TABLE 1 Temperature Indices Used in This Study

Type of Record

Time Coverage


Index No.*

Ice-core d18O

Agassiz Ice Cap (Ellsmere Is.)

A.D. 1349-1977

Fisher and Koerner (1983)


Devon Island Ice Cap

A.D. 1512-1973

Koerner (1977)


Camp Century (Greenland)

A.D. 1176-1967

Johnsen et al. (1972)


Milcent (Greenland)

A.D. 1176-1967

Hammer et al. (1978)


Quelccaya Ice Cap (Peru)

A.D. 1481-1981

Thompson et al. (1986)


Dunde Ice Cap (China)

A.D. 1606-1987

Thompson et al. (1990)


Temperature reconstructions from tree rings

Western U.S. (annual) summer

A.D. 1602-1961

Fritts (1991)


Eastern U.S. (annual) summer

A.D. 1602-1961

Fritts (1991)


Western U.S. & SW Canada (annual) summer

A.D. 1602-1961

Fritts (1991)


Northern Treeline (North America) (annual)

A.D. 1601-1974

D'Arrigo & Jacoby (1992)


U.S. & SW Canada


A.D. 1600-1982

Briffa et al. (1992b)


Northern Scandinavia


A.D. 500-1980

Briffa et al. (1992a)


Northern Urals (June-July)

A.D. 961-1969

Graybill and Shiyatov (1992)


Tasmania, Australia


A.D. 900-1989

Cook et al. (1992)


Patagonia, Argentina


A.D. 1500-1974

Boninsegna (1992) & Villalba et al. (1989)


Rio Alerce, Argentina


A.D. 870-1983

Villalba (1990)



Central England Temperature (annual)

A.D. 1660-1987

Manley (1974)


Dec-Jan-Feb series




June-July-Aug series




* These numbers are used in text and later tables to identify the various indices.

climate-sensitive tree-ring records that have been thoroughly documented in the refereed scientific literature. Second, we chose the longest of those records in order to maximize the temporal coverage, and tried, as far as possible, to select samples from representative geographical areas.

A number of problems are inherent in any climate reconstruction. These problems are discussed in detail in the original published papers; however, we will briefly highlight here the more critical ones as they may affect the results presented below. Because we have analyzed changes in variability, temporal changes in the composition of the tree-ring network used for the reconstructions will, in general, affect the high-frequency variance, and to some degree the low-frequency variance as well. In interpreting the temperature reconstructions shown here, we have taken into account these potential sources of biases as much as possible.

Regardless of whether one uses the width of the annual growth rings or the maximum latewood density to reconstruct a particular climate variable (generally, growing-season temperature and/or precipitation), a process of standardization is required to account for different rates of tree growth as a function of age. This standardization is achieved by fitting a growth curve to the series of annual values, usually a cubic smoothing spline (see Cook and Kariukstis, 1990), and taking residuals about the smoothed curve. The degree of smoothing and the functional form of the growth curve partly determine the spectral properties of the residual series. In order to develop a climate reconstruction from these records, it is necessary to formulate a transfer function to convert the tree-growth index into, say, a temperature index. The procedure usually involves a calibration phase, in which a set of regression coefficients is derived that convert the tree-growth parameter into a climatic estimate, and a verification phase (see, e.g., Cook

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