof the shifts at 1923 and 1942 are weaker than that for
1976 ( p ⬍ 0.05) and are only significant at the 90%
confidence limit. Prior to the known twentieth-century
shifts, the intervention analysis identifies significant
shifts at 1825, 1879, and 1894 (Fig. 4b). As with the TR
NPI series, less confidence is advised when interpretingthese earlier shifts, as the fidelity of the reconstruction
decreases back in time (Figs. 4c and 4d) due to thedecreasing number of coral records (Fig. 4b).

4. Comparison of tropical and extratropicalreconstructions
Figure 5 compares the TR NPI and coral OTI reconstructions. Running correlations show that the two series correlate significantly (note that the sign of the OTI
reconstruction has been reversed) for most of the twentieth century, but prior to the calibration period correlations are generally not significant, except for the earlynineteenth century where coherence is similar instrength and sign to that of the twentieth century. We
note that the period of weaker correlation (centered in
the mid- to late nineteenth century) appears to coincidewith a period of generally weaker interannual variancein the OTI reconstruction, suggesting that this may be a

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FIG. 5. (top) Comparison of the TR NPI and coral OTI reconstructions. Both series have been normalized to their common period
while the sign of the coral OTI series has been reversed to aid comparison. (bottom) Running 51-yr correlations between both series.
The 95% confidence limits have been adjusted to take into account the autocorrelation in the time series (Trenberth 1984).

factor in determining the strength of the correlation
between these annually resolved time series. A crossspectral analysis (Mann and Lees 1996) was also performed to compare the OTI and NPI reconstructions(not shown). It reveals statistically significant (95%–99% level) coherency between the two series (for thecommon period from 1745 to 1783) on interannual todecadal time scales, including the broader ENSO bandwidth (2–11 yr; Allan 2000).
Relationships between the NPI and ENSO-related
indices (tropical Pacific SSTs and the Southern Oscillation index or SOI) were previously evaluated for the
recent instrumental period (e.g., Trenberth and Hurrell
1994; Deser et al. 2004). In Fig. 6 we extend this assessment with a comparison and running correlation between the TR NPI and coral OTI series and an independent reconstruction of Niño-3 SSTs based on a multiproxy dataset that includes information on decadal tomultidecadal variability (Mann et al. 2000). Similar patterns of correlation were observed by comparing the
TR NPI and coral OTI reconstructions to a largely independent reconstruction of the SOI based primarily

on subtropical western North American tree-ring data,
which has less decadal variability (Stahle et al. 1998).
For the TR NPI comparison with the Mann et al. (2000)
series, the sliding correlations (Fig. 6a) show varying
coherence through time with significant but weak correlations around 1800–50 and significant correlations in
the early twentieth century. Correlations are also significant for a brief period in the early 1700s. The sliding
correlation results using the coral OTI reconstruction(Fig. 6b) indicate strong coherence with the Niño-3 reconstruction for the twentieth century (r ⫽ 0.72), which
declines to zero in the mid–nineteenth century. The
lack of a correlation between these time series in the
mid–nineteenth century is interesting given the importance of ENSO to the variance in both. One possible
explanation is that the Niño-3 reconstruction appears toreflect anomalous (non-ENSO like) conditions during
this period (Mann et al. 2000). Alternatively, or in addition, the importance of ENSO to variance in the OTI
may weaken over this period.
The observations for the twentieth century are further explored in Table 1, in which we compare the in-15 DECEMBER 2005

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FIG. 6. (a, top) Comparison of the TR NPI (reversed sign) with the Niño-3 SST reconstruction of Mann et al. (2000). Both series havebeen normalized to their common period. (a, bottom) Running 51-yr correlations between both series. The 95% confidence limits havebeen adjusted to take into account the autocorrelation in the time series (Trenberth 1984). (b) As in (a) but for comparison between
the coral OTI series and the Niño-3 reconstruction.

5262

JOURNAL OF CLIMATETABLE 1. (a) Correlation of four proxy series with climate indices related to ENSO and Indo-Pacific climate. Proxies are the
NPI reconstruction (TR NPI), the coral OTI reconstruction, areconstruction of Niño-3 SST based on multiproxy data (Mann etal. 2000), and the first eigenvector scores (PC1) of three tree-ringwidth chronologies of teak for Indonesia (D’Arrigo et al. 1994).
The instrumental records are an index of the SOI, Niño-3 SST,
Indian Ocean SST, and an index of Indian monsoon rainfall. SOI,
Niño-3, and monsoon data from R. Allan, U.K. Hadley Center;
Indian Ocean SST from Kaplan et al. (1998)’s analysis. (b) As in(a) except correlations are made using actual indices of the NPI(Dec–May) and the OTI of Deser et al. (2004). The unfilteredcorrelations were made over the 1900–83 period (except for the
Niño-3 reconstruction data: 1900–80), while the filtered (threepoint binomial) correlations were made over the 1901–82 period(Niño-3 reconstruction: 1901–80). Double (single) asterisks denote significance at the 95% (90%) confidence limit. The significance values have been adjusted for autocorrelation in the data
(Trenberth 1984). The “optimized seasons” are those for which
the highest correlation was identified in an initial screening
process.
(a)Unfiltered

SOI

Niño-3
SST

IndianSST

Monsoonindex

TR NPI
Coral OTI
Niño-3 reconstruction
PC1 teak

0.28**⫺0.69**⫺0.74**
0.42**⫺0.38**
0.76**
0.77**⫺0.41**⫺0.37**
0.71**
0.73**⫺0.27**⫺0.05⫺0.20*⫺0.04
0.32**

Three-point binomial

SOI

Niño-3
SST

IndianSST

Monsoonindex

TR NPI
Coral OTI
Niño-3 reconstruction
PC1 teak

0.43**⫺0.75**⫺0.71**
0.25⫺0.37*
0.76**
0.75**⫺0.40**⫺0.40
0.68**
0.71**⫺0.13-0.06⫺0.41**
⫺0.21
0.31*

Optimized seasons for each proxy: SOI—NPI recon (Aug–Nov),
coral OTI (Jan–Dec), Niño-3 reconstruction (Jul–Apr), teak PC1(Jun–Dec); Niño-3 SST—NPI reconstruction (Feb–May), coral
OTI (Jan–Jun), Niño-3 reconstruction (pJul–Apr), and teak PC1(Sep–Dec); Indian Ocean SST—NPI recon (Jun–Nov), coral OTI(Jan–Dec), Niño-3 reconstruction (pNov–Aug), and teak PC1(Oct–Dec).
(b)
Unfiltered
Dec–May NPI
OTIThree-point binomial
Dec–May NPI
OTI

SOI

Niño-3
SST

IndianSST

Monsoonindex

0.44**⫺0.76**⫺0.51**
0.84**⫺0.53**
0.79**⫺0.22**
0.09

SOI

Niño-3
SST

IndianSST

Monsoonindex

0.37**⫺0.71**⫺0.57**
0.79**⫺0.69**
0.79**

⫺0.06
⫺0.15

Optimized seasons for synoptic series: SOI—Dec–May NPI reconstruction (Dec–Apr) and tropical index (pJun–Mar); Niño-3
SST—Dec–May NPI reconstruction (Jan–May) and tropical index(pJun–May); Indian Ocean SST—Dec–May NPI reconstruction(Mar–Sep) and tropical index (Dec–Jun).

VOLUME 18

strumental and proxy NPI and OTI to various indices oftropical Indo-Pacific climate. Correlations are presented for the NPI, OTI, and Niño-3 reconstructions(Table 1a) and actual indices of the NPI and OTI(Table 1b) against indices of ENSO and related IndoPacific climate (including the SOI, Niño-3 SST, Indian
Ocean SSTs, and an Indian monsoon rainfall index).
Also included are correlations with a teak tree-ringwidth record based on three chronologies from Indonesia, one of the few other high-resolution tropical
proxies available for comparison (D’Arrigo et al. 1994).
As expected, the TR NPI series, based only on North
Pacific tree-ring data, is more weakly (but in most cases
significantly) correlated with the ENSO and tropicalindices than the other series. Interestingly, comparisonof the coral OTI reconstruction with the ENSO-related
indices reveals correlations that are comparable tothose identified for the Niño-3 reconstruction (Table
1a). This result is not surprising, however, as the actual
OTI series is also highly correlated with ENSO-related
time series (Table 1b) and many of the coral records
used for the OTI reconstruction are documented toshow a strong ENSO signal. The teak record and thecoral OTI reconstruction also correlate significantlywith Indian monsoon rainfall (which may be a factor
linking tropical and extratropical climate; see section5), although the actual OTI series does not.

5. Discussion and conclusions
We have presented an extended tree-ring-based record of the NPI, an important index of the atmosphericcirculation closely linked to the climate of the North
Pacific and adjacent land areas (Trenberth and Hurrell1994). This reconstruction shows agreement with instrumental indices of both North Pacific and tropicalclimate. Both the NPI reconstruction and an independently derived coral-based reconstruction of an optimal
tropical climate index (OTI) for the Indian and Pacific
Oceans (Deser et al. 2004) reflect the decadal-scale regime shifts of the twentieth century and support theconcept of a tropical role in PDV in the recent period.
Both the tree-ring- and coral-based reconstructions reveal regime shifts prior to the instrumental record, but,
crucially, none appear synchronous between the tworecords. These shifts are generally comparable in intensity to those of the recent period although some are ofeven longer duration. Our analysis thus suggests thatthe 1976 transition was not unique in terms of magnitude, but that for some periods prior to the twentiethcentury, different mechanisms may have been responsible for tropical and extratropical interdecadal vari-15 DECEMBER 2005

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ability. A similar conclusion was reached in related
studies of North Pacific and South American tree-ringdata (e.g., Evans et al. 2001; Gedalof et al. 2002). Unlike such other studies, our report extends the paleoevidence for better assessment of a potential tropical–
high-latitude connection into the Indian Ocean as well,although it should be emphasized that the coral dataset
is biased to the central and western Pacific.
Changes in common variance over time could be related to the robustness of the proxies in their earlier
periods. Alternatively, the varying sign and magnitude
of correlations between the TR NPI and coral OTI reconstructions and Niño-3 proxy may reflect the timevarying impact of tropical forcing (e.g., ENSO, monsoon effects; Fig. 6 and Table 1) and its teleconnections
on North Pacific climate. The strongest positive correlation between the tropical and North Pacific proxies isin the twentieth century. Consistent with this observation, various reconstructions of the PDO, based on
North Pacific and southwestern United States tree-ring
data, show greater coherency during the twentieth century (Biondi et al. 2001; D’Arrigo et al. 2001; Gedalof
and Smith 2001; Cook 2003). Similarly, South Pacificcoral records indicate more symmetry across the Northand South Pacific after the late 1880s (Linsley et al.
2004), and there is stronger agreement between higherlatitude Pacific tree-ring data and a tropical coral record in the twentieth century, suggesting a stronger role
for the Tropics at this time (Evans et al. 2001).
The relationships described by Villalba et al. (2001,
2003), Evans et al. (2001), and herein suggest basinwide relationships linked to decadal to longer-term
fluctuations of ENSO or other forcing mechanisms(e.g., Linsley et al. 2004). The significant contributionsof ENSO-sensitive coral records to the coral OTI, andthe frequency characteristics of this index, suggest that
ENSO plays a role in low-frequency Pacific variability.
However, the ephemeral correlation between the coral
OTI and tree-ring NPI indicates that the importance oftropical dynamics has fluctuated in strength over the
past few centuries, invoking the need for alternate(nontropical) mechanisms for multidecadal North Pacific climate shifts. The Asian monsoon may also play a
key role in the transmission of climate signals between
the Tropics and extratropics (Table 1; Yamagata andMasumoto 1992). Variations in the NPI may thus be aremote response to tropical Pacific forcing from precipitation via atmospheric dynamics (Deser et al. 2004).
More research is needed using instrumental and proxy
data from the tropical Indian Ocean as well as the Pacific sector (along with modeling and theoretical work)in order to explore this theory.

Acknowledgments. This project was funded by the
National Science Foundation’s Paleoclimate Program(Grants ATM02-02898 and OCE 04-02474). This project was also supported by the Inter American Institute(IAI). We thank contributors to the NOAA Paleoclimatology Data Bank. We thank Adam Phillips(NCAR) for assistance with Fig. 3. We thank Ze’ev
Gedalof and one anonymous reviewer for commentsthat considerably improved the manuscript. Rob Wilson and Alexander Tudhope are partly funded by theEuropean Union Project “Simulations, Observations
and Palaeoclimatic data” (SOAP) and by the U.K.
NERC. Clara Deser gratefully acknowledges support
from the NOAA–OGP CLIVAR Program. Julia Coleis funded by a CAREER grant from the National Science Foundation and NOAA’s Climate Change Data
and Detection Program. Braddock Linsley is funded by
NSF Grant OCE-0318296.
REFERENCES
Allan, R., 2000: ENSO and climatic variability in the past 150
years. El Niño and the Southern Oscillation: Multiscale Variability and Global and Regional Impacts, H. Diaz and V.
Markgraf, Eds., Cambridge University Press, 3–56.
Biondi, F., A. Gershunov, and D. Cayan, 2001: North Pacific decadal climate variability since AD 1661. J. Climate, 14, 5–10.
Box, G. E. P., and G. C. Tiao, 1975: Intervention analysis withapplications to economic and environmental problems. J.
Amer. Stat. Assoc., 70, 70–79.
Charles, C. D., D. E. Hunter, and R. G. Fairbanks, 1997: Interaction between the ENSO and the Asian monsoon in a coral
record of tropical climate. Science, 277, 925–928.
——, K. Cobb, M. D. Moore, and R. G. Fairbanks, 2003: Monsoon–tropical ocean interaction in a network of coral records
spanning the 20th century. Mar. Geol., 201, 207–222.
Cobb, K. M., C. D. Charles, and D. E. Hunter, 2001: A central
tropical Pacific coral demonstrates Pacific, Indian, and Atlantic decadal climate connections. Geophys. Res. Lett., 28,
2209–2212.
Cole, J. E., and R. G. Fairbanks, 1990: The Southern Oscillation
recorded in the oxygen isotopes of corals from Tarawa Atoll.
Paleoceanography, 5, 669–683.
——, ——, and G. T. Shen, 1993: The spectrum of recent variability in the Southern Oscillation: Results from a Tarawa
atoll coral. Science, 260, 1790–1793.
Cole, J., R. Dunbar, T. McClanahan, and N. Muthiga, 2000: Tropical Pacific forcing of decadal SST variability in the western
Indian Ocean over the past two centuries. Science, 287, 617–
619.
Cook, E., 2003: Reconstructions of Pacific decadal variability
from long tree-ring records. Eos, Trans. Amer. Geophys.
Union, 83, S133.
——, and L. Kairiukstis, 1990: Methods of Dendrochronology.
Kluwer, 394 pp.
——, D. Stahle, D. Meko, and M. Cleaveland, 1999: Droughtreconstructions for the continental United States. J. Climate,12, 1145–1162.

5264

JOURNAL OF CLIMATE——, R. D’Arrigo, and M. E. Mann, 2002: A well-verified, multiproxy reconstruction of the winter North Atlantic Oscillation index since A.D. 1400. J. Climate, 15, 1754–1764.
D’Arrigo, R. D., G. C. Jacoby, and P. J. Krusic, 1994: Progress indendroclimatic studies in Indonesia. Terr. Atmos. Oceanogr.
Sci., 5, 349–363.
——, G. Wiles, G. Jacoby, and R. Villalba, 1999: North Pacific sea
surface temperatures: Past variations inferred from tree rings.
Geophys. Res. Lett., 26, 2757–2760.
——, R. Villalba, and G. Wiles, 2001: Tree-ring estimates of Pacific decadal climate variability. Climate Dyn., 18, 219–224.
——, E. Mashig, D. Frank, G. Jacoby, and R. Wilson, 2004: Reconstructed warm season temperatures for Nome, Seward
Peninsula, Alaska since AD 1389. Geophys. Res. Lett., 31,
L09202, doi:10.1029/2004GL019756.
Davi, N., R. D’Arrigo, G. Jacoby, B. Buckley, and O. Kobayashi,
2002: Warm-season annual temperature variability for Hokkaido, Japan reconstructed from tree-ring density data: AD
1557–1990. Climatic Change, 52, 201–217.
Deser, S., A. Phillips, and J. Hurrell, 2004: Pacific interdecadal
climate variability: Linkages between the Tropics and North
Pacific during boreal winter since 1900. J. Climate, 17, 3109–
3124.
Ebbesmeyer, C., D. Cayan, D. McLain, F. Nichols, D. Peterson,
and K. Redmond, 1991: 1976 step in the Pacific climate: Forty
environmental changes between 1968–75 and 1977–84. Proc.
Seventh Annual Pacific Climate Workshop, Asilomar, CA,
California Dept. of Water Resources, 115–126.
Evans, M. N., M. A. Cane, D. P. Schrag, B. K. Alexey Kaplan, R.
Linsley, R. Villalba, and G. M. Wellington, 2001: Support fortropically-driven Pacific decadal variability based on paleoproxy evidence. Geophys. Res. Lett., 28, 3689–3692.
Fritts, H., 1976: Tree Rings and Climate. Academic Press, 567 pp.
Garreaud, R., and D. Battisti, 1999: Interannual (ENSO) and interdecadal (ENSO-like) variability in the Southern Hemisphere tropospheric circulation. J. Climate, 12, 2113–2122.
Gedalof, Z., and D. Smith, 2001: Interdecadal climate variability
and regime-scale shifts in Pacific North America. Geophys.
Res. Lett., 28, 1515–1518.
——, N. J. Mantua, and D. L. Peterson, 2002: A multi-century
perspective of variability in the Pacific decadal oscillation:
New insights from tree rings and coral. Geophys. Res. Lett.,
29, 2204, doi:10.1029/2002GL015824.
Gordon, G., and S. LeDuc, 1981: Verification statistics for reconstruction models. Preprints, Seventh Conf. on Probability andStatistics in Atmospheric Sciences, Monterey, CA, Amer. Meteor. Soc., 129–133.
Graham, N., 1994: Decadal-scale climate variability in the 1970s
and 1980s: Observations and model results. Climate Dyn., 10,
135–162.
——, 2004: Late-Holocene teleconnections between tropical Pacific climatic variability and precipitation in the western
USA: Evidence from proxy records. Holocene, 14, 436–447.
Guilderson, T. P., and D. P. Schrag, 1999: Reliability of coral isotope records from the western Pacific warm pool: A comparison using age-optimized records. Paleoceanography, 14, 457–
464.
Isdale, P. J., B. J. Stewart, K. S. Tickle, and J. M. Lough, 1998:
Palaeohydrological variation in a tropical river catchment: A
reconstruction using fluorescent bands in corals of the Great
Barrier Reef, Australia. Holocene, 8, 1–8.

VOLUME 18

Jacoby, G., O. Solomina, D. Frank, N. Eremenko, and R.
D’Arrigo, 2004: Kunashir (Kurile Islands) oak response totemperature and relation to the Pacific Decadal Oscillation(PDO). Palaeogeogr., Palaeoclimatol., Palaeoecol., 209, 303–
311.
Kaplan, A., M. Cane, Y. Kushnir, A. Clement, B. Blumenthal, and
B. Rajagopalan, 1998: Analyses of global sea surface temperature 1856–1991. J. Geophys. Res., 103, 18 567–18 589.
Labeyrie, L., J. Cole, K. Alverson, and T. Stocker, 2003. The
history of climate dynamics. Paleoclimate, Global Change
and the Future, K. Alverson, R. Bradley, and T. Pederson,
Eds., Springer-Verlag, 33–61.
Linsley, B. K., L. Ren, R. B. Dunbar, and S. S. Howe, 2000: El
Niño–Southern Oscillation (ENSO) and decadal-scale climate variability at 10N in the eastern Pacific from 1893 to
1994: A coral-based reconstruction from Clipperton Atoll.
Paleoceanography, 15, 322–335.
——, G. Wellington, D. Schrag, L. Ren, M. Salinger, and A. Tudhope, 2004: Geochemical evidence from corals for changes in
the amplitude and spatial pattern of South Pacific interdecadal climate variability over the last 300 years. Climate Dyn.,
22, 1–11.
Mann, M. E., and J. Lees, 1996: Robust estimation of backgroundnoise and signal detection in climatic time series. Climatic
Change, 33, 409–445.
——, R. S. Bradley, and M. K. Hughes, 2000: Long-term variability in the El Nino Southern Oscillation and associated teleconnections. El Niño and the Southern Oscillation: Multiscale
Variability and its Impacts on Natural Ecosystems and Society, H. F. Diaz and V. Markgraf, Eds., Cambridge University
Press, 357–412.
Mantua, N., and S. Hare, 2001: The Pacific decadal oscillation. J.
Oceanogr., 58, 35–44.
——, S. Hare, Y. Zhang, J. Wallace, and R. Francis, 1997: A
Pacific interdecadal oscillation with impacts on salmon production. Bull. Amer. Meteor. Soc., 78, 1069–1079.
Meko, D. M., 1997: Dendroclimatic reconstruction with time varying subsets of tree indices. J. Climate, 10, 687–696.
Minobe, S., 1997: A 50–70 year climatic oscillation over the North
Pacific and North America. Geophys. Res. Lett., 24, 683–686.
Nakamura, H., G. Lin, and T. Yamagata, 1997: Decadal climate
variability in the North Pacific during the recent decades.
Bull. Amer. Meteor. Soc., 78, 2215–2225.
Percival, D., J. Overland, and H. Mofjeld, 2001: Interpretation of
North Pacific variability as a short- and long-memory process. J. Climate, 14, 4545–4559.
Stahle, D. W., and Coauthors, 1998: Experimental dendroclimaticreconstruction of the Southern Oscillation. Bull. Amer. Meteor. Soc., 79, 2137–2152.
Trenberth, K., 1984: Some effects of finite sample size and persistence on meteorological statistics. Part I: Autocorrelations.
Mon. Wea. Rev., 112, 2359–2368.
——, and J. Hurrell, 1994: Decadal atmospheric–ocean variationsin the Pacific. Climate Dyn., 9, 303–319.
Tudhope, A. W., and Coauthors, 2001: Variability in the El Nino–
Southern Oscillation through a glacial–interglacial cycle. Science, 291, 1511–1517.
Urban, F. E., J. E. Cole, and J. T. Overpeck, 2000: Influence ofmean climate change on climate variability from a 155-year
tropical Pacific coral record. Nature, 407, 989–993.
Villalba, R., R. D’Arrigo, E. Cook, G. Wiles, and G. Jacoby, 2001:

15 DECEMBER 2005

D’ARRIGO ET AL.

Decadal-scale climatic variability along the extratropicalwestern coast of the Americas: Evidence from tree-ringrecords. Inter-Hemispheric Climate Linkages, V. Markgraf,
Ed., Academic Press, 155–172.
——, and Coauthors, 2003: Large-scale temperature changes
across the southern Andes: 20th century variations in thecontext of the past 400 years. Climatic Change, 59, 177–232.
Wiles, G., R. D’Arrigo, and G. Jacoby, 1998: Gulf of Alaska at-5265mosphere–ocean variability over recent centuries inferredfrom coastal tree-ring records. Climatic Change, 38, 289–306.
Yamagata, T., and Y. Masumoto, 1992: Interdecadal natural climate variability in the western Pacific and its implications on
global warming. J. Meteor. Soc. Japan, 70, 167–175.
Zhang, Y., J. Norris, and J. Wallace, 1998: Seasonality of largescale atmosphere–ocean interaction over the North Pacific. J.
Climate, 11, 2473–2481.