Monthly-mean air-temperature records for 6487 independent land-surface weather stations located north of 43 N were used to produce this gridded archive. Some 1798 station records were drawn from version 2 of the Global Historical Climatology Network (Peterson and Vose, 1998), while 4655 station records were obtained from the Atmospheric Environment Service/Environment Canada. Fourteen more Russian station records were acquired through collaboration with the State Hydrometeorological Institute, St. Petersburg, Russia. Fourteen station records also were obtained for Greenland from the GC-Net (Steffen, 1996), while six Greenland station-records were acquired from the Automatic Weather Station Project (courtesy of Charles R. Stearns at the University of Wisconsin-Madison).

Traditional interpolation was accomplished with the spherical version of Shepard's algorithm, which employs an enhanced distance-weighting method (Shepard, 1968; Willmott et al., 1985). Station averages of air temperature were interpolated to a 0.5 degree by 0.5 degree of latitude/longitude grid, where the grid nodes are centered on 0.25 degree. The number of nearby stations that influence a grid-node estimate was increased to an average of 20, from an average of 7 in earlier applications. This resulted in smaller cross-validation errors (see below) and visually more realistic air-temperature fields. A more robust neighbor finding algorithm, based on spherical distance, also was used.

Incorporating elevational influences, through an average air-temperature lapse rate, can further increase the accuracy of spatially interpolating average air temperature (Willmott and Matsuura, 1995). Digital-elevation-model- or DEM-assisted interpolation of air temperature, therefore, was employed. Briefly, station air temperature was first "brought down" to sea level at an average environmental lapse rate (6.0 deg C/km). Traditional interpolation then was performed on the adjusted-to-sea-level station air temperatures. Finally, the gridded sea-level air temperatures were brought up to the DEM-grid height, again, at the average environmental lapse rate.

To indicate (roughly) the spatial interpolation errors, station-by-station cross validation was employed (Willmott and Matsuura, 1995). One station was removed at a time, and the air temperature was then interpolated to the removed station location from the surrounding nearby stations. The difference between the real station value and the interpolated value is a local estimate of interpolation error. After each station cross validation was made, the removed station was put back into the network. To reduce network biases on cross-validation results, absolute values of the errors at the stations were interpolated to the same spatial resolution as the air temperature field.

Peterson, T. C. and R. S. Vose (1997). An Overview of the Global Historical Climatology Network Temperature Database. Bulletin of the American Meteorological Society, 78, 2837-2849.

Shepard, D. (1968). A two-dimensional Interpolation function for irregularly-spaced Data. Proceedings, 1968 ACM National Conference, 517-523.

Steffen, K., J. E. Box, and W. Abdalati (1996). Greenland Climate Network: GC-Net. Colbeck, S. C. Ed. CRREL 96-27 Special Report on Glaciers, Ice Sheets and Volcanoes, trib. to M. Meier, 98-103.

Willmott, C. J., C. M. Rowe and W. D. Philpot (1985). Small-Scale Climate Maps: A Sensitivity Analysis of Some Common Assumptions Associated with Grid-point Interpolation and Contouring. American Cartographer, 12, 5-16.

Willmott, C. J. and K. Matsuura (1995). Smart Interpolation of Annually Averaged Air Temperature in the United States. Journal of Applied Meteorology, 34, 2577-2586.