Global and Planetary Change 40 (2004) 11 – 26
www.elsevier.com/locate/gloplacha
Large-scale temperature inferences from tree rings: a review
K.R. Briffa a,*, T.J. Osborn a, F.H. Schweingruber b
b
a
Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, UK
Swiss Federal Institute for Forest, Snow and Landscape Research, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland
Received 21 October 2002; accepted 7 May 2003
Abstract
This paper is concerned with dendroclimatic research aimed at representing the history of very large-scale temperature
changes. It describes recent analyses of the data from a widespread network of tree-ring chronologies, made up of ring width
and densitometric measurement data spanning three to six centuries. The network was built over many years from trees selected
to maximise their sensitivity to changing temperature. This strategy was adopted so that temperature reconstructions might be
achieved at both regional and very large spatial scales. The focus here is on the use of one growth parameter: maximum
latewood density (MXD). The detailed nature of the temperature sensitivity of MXD across the whole network has been
explored and the dominant common influence of mean April – September temperature on MXD variability is demonstrated.
Different approaches to reconstructing past temperature for this season include the production of detailed year-by-year gridded
maps and wider regional integrations in the form of subcontinental and quasi-hemispheric-scale histories of temperature
variability spanning some six centuries.
These ‘hemispheric’ summer series can be compared with other reconstructions of temperature changes for the Northern
Hemisphere over the last millennium. The tree-ring-based temperature reconstructions show the clear cooling effect of large
explosive volcanic eruptions. They also exhibit greater century-timescale variability than is apparent in the other hemispheric
series and suggest that the late 15th and the 16th centuries were cooler than indicated by some other data.
However, in many tree-ring chronologies, we do not observe the expected rate of ring density increases that would be
compatible with observed late 20th century warming. This changing climate sensitivity may be the result of other environmental
factors that have, since the 1950s, increasingly acted to reduce tree-ring density below the level expected on the basis of summer
temperature changes. This prevents us from claiming unprecedented hemispheric warming during recent decades on the basis of
these tree-ring density data alone. Here we show very preliminary results of an investigation of the links between recent changes
in MXD and ozone (the latter assumed to be associated with the incidence of UV radiation at the ground).
D 2003 Elsevier B.V. All rights reserved.
Keywords: Dendroclimatology; Tree-ring density; Northern Hemisphere; Temperature reconstructions; Global warming
1. Introduction
* Corresponding author. Tel.: +44-1603-593909; fax: +441603-507784.
E-mail address: [email protected] (K.R. Briffa).
0921-8181/$ - see front matter D 2003 Elsevier B.V. All rights reserved.
doi:10.1016/S0921-8181(03)00095-X
A large amount of tree-ring research is concerned
with very localised site studies (Dean et al., 1996),
necessarily reflecting the complex ecological processes that operate on small scales in forest ecosystems.
Depending on the specific situation, dendrochronolo-
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K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
gy can focus on the study of many different factors
that influence tree growth. Examples include the
following: the frequency of insect defoliation, the
occurrence of severe frosts or fire, or the general
competitional interactions in forest dynamics. The
challenge for the tree-ring researcher is to establish
an optimal representation or reconstruction of the past
variability of the particular factor under study. This
should involve providing realistic estimates of uncertainty, given that in practice many factors can act
together to produce the changing patterns of tree
growth that are measured.
From its beginnings, dendroclimatology recognised the need to undertake careful site selection in
order to maximise the potential climate sensitivity
within sampled tree-ring data. Dendroclimatologists
also had to take account of the bias that might be
introduced into tree-ring chronologies by the temporal
distribution of data drawn from different age trees:
younger trees lay down wider and generally more
dense rings than older trees (Fritts, 1976; Schweingruber, 1988).
This paper sets out to share some insights into how
one particular extensive set of tree-ring data has been
used as evidence of regional and hemispheric-scale
temperature variability, going back hundreds of years
from today. The intention is to illustrate the important
contribution that such data can make in providing well
dated and relatively accurate indications of the variability of climate and its causes, here using the
evidence of interannual density variations recorded
in wood from locations spread across the Northern
Hemisphere. Issues relating to the statistical processing and climatic calibration of these data are discussed. These must be borne in mind when reviewing
the accuracy of density-based reconstructions and in
particular when considering the apparent magnitude
of 20th century and other, longer timescale, deduced
temperature changes. As requested, this selected
review draws mainly on our own recent research—
some published, some unpublished—to demonstrate
how the interpretation of tree-ring records like other
proxy climate data is, to some extent, a compromise
and may be subject to recent confounding influences.
For wider dendroclimatic reviews, the reader is
referred to Cook and Kairiukstis (1990), Dean et
al. (1996), and Kaennel Dobbertin and Bräker
(2001).
2. The database and inherent temperature signals
Fig. 1 shows an extensive network of nearly 400
locations. From each, multiple tree core samples have
been collected from coniferous tree species and processed to provide separate ring width and maximum
(latewood) ring density chronologies (Schweingruber,
1988; Schweingruber and Briffa, 1996). These chronologies are time series of growth indices that represent the average of the interannual measurements for
one or the other parameter from selected trees at that
site. The choice of which sites to sample was guided
by a belief that the year-to-year growth of trees in
cool, relatively moist areas is likely to reflect a
predominant changing limitation of growing season
temperature, as evidenced by the width of the annual
rings and the density of the wood formed late in the
growing season (Schweingruber et al., 1993; Jacoby
and D’Arrigo, 1995). Hence a range of different tree
species was sampled in northern or relatively high
elevation areas. In this discussion we focus on the
maximum latewood density chronologies (MXD).
Each location in Fig. 1 is represented by a symbol
that shows the magnitude of the local correlation
between MXD and co-located instrumental temperature records, averaged over an extended (April – September) warm season. Detailed analyses of the
associations between each site chronology and ‘local’
average temperature (Jones et al., 1999) and precipitation (New et al., 2000) measurements for individual
months, preceding and during the tree growing season,
have established that the temperature during an April –
September season is an optimum choice to represent
the climate forcing of tree-ring density variation, when
considering the network as a whole (Briffa et al.,
2002a). [We use ‘local’ to mean the closest grid-box
average climate record.] There are regions where
correlations between MXD series and a shorter seasonal (summer) average temperature are systematically
higher (e.g. June –August or July – August in locations
in central and eastern Siberia) than those for this longer
warm season. There is also some variability in the
strength of correlations with the longer season within
all regions, in part reflecting variability in the temperature responses of different tree species. However, a
ubiquitous statistically significant positive response, in
the form of high density associated with above average
spring and summer warmth, is clearly present over the
K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
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Fig. 1. Locations of tree-ring maximum latewood density chronologies, with symbols indicating the correlation between each chronology and its
local grid-box temperature record for the April – September season. The key defines the correlation range associated with each symbol and lists
the number of sites falling in each range. Nine arbitrary regions are defined by the black lines and identified by the acronyms: NEUR = northern
Europe; SEUR = southern Europe; NSIB = northern Siberia; ESIB = eastern Siberia; CAS = central Asia; TIBP = Tibetan Plateau; WNA = western North America; NWNA = northwestern North America; ECCA = eastern and central Canada.
whole network. When the MXD and instrumental
observations are each separately averaged within different regions (such as those arbitrarily defined and
shown in Fig. 1), to represent large-scale integrated
series, there is invariably a very high correlation
between them. This is evidence of a likely common
response across the region that is frequently of equivalent, or even greater, magnitude than the strongest
response shown at any of the local sites contained
within the region (Briffa et al., 2002a).
This averaging of different site data to enhance the
expression of an underlying common regional growthinfluence on trees (even of different species) is exem-
plified in Fig. 2. This summarises the seasonal extent
and strength of association between temperature and
tree-ring density across the entire network shown in
Fig. 1. Correlations between all of the density chronologies and ‘local’ temperature records are summarised
for each of the months, leading up to and during the
period when ring formation occurs. Correlations are
also shown for various mean temperature ‘seasons’.
The shaded arrows (5th and 95th percentile ranges)
indicate the range of individual site temperature correlations. The histograms show the average values of all
these individual site associations. The open circles
show the results achieved when all the local density
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K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
to use as a predictand in attempts to reconstruct past
temperature variability with these data.
Such a choice is, of course, a statistical compromise
and at a very local or even larger regional scale, other
targets could be used. Defining a rigid calendar-based
season obviously takes no account of any direct
physiological mechanism by which the seasonal
growth of trees is triggered or terminated. The use of
mean monthly data averages is, perhaps, crude but it is
dictated by the need for widely available data. The start
and end of ring growth and seasonal density changes
do not correspond to any particular fixed season. Nor
are they controlled directly or solely by temperature.
The April – September mean temperature is, nevertheless, highly correlated with other thermal measures,
even those not calendrically fixed (e.g. cumulative
degree-day sums: Jones and Briffa, 1995), and offers
a very defensible focus for attempts at large-scale
reconstruction.
Fig. 2. Summary of correlations between individual chronologies
and their monthly or seasonal local grid-box temperature record for
months from the previous June to September of the year of growth,
for the October to September annual mean, and for four seasonal
means. Bars indicate the mean of the local correlations, with the 5th
and 95th percentiles marked by triangles. The open circles are
correlations between the average of all density chronologies and the
average of all the grid-box temperatures at the chronology sites.
chronologies are averaged to form a single series and
this is correlated with the equivalent single record made
up by averaging all of the local temperature series. In
effect, these are the correlations between ‘whole network’ chronologies and averaged temperatures for
nearly the entire Northern Hemisphere land series for
that month or season. We can see, in Fig. 2, little if any
significant influence on tree-ring density during the
months of late summer or winter preceding the formation of the ring. There is, though, a near universal
positive response across the network to warmth in each
of the spring and summer months.
In some regions, such as northeastern Siberia, a
shorter seasonal (June – August or even July –August)
temperature average displays a stronger association
with density variability (see Briffa et al., 2002a) but
the mean temperature for April –September can be
clearly identified as a very significant influence on
tree-ring latewood density across the whole network,
and as such it represents a justifiable common ‘target’
3. Temperature patterns over six centuries
Figs. 3 and 4 are presented here to illustrate some
initial results that exploit the spatial dimension of this
network in the form of estimates of past April –
September mean temperature patterns. Density chronologies, averaged over individual 5j latitude by 5j
longitude boxes, have been regressed against modern
instrumental temperatures (Jones et al., 1999), similarly averaged in the same boxes, to provide estimates
of past temperature that, in some areas, extend back to
AD 1400 (Briffa et al., 2002b; Osborn et al., in
preparation). Fig. 3 shows maps for the 12 coolest
and 12 warmest years, ranked by the value obtained
when available data are averaged across the whole
network. The spatial coverage of the maps is reduced
in earlier years when fewer locations have tree-ring
data, particularly before the 17th century and particularly in northwest and northeast North America. As the
individual grid-box estimates are independent of each
other, consistency in the anomalies across wide areas
gives additional confidence in the realism of the
inferred changes, above that provided by the high
regression significance. Even in the coldest/warmest
summers there are regions of relative warmth/cold.
Indeed, the maps frequently divide into subcontinental-scale regions of alternating sign, with western and
K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
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Fig. 3. Estimates of warm-season temperature anomalies (jC with respect to the 1961 – 1990 mean) for the 12 coolest (coldest first) and the 12
warmest (hottest last) summers in the tree-ring density reconstructions.
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K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
Fig. 4. Longitude versus time (1400 – 1960) diagram of reconstructed high-latitude warm-season temperature anomalies (jC with respect to the
1961 – 1990 mean). Each value represents the average of any reconstructed temperatures poleward of 50jN at each longitude, with decadal
smoothing applied to the time series. The locations of the three main continents are given at the top.
K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
eastern North America often showing contrasting
anomalies and, similarly, northern Eurasia dividing
into three or four regions of alternating warm and
cold. In some of the coolest overall years, northwest
Europe, including Britain and southern Scandinavia, is
sometimes clearly warm (e.g., in 1698, 1699 and 1884)
while this area is often cool when the overall network
mean is warm (e.g., in 1478, 1686, 1722 and 1931).
In Fig. 4, the reconstructions have been smoothed
using a decadal low-pass filter and meridionally averaged to highlight decadal timescale changes, effectively between 50j and 75jN, at different longitudes over
the time period from AD 1400 to 1960. [The data in
Fig. 4 have additional low-frequency variability to that
shown both in Fig. 3 and by Briffa et al. (2002a)
because the low-frequency regional temperature variability reconstructed by Briffa et al. (2001) has been
superimposed on the data (Osborn et al., in preparation)]. The complexity and longitudinal variation of
these temperature changes is apparent. In Europe and
western Siberia, beside the warmth of much of the first
half of the 20th century, the relative warmth of the 15th
and much of the early 16th centuries is clear. There are
also very distinct periods of widespread contemporaneous cool conditions: the most prominent and persistent began during the last few decades of the 16th
17
century and continued through to the mid-17th century
in Eurasia, perhaps persisting longer, to the end of the
17th century, in North America. It is possible that this
cold occurred earlier in eastern Siberia (near the mid16th century) and ‘propagated’ westward. There are
several other, much shorter but very distinct, periods
when cool conditions appeared abruptly and simultaneously across all or much of the network: during the
1810s, 1830s, late 1860s and late 1880s (except in
Alaska).
When we average the chronology data across the
whole network and calibrate the resulting series
against average land temperatures north of 20jN
(Fig. 5), these periods with extremely cool summers
now stand out. Comparison with years of known large,
explosive volcanic eruptions (identified by Volcanic
Explosivity Index, VEI, values greater than 4 in Fig.
5), provides extremely strong circumstantial evidence
that many widespread cold excursions were a response
to known volcanoes, while other cold summers (such
as in 1695) are strongly suggestive of major eruptions
that have not, as yet, been identified on the basis of
existing historical or geological evidence (Briffa et al.,
1998a).
Note the century-timescale variance in Fig. 5,
emphasised by the smooth curve, which shows a
Fig. 5. Estimates of warm-season temperature (jC anomalies from the 1961 – 1990 mean) for land areas north of 20jN. The smoothed curve is
the 25-year low-pass filtered reconstruction produced using the Age-Band Decomposition approach of Briffa et al. (2001). The Volcanic
Explosivity Index (VEI) is indicated by the arrows at the bottom; ‘?’ marks those eruptions whose date is uncertain.
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K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
gradual cooling trend throughout the 16th century,
persistent cool conditions throughout much of the
17th century, and a slow warming through the 18th
and 19th centuries. This degree of long-timescale
variance is preserved in these data by the use of a
new statistical processing technique (Age-Band Decomposition, ABD, standardisation), required to remove age-related bias inherent in the direct
measurements of the tree-ring densities (Briffa et al.,
2001). The bias, which is commonly expressed as a
negative trend in radially measured tree growth parameters, is associated with tree life-cycle changes: trees
often laying down wider and denser rings in their
youth and progressively narrower and less dense rings
as they age (Fritts, 1976; Schweingruber, 1988). Some
earlier methods used to correct for this potential bias
removed long-timescale variability in the resulting
chronologies and with it any potential for preserving
slowly evolving climate trends in the reconstructions
produced from them (Cook et al., 1990, 1995; Briffa et
al., 1996). The MXD chronologies used to produce the
maps in Fig. 3 did not use these new ‘standardization’
techniques. So while they do represent up to multidecadal timescale variability, they do not show evidence of multi-century changes. This will not
significantly affect the spatial patterns in relative
temperatures reconstructed, but the regional average
time series produced from them (see Briffa et al.,
2002a) do not show the same extent of long-timescale
variability exhibited in Figs. 4 and 5. For further
discussion of the important ‘standardization’ issue as
it relates to these data see also Briffa et al. (1992, 1996)
and Cook et al. (1995).
4. An inconsistency in the relationship between
tree-ring density and temperature
The near hemispheric scale record of temperature
estimates in Fig. 5 displays a clear underlying cooling
trend during the second half of the 20th century. No
such trend is seen in the summer (or any other
Fig. 6. (a) Instrumental temperatures (red) and tree-ring density reconstructions of temperature (black) averaged over all land grid boxes north of
50jN, smoothed with a 5-year low-pass filter. (b) Pattern of regression coefficients between the difference between the smoothed, area-averaged
curves in (a) and the difference between the grid-box temperature reconstructions and observations. The difference is dominated by the relative
decline in tree-ring density over recent decades, and regression slopes >1 indicate the local decline is stronger than average, < 1 indicates the
local decline is weaker, and < 0 that there is no local decline. (c) Correlation between area-average of all instrumental (April – September)
temperatures and area-average of all tree-ring densities, both high-pass filtered to retain only subdecadal variability, and then correlated in a 20year sliding window. The shaded area is bounded by the 5th and 95th percentile values of multiple sample correlations of sample size 20 and the
horizontal line represents the overall mean of the correlations.
K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
seasonal) instrumental record. Fig. 6a shows how the
trend in latewood density averaged across all northern
site trees (i.e. selecting the chronologies from north of
50jN) begins to diverge from the April– September
mean temperature record for the same northern land
areas, after about 1960. This phenomenon can be
recognised on larger geographical scales, virtually
across the whole northern sampling network, and has
been illustrated and discussed previously for subcontinental scale regions (Briffa et al., 1998b). Fig. 6b
shows a detailed geographical breakdown of where the
trend of late 20th century tree-ring density falls in
relation to coincident regional temperatures, expressed
relative to the average decline shown in Fig. 6a.
In only a very few grid boxes (in southern Europe,
eastern Canada, northwest and southwest United
States and central Asia) is there no relative density
decline. Over virtually the whole of the remaining
area, it is easily discernible and at three areas in
particular, all at higher latitudes, the decline in density
relative to local temperatures is even stronger than that
represented by the average high-latitude decline: in
north central Canada, northwest Siberia south of
Novaya Zemlya, and northwest central Siberia just
east of the Taimyr Peninsula. Though these differences in trend are real, they are largely masked at local
scales by the high interannual variability of the
temperature and MXD data that is largely coincident
in both, even in the second half of the 20th century.
This is demonstrated (at the overall hemispheric scale)
in Fig. 6c, which shows the temporal stability in the
strength of the interannual-timescale correlation between the mean network MXD chronology and
corresponding regionally averaged April –September
mean temperatures through the late 19th and 20th
centuries. The link between these is clearly very firm
and apparently time stable during all of the second
half of the 20th century. However, similar analyses
repeated for each of the major regions that make up
the network show that the strength of the correlations
at high frequency (i.e., based on 10-year high-pass
filtered time series) also displays a degradation from
about 1970 onwards, in a few regions, particularly in
northern Europe and northwest North America (see
also Fig. 14 of Briffa et al., 2002a).
The above facts seem to support an inference that
some slowly varying factor began to exert a very
widespread negative influence on the trend of these
19
MXD data from around the middle of the 20th
century, with effects at higher frequency also becoming noticeable in some high-latitude regions. For the
time being, we circumvent this problem by restricting
the calibration of the density data to the period before
1960. This reduces the potential overlap between
temperature observations and density measurements
and means that less data can be reserved for independent tests of the validity of predictive equations. This
situation is far from ideal, but the alternative, using
data after 1960 and thus incorporating non-temperature-related bias when fitting regression equations as a
function of density variability, would invariability
produce earlier estimates of past temperature that, to
some extent, too warm.
5. A possible link between tree-ring density
changes and ozone?
There is some, though limited, experimental evidence of the negative effect of enhanced ultra violet
radiation (UV-B) on the photosynthetic process of
some higher plants (e.g., see references in Sullivan,
1994; Tevini, 1994). It has been suggested that an
‘unusual’ increase in the incidence of UV at nearground level, a possible consequence of falling concentrations of ozone in the stratosphere (DeLuisi et
al., 1994), might be associated with a reduction in tree
productivity (Briffa et al., 1998b; Briffa, 1999). Unfortunately, there are virtually no systematic direct
measurements of UV for any length of time across the
hemisphere. Therefore, as a basic first exploration of
the empirical evidence for such an effect, we have
investigated whether there is any correlation between
observations of ozone concentrations and our MXD
data. As no widespread data on stratospheric ozone
exist, we use satellite-based estimates of total column
ozone, provided by the Total Ozone Mapping Spectrometer (TOMS: McPeters et al., 1996). These data
do not distinguish between tropospheric and stratospheric ozone concentrations, but they are available
for the whole of the Northern Hemisphere, though
unfortunately only from 1979 onwards. Fig. 7a illustrates the mean April field for 1979 – 1993 along with
the spatial distribution of ozone trends over the same
period. Virtually the whole land area north of 40jN
displays a reduction in total ozone, with the greatest
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K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
falls evident over the northwest and the extreme east
of Siberia, and over the western Arctic Ocean, including the northern part of Greenland. This pattern of
negative trends across much of the high Northern
Hemisphere is, in some part, forced by the pattern
of relatively severe ozone reduction that occurred in
1993 (Fig. 7a). However, there is a high interannual
variation in the pattern of ozone concentrations and
relatively high values (above the 1979 – 93 mean)
occurred over some regions in some years; such as
over Novaya Zemlya in 1988, and north of the Taimyr
peninsula in 1993 (see also Fig. 7a).
Note that all of the single-year patterns and longerperiod mean maps shown in Fig. 7a refer to the
average of April measurements only. We have chosen
April, as it is early in the daylight season in the area of
the northern tree line and so it represents the time
when maximum ozone reduction would be expected
to occur. The recent time-dependent change in the
nature of the seasonal association between temperature and MXD has also been shown to occur during
the spring (Briffa et al., 2002a).
Obviously, the overlap period between the ozone
measurements and our currently available tree-ring
density chronologies is very short and precludes any
possibility of testing coincidence in common regional
trends, but given the large year-to-year variability in
the ozone and MXD patterns, we considered it worthwhile exploring whether there was any possible statistically significant link between them.
Rather than compare ozone variability with MXD
data directly, we chose instead to use residuals from a
regression of April– September mean temperature on
MXD data. Hence we seek to test whether years with
low ozone (assumed to be related to higher UV
radiation) are associated with MXD values below
those expected on the basis of April –September mean
seasonal temperatures.
We chose three regions for this initial comparison
(NEUR, NSIB and CAS: see Fig. 1) because they
offered the largest periods of data overlap, and because they represent a range of regional associations
between temperature and MXD (strong association in
NEUR and NSIB and weaker association in CAS).
Also note that the interannual correlations in the
NEUR and NSIB regions degrade progressively after
about 1960, as mentioned earlier. The results are
shown in Fig. 7b.
Good correspondence between the temperature and
MXD series is apparent during the 19th and early 20th
centuries, for both the NEUR and NSIB regions, but a
common systematic divergence can be clearly seen in
NEUR beginning in the early 1960s and, similarly, in
NSIB in the mid-1960s. Though the general MXD/
temperature link in CAS (a large and less homogeneous temperature region with many fewer chronologies) is clearly weaker, it is also possible to detect a
systematic difference beginning around 1970. The
short ozone series (the average of April data extracted
over roughly adjacent regions to the tree-ring areas)
exhibit qualitatively similar declining trends within
each region. The correlations with the MXD residual
data, which are strongly influenced by the high
interannual variability as well as the trend, are all
positive, consistent with the notion that reduced ozone
might be associated with reduced MXD. To be significant, these correlations would need to be of the
order of 0.44 or above (at a p = 0.05 level, using a onetailed test and 13 degrees of freedom). This is not the
case for NEUR (r = 0.25) or NSIB (0.34), though the
correlation for CAS (0.45) is just at this level. Hence
the results are equivocal, though not negative.
Other possible causes of, or contributors to, the
apparent recent dissociation between this, admittedly
crude, seasonal temperature parameter and the MXD
data are possible (Briffa et al., 1998b). An increasing
influence of later snow cover delaying the onset of
seasonal tree growth is one suggestion (Vaganov et al.,
1999). This theory, like that of a possible UV influence,
requires further investigation. This could involve
smaller spatial scales and more refined specification
of the regional ozone data and the use of data for
months other than April. Detailed exploration of the
intercorrelations between temperature and ozone, and
Fig. 7. (a) Total Ozone Mapping Spectrometer (TOMS) measurements of total column ozone in April: top row, 1979 – 1993 mean and linear
trend; middle row, 1988 and 1989 anomalies; and bottom row, 1990 and 1993 anomalies. All anomalies are from the 1979 – 1993 mean. (b) The
MXD chronologies (black) superimposed on estimates of these based on regression using local April – September mean temperature as a
predictor (red), for three regions shown in Fig. 1: northern Europe, northern Siberia and central Asia. For each region, the regression residuals
are also shown in black with local regional ozone concentration anomalies (arbitrarily scaled here) shown in green.
K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
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K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
ozone and MXD are also needed, and, where possible,
local studies should be undertaken where longer direct
measures of UV radiation are available (Weatherhead et
al., 1997; Staehelin et al., 1998). Other factors need to
be considered also, such as the effect of cloud cover on
UV penetration (Schafer et al., 1996).
6. Late Holocene Northern Hemisphere
Temperature
All of the tree-ring data taken from the wider
network shown in Fig. 1, processed to retain evidence
of low-frequency temperature forcing (as shown in
Fig. 5), provide information on the variability of warm
season temperatures over a large area of the Northern
23
Hemisphere land, though with increasing uncertainty,
back to AD 1400 (Briffa et al., 2001). Longer series of
similar tree-ring MXD data, but for much more
restricted regions (e.g. individual sites in Sweden,
Russia or western Canada), also contribute to our
knowledge of the history of hemispheric temperature
change through their incorporation within different
multi-proxy amalgamations representing the last 1000
years (e.g., Jones et al., 1998; Mann et al., 1999). A
selection of temperature reconstructions is shown in
Fig. 8. Tree-ring-based reconstructions contained in
these compilations represent a significant proportion
of the palaeoclimate data, especially for the period
before AD 1600. Fig. 8 also includes two reconstructions made up exclusively from tree-ring width measurements: one (Briffa and Osborn, 1999) is an average
Fig. 8. Average temperature over land areas north of 20jN, as observed (black) and reconstructed by a simple linear regression recalibration of
published series by Jones et al. (1998) in red; Mann et al. (1999) in purple; Briffa and Osborn (1999) in green; Briffa et al. (2001) in blue; and
Esper et al. (2002) in pink. The series used from Mann et al. (1999) was an average of land grid boxes north of 20jN from their spatially
resolved reconstructions. Each series was recalibrated over 1881 – 1960 against (a) annual-mean temperature and (b) April – September mean
temperature. Note the effect on the temperature magnitudes in the two sets of series caused by calibrating the same data against these alternative
predictands.
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K.R. Briffa et al. / Global and Planetary Change 40 (2004) 11–26
of only three regional chronologies from northwest
Sweden (Grudd et al., 2002), and the Yamal (Hantemirov and Shiyatov, 2002) and Taimyr (Naurzbaev et
al., 2002) regions of northern Siberia. The other
(Esper et al., 2002) uses data from 14 widespread
sites, many (though not all) independent of those used
in the other compilations.
Many (but in some cases not all) tree-ring width
and MXD data contained in these reconstructions
have been processed to retain long-timescale variance
and together they demonstrate how temperatures
have changed over the centuries, prior to the clear
20th century warming shown in the instrumental
curve. The relative magnitude of these changes varies
between the different compilations, despite the element of common data input (see Briffa and Osborn,
1999, 2002), because of different regional concentrations of data and because of different approaches
used to assemble and express them quantitatively in
terms of different temperature ‘targets’. Those based
solely on tree-ring data (Briffa and Osborn, 1999;
Briffa et al., 2001; Esper et al., 2002) tend to show
greater relative cold overall, though most clearly in
the 13th and 17th centuries, and possibly slightly
more warmth around AD 1000, but the large uncertainty (not shown here, but see Mann et al., 1999;
Briffa et al., 2001) associated with all of the records
should caution against over-interpretation of these
differences. It is also likely that many of the treering data respond more to summer rather than winter
conditions and represent more northerly, rather than
full, Northern Hemisphere temperatures. The Mann
et al. (1999) data were calibrated directly against
annual temperature records and contain tree-ring, and
non-tree-ring series that are influenced to a greater
extent by winter conditions than are our MXD data.
Hence, this is likely to be a better indicator of mean
annual temperature change than any of the MXD data
alone (see also Briffa and Osborn, 2002). The question of different seasonal responses in palaeoclimate
data is an important one, not least because regression-based reconstruction of different seasonal data
can affect the relative magnitude (and uncertainty) of
past changes, even using similar predictor data, as
shown in Fig. 8.
However, even allowing for differences in these
various records, they provide strong evidence that the
hemisphere has warmed over the last century, and
particularly the last two decades, to a level that
appears unusual. Even considering the uncertainties
associated with all of these curves, it is not possible to
discount the possibility that this warming is unprecedented in the context of the last millennium.
7. Conclusions
This paper was intended as a brief summary of the
authors’ recent work and an illustration of the progress and potential in using tree-ring density data from
around the Northern Hemisphere. It is, hopefully,
apparent that such work is contributing useful information on the past natural variability of late Holocene
climate, but we have clearly pointed to some interpretational problems associated with the use of these
data. While real progress is being made in overcoming
them, several require further study. Tree-ring density
and tree-ring width data will continue to enhance our
detailed knowledge of past temperature and other
climate changes, but a major priority, besides the need
to further develop and expand the networks, is an
urgent requirement to systematically update the existing sample collections with more recent data to allow
better exploration of the implications of different
chronology production and climate calibration techniques, and to enable more holistic exploration of the
nature and expression of the climate sensitivity of the
data to be undertaken.
Acknowledgements
KRB and TJO acknowledge current support from
the European Commission (under EVK2-CT-200200160{SOAP}) and the UK NERC (under NER/T/S/
2002/00440). We thank Ed Cook and Mike Baillie for
comments on the initial draft of this paper.
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