Global Air Temperature and Precipitation: Regridded Monthly and Annual Climatologies

(Version 2.01)

reinterpolated and documented by

Cort J. Willmott, Kenji Matsuura and David R. Legates
(with support from NASA's Seasonal to Interannual ESIP)

For additional information concerning this archive, please contact us at:

Center for Climatic Research
Department of Geography
University of Delaware
Newark, DE 19716
(302) 831-2294

or

kenjisan@udel.edu


Archive (Version 2.01) created November 18, 1998


DATA SOURCES:

Legates and Willmott's (1990a and b) station records of monthly and annual mean air temperature (T) and precipitation (P) were used to produce this archive. The number of stations (and oceanic grid nodes) used was 24,941 for air temperature, and 26,858 for precipitation, respectively.

SPATIAL INTERPOLATION:

Traditional reinterpolation 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 and precipitation 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 and precipitation fields. A more robust neighbor finding algorithm, based on spherical distance, also was developed and used.

Incorporating station-height information, 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 is first "brought down" to sea level at the average environmental lapse rate (6.5 deg C/km). Traditional interpolation is performed on the adjusted-to-sea-level station air temperatures. Then, the gridded sea-level air temperatures are brought up to the DEM-grid height, again, at the average environmental lapse rate.

SPATIAL CROSS VALIDATION:

To indicate (roughly) the spatial interpolation errors, station-by-station cross validation was employed (Willmott and Matsuura, 1995). One station is removed at a time, and air temperature (or precipitation) is 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 is made, the removed station is 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 or precipitation field.

ARCHIVE STRUCTURE:

air_temp.clim:
Average monthly and annual air temperature interpolated to a 0.5 by 0.5 degree grid resolution (centered on 0.25 degree). The format of each record is
Field Columns Variable Fortran Format
1 1 - 8 Longitude (decimal degrees)
F8.3
2 9 - 16 Latitude (decimal degrees)
F8.3
3-14 17 - 100 Monthly Air Temperature (deg C, Jan - Dec)
12F7.1
15 101 - 107 Mean Annual Air Temperature
F7.1

air_temp.cve.clim:
Cross-validation errors associated with air temperatures interpolated to a 0.5 by 0.5 degree grid resolution. The format of each record is
Field Columns Variable Fortran Format
1 1 - 8 Longitude (decimal degrees)
F8.3
2 9 - 16 Latitude (decimal degrees)
F8.3
3-14 17 - 100 Cross-validation errors for Monthly Air Temperature (deg C , Jan - Dec)
12F7.1
15 101 - 107 Cross-validation errors for Mean Annual Air Temperature
F7.1

air_temp_dem.clim:
Average monthly and annual air temperature interpolated with Willmott and Matsuura's (1995) DEM-assisted algorithm to a 0.5 by 0.5 degree grid resolution. The format for each record is the same as for the air_temp.grid file.

air_temp_dem.cve.clim:
DEM-assisted air-temperature cross-validation errors interpolated to a 0.5 by 0.5 degree grid resolution. The format of each record is the same as for the air_temp.cve.grid.

precip.clim:
Average monthly and annual precipitation interpolated to a 0.5 by 0.5 degree grid resolution. The format of each record is
Field Columns Variable Fortran Format
1 1 - 8 Longitude (decimal degrees)
F8.3
2 9 - 16 Latitude (decimal degrees)
F8.3
3-14 17 - 100 Monthly Precipitation (mm, Jan - Dec)
12F7.1
15 101 - 107 Mean Annual Precipitation
F7.1

precip.cve.clim:
Cross-validation errors associated with average monthly and annual precipitation interpolated to a 0.5 by 0.5 degree grid resolution. The format of each record is
Field Columns Variable Fortran Format
1 1 - 8 Longitude (decimal degrees)
F8.3
2 9 - 16 Latitude (decimal degrees)
F8.3
3-14 17 - 100 Cross-validation errors for Monthly Precipitation (mm, Jan - Dec)
12F7.1
15 101 - 107 Cross-validation errors for Mean Annual Precipitation
F7.1

precip_corrected.clim:
Average monthly and annual gage-corrected precipitation interpolated to a 0.5 by 0.5 degree grid resolution. The format of each record is the same as for the precip.grid file.

precip_corrected.cve.clim:
Cross-validation errors associated with monthly and annual raingage corrected precipitation interpolated to a 0.5 by 0.5 degree grid resolution. The format of each record is the same as for the precip.cve.grid file.


SELECTED REFERENCES:

Legates, D. R. and C. J. Willmott (1990a) Mean Seasonal and Spatial Variability Global Surface Air Temperature. Theoretical and Applied Climatology , 41, 11-21.

Legates, D. R. and C. J. Willmott(1990b) Mean Seasonal and Spatial Variability in Gauge-Corrected, Global Precipitation. International Journal of Climatology, 10, 111-127.

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

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.