26. Marker Hs. 11974 in P. Deloukas et al., Science 282,
744 (1999).
27. A. E. Hughes et al., Hum. Mol. Genet. 4, 1225 (1995).
28. L. J. Andrew et al., Am. J. Hum. Genet. 64, 136 (1999).
29. K. Rojas et al., Genomics 62, 177 (1999).
30. G. Lust, G. Faure, P. Netter, J. E. Seegmiller, Science
214, 809 (1981).
31. Skin samples were removed from pairs of age- and
sex-matched wild-type and ank mice, minced, and
dissociated at 37°C in medium containing 0.05%
trypsin, 0.53 mM EDTA, dispase (2.5 U/ml), and col-
lagenase (200 U/ml). Attached skin fibroblasts were
grown in Dulbecco’s minimum essential medium
(DMEM) containing 15% FBS, 2 mM GlutaMax, 0.1
mM nonessential amino acids, penicillin G (100
U/ml), streptomycin (100 mg/ml), and amphotericin
B (0.25 mg/ml). Intracellular pyrophosphate levels
were determined by coupled enzymatic and fluori-
metric assay [G. Lust and J. E. Seegmiller, Clin. Chim.
Acta 66, 241 (1976)]. Extracellular pyrophosphate
was determined by incubating cells in 3 ml of DMEM
(10% FBS, 2 mM GlutaMax, 0.1 mM nonessential
amino acids, no phenol red) for 48 hours. Condi-
tioned medium (500 ml) was pre-cleared by centrif-
ugation, adjusted to 1 M perchloric acid, and centri-
fuged. The supernatant was neutralized with 4 M
KOH, centrifuged to remove KClO
4
precipitate, and
assayed for pyrophosphate as above. Sample means
were compared with the use of the Student’s t test.
32. H. Fleisch, Metab. Bone Dis. Relat. Res. 3, 279 (1981).
33. iiii and S. Bisaz, Nature 195, 911 (1962).
34. Primary mouse fibroblasts (0.5 3 10
6
to 1 3 10
6
)or
simian COS-7 cells (1 3 10
6
to 2 3 10
6
) were plated
in 100-mm dishes, grown for 6 to 12 hours, and
incubated for 4 to 6 hours in serum-free medium
with DNA (5 mg), Plus reagent (18 ml), and Lipo-
fectamine (18 ml)(Gibco-BRL). Following transfec-
tion, cells were grown in fresh antibiotic-free medium
for 36 to 48 hours before assay. Control experiments
with a pCMV-lacZ plasmid showed about fivefold
higher expression levels in COS-7 cells than in mouse
fibroblasts under these conditions.
35. S. E. Guggino, G. J. Martin, P. S. Aronson, Am. J.
Physiol. 244, F612 (1983).
36. A. K. Rosenthal and L. M. Ryan, J. Rheumatol. 21, 896
(1994).
37. H. Fleisch, D. Schibler, J. Maerki, I. Frossard, Nature
207, 1300 (1965).
38. H. Fleisch et al., Am. J. Physiol. 211, 821 (1966).
39. A. M. Caswell, M. P. Whyte, R. G. Russell, Crit. Rev.
Clin. Lab. Sci. 28, 175 (1991).
40. A. Okawa et al., Nature Genet. 19, 271 (1998).
41. I. Nakamura et al., Hum. Genet. 104, 492 (1999).
42. D. J. White et al., J. Clin. Dent. 7, 46 (1996).
43. W. P. Tew et al., Biochemistry 19, 1983 (1980).
44. H. E. Krug et al., Arthritis Rheum. 36, 1603 (1993).
45. P. Dieppe and I. Watt, Clinics Rheum. Dis. 11, 367
(1985).
46. D. T. Felson et al., J. Rheumatol. 16, 1241 (1989).
47. P. A. Gibilisco, H. R. Schumacher, Jr., J. L. Hollander,
K. A. Soper, Arthritis Rheum. 28, 511 (1985).
48. A. Swan et al., Ann. Rheum. Dis. 53, 467 (1994).
49. M. Doherty, I. Watt, P. A. Dieppe, Lancet i, 1207
(1982).
50. A. L. Concoff and K. C. Kalunian, Curr. Opin. Rheu-
matol. 11, 436 (1999).
51. L. M. Ryan and H. S. Cheung, Rheum. Dis. Clin. North
Am. 25, 257 (1999).
52. We thank M. Wagener for excellent assistance with
animal experiments and G. Barsh and members of the
Kingsley lab for helpful comments on the manuscript.
A.M.H. is a trainee of the Medical Scientist Training
Program at Stanford, supported by NIH training
grant 5T32GM07365 (NIGMS). The initial stages of
the genetic cross were supported by a Stanford-
SmithKline Beecham research award. D.M.K. is an
HHMI assistant investigator.
18 April 2000; accepted 6 June 2000
Causes of Climate Change Over
the Past 1000 Years
Thomas J. Crowley
Recent reconstructions of Northern Hemisphere temperatures and climate
forcing over the past 1000 years allow the warming of the 20th century to be
placed within a historical context and various mechanisms of climate change
to be tested. Comparisons of observations with simulations from an energy
balance climate model indicate that as much as 41 to 64% of preanthropogenic
(pre-1850) decadal-scale temperature variations was due to changes in solar
irradiance and volcanism. Removal of the forced response from reconstructed
temperature time series yields residuals that show similar variability to those
of control runs of coupled models, thereby lending support to the models’ value
as estimates of low-frequency variability in the climate system. Removal of all
forcing except greenhouse gases from the ;1000-year time series results in a
residual with a very large late-20th-century warming that closely agrees with
the response predicted from greenhouse gas forcing. The combination of a
unique level of temperature increase in the late 20th century and improved
constraints on the role of natural variability provides further evidence that the
greenhouse effect has already established itself above the level of natural
variability in the climate system. A 21st-century global warming projection far
exceeds the natural variability of the past 1000 years and is greater than the
best estimate of global temperature change for the last interglacial.
The origin of the late-20th-century increase
in global temperatures has prompted consid-
erable discussion. Detailed comparisons of
climate model results with observations (1)
suggest that anthropogenic changes, particu-
larly greenhouse gas (GHG) increases, are
probably responsible for this climate change.
However, there are a number of persistent
questions with respect to these conclusions
that involve uncertainties in the level of low-
frequency unforced variability in the climate
system (2) and whether factors such as an
increase in solar irradiance or a reduction in
volcanism might account for a substantial
amount of the observed 20th-century warming
(1, 3–10). Although many studies have ad-
dressed this issue from the paleoclimate per-
spective of the past few centuries (3–10), robust
conclusions have been hampered by inadequate
lengths of the time series being evaluated. Here
I show that the agreement between model re-
sults and observations for the past 1000 years is
sufficiently compelling to allow one to con-
clude that natural variability plays only a sub-
sidiary role in the 20th-century warming and
that the most parsimonious explanation for
most of the warming is that it is due to the
anthropogenic increase in GHG.
Data
The data used in this study include physically
based reconstructions of Northern Hemi-
sphere temperatures and indices of volca-
nism, solar variability, and changes in GHGs
and tropospheric aerosols.
Northern Hemisphere temperatures. Four
indices of millennial Northern Hemisphere
temperature have been produced over the past
3 years (11–14). The analysis here uses the
mean annual temperature reconstructions of
Mann et al. (11) and of Crowley and Lowery
(CL) (12), because the energy balance model
used in this study calculates only this term
[the other records (13, 14) are estimates of
warm-season temperature at mid-high lati-
tudes]. The Mann et al. reconstruction was
determined (8) by first regressing an empiri-
cal orthogonal function analysis of 20th-cen-
tury mean annual temperatures against vari-
ous proxy indices (such as tree rings, corals,
and ice cores). Past changes in temperature
are estimated from variations in the proxy
data (15). The Mann et al. reconstruction has
a varying number of records per unit of time
(although the number in the earlier part of the
record is still greater than in CL). The CL
reconstruction is a more heterogeneous mix
of data than the Mann et al. reconstruction,
but the number of records is nearly constant
in time. It is a simple composite of Northern
Hemisphere climate records and was scaled
(12) to temperature using the instrumental
record (16) in the overlap interval 1860–
1965. The instrumental record was substitut-
ed for the proxy record after 1860 for two
reasons: (i) there were too few proxy data in
the CL time series after 1965 to reconstruct
temperatures for this interval, and (ii) the
original CL reconstruction indicated a
“warming” over the interval 1885–1925 that
is at variance with the instrumental record.
This difference has been attributed (11, 17)to
Department of Oceanography, Texas A&M University,
College Station, TX 77843, USA. E-mail: tcrowley@
ocean.tamu.edu
R ESEARCH A RTICLES
14 JULY 2000 VOL 289 SCIENCE www.sciencemag.org270

an early CO
2
fertilization effect on tree
growth. The significance of this decision will
be further discussed below; model-data cor-
relations presented in the study include both
the original proxy record and the substituted
instrumental time series.
Despite the different number and types
of data and different methods of estimating
temperatures, comparison of the decadally
smoothed variations in each reconstruction
(Fig. 1) indicates good agreement (r 5 0.73
for 11-point smoothed correlations over the
preanthropogenic interval 1005–1850, with
P , 0.01). Both records [and the Jones et
al. (13) and Briffa (14) reconstructions]
show the “Medieval Warm Period” in the
interval ;1000–1300, a transition interval
from about 1300–1580, the 17th-century
cold period, the 18th-century recovery, and
a cold period in the early 19th century.
Even many of the decadal-scale variations
in the Medieval Warm Period are reproduc-
ible (12), and both reconstructions [and
(13, 14)] indicate that peak Northern Hemi-
sphere warmth during the Middle Ages was
less than or at most comparable to the
mid-20th-century warm period (;1935–1965).
This result occurs because Medieval tem-
perature peaks were not synchronous in all
records (12). The two temperature recon-
structions also agree closely in estimating
an ;0.4°C warming between the 17th-cen-
tury and the mid-20th-century warm period
(18).
Volcanic forcing. There is increasing
evidence (3, 7–10) that pulses of volcanism
significantly contributed to decadal-scale
climate variability in the Little Ice Age.
Although some earlier studies (9, 10)of
forced climate change back to 1400 used a
composite ice core index of volcanism (19),
which has a different number of records per
unit of time, the present study primarily
uses two long ice core records from Crete
(20) and the Greenland Ice Sheet Project 2
(GISP2) (21) on Greenland, with a small
augmentation from a study of large erup-
tions recorded in ice cores from both
Greenland and Antarctica (22). This ap-
proach avoids the potential for biasing
model results versus time because of
changes in the number of records. Because
Southern Hemisphere volcanism north of
20°S influences Northern Hemisphere tem-
peratures, the ice core volcano census sam-
ples records down to this latitude. The vol-
canism record is based on electrical con-
ductivity (20) or sulfate measurements
(21), and a catalog of volcanic eruptions
(23) was used to remove local eruptions
(24) and identify possible candidate erup-
tions in order to weight the forcing accord-
ing to latitude. Eruptions of unknown ori-
gin were assigned a high-latitude origin
unless they also occurred in Antarctic ice
core records (22).
The relative amplitude of volcanic peaks
was converted to sulfate concentration by
first scaling the peaks to the 1883 Krakatau
peak in the ice cores. Although earlier studies
(9, 10) linearly converted these concentration
changes to radiative forcing changes, subse-
quent comparison (25) of the very large 1259
eruption [eight times the concentration of
sulfate in ice cores from Krakatau and three
times the size of the Tambora (1815) eruption
(21)] with reconstructed temperatures (11–
14) failed to substantiate a response com-
mensurate with a linearly scaled prediction of
an enormous perturbation of;25 W/m
2
(26).
Calculations (27) suggest that for strato-
spheric sulfate loadings greater than about 15
megatons (Mt), increasing the amount of sul-
fate increases the size of aerosols through
coagulation. Because the amount of scattered
radiation is proportional to the cross-sectional
area, and hence to the 2/3 power of volume
(or mass), ice core concentrations estimated
as .15 Mt were scaled by this amount (25).
Aerosol optical depth was converted to
changes in downward shortwave radiative
forcing at the tropopause, using the relation-
ship discussed in Sato et al. (28). There is
significant agreement (29) between the 1000-
year-long volcano time series and the concen-
tration-modified Robock and Free (19) times
series (Fig. 2A). Both proxy records show the
general trends estimated from ground-based
observations of aerosol optical depth (28): the
pulse of eruptions in the early 20th century
and the nearly 40-year quiescent period of
volcanism between about 1920–1960. Be-
cause volcano peaks are more difficult to
determine in the expanded firn layer of snow/
ice cores, updated estimates of Northern
Hemisphere radiative forcing from Sato et al.
were used to extend proxy time series from
1960 to 1998.
Solar forcing. There has been much dis-
cussion about the effect of solar variability on
decadal-to-centennial–scale climates (3, 6,
8–10). An updated version of a reconstruc-
tion by Lean et al. (5) that spans the interval
1610–1998 was used to evaluate this mech-
anism [for reference, Free and Robock (10)
obtained comparable solar-temperature corre-
lations for the interval 1700–1980 using the
Lean et al. and alternate Hoyt and Schatten
(4) solar reconstructions]. The Lean et al.
time series has been extended to 1000 by
splicing in different estimates of solar vari-
ability based on cosmogenic isotopes. These
estimates were derived from ice core mea-
surements (30)of
10
Be, residual
14
C from
tree ring records (31), and an estimate of
14
C
from
10
Be fluctuations (30). The justification
for including the latter index is that neither of
Fig. 1. Comparison of decadally smoothed Northern Hemisphere mean annual temperature records
for the past millennium (1000–1993), based on reconstructions of Mann et al. (Mn) (11) and CL
(12). The latter record has been spliced into the 11-point smoothed instrumental record (16) in the
interval in which they overlap. CL2 refers to a new splice that gives a slightly better fit than the
original (12). The autocorrelation of the raw Mann et al. time series has been used to adjust (adj)
the standard deviation units for the reduction in variance on decadal scales.
R ESEARCH A RTICLES
www.sciencemag.org SCIENCE VOL 289 14 JULY 2000 271