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exchanges, (c) reconstructing full global grids using the
spatial and temporal covariance of the field (e.g., Smith et al.,
1998), and (d) developing new space-based observing systems.
However, global coverage of in situ data can never be achieved,
particularly historically. Therefore, inventive area averaging
techniques have been developed to provide robust estimates of
global temperatures. These techniques include grid-box averaging of
climate anomalies (e.g., Jones, 1994), or averaging of the
interannual change in temperature (Peterson et al., 1998a). A more
complex approach that interpolates anomalies adjusted to regional
reference stations produces information for each grid box (Hansen
and Lebedeff, 1987). Smith et al. (1998) also fill in the full grid
using the spatial and temporal covariance of the sea surface
temperature field together with the available data. Within this
latter approach is the assumption that the covariance pattern
developed in the satellite era is an appropriate guide for
interpolating data in earlier eras.
Several efforts have been made to put error bars on global
surface temperature time series, primarily by focusing on the
impact of inadequate spatial sampling and using model simulations
of global climate. Jones et al. (1997) estimated that the typical
standard errors for annual data on the interannual time scale since
1951 are about ±0.06 °C.13 Errors associated with century-scale
surface temperature trends are probably an order of magnitude
smaller than the observed warming of about 0.5 °C per 100 years
since the late nineteenth century (Karl et al., 1994).break
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