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
13 Unless stated otherwise, the quantitative error estimates given in this report represent 95% confidence intervals.