Terrestrial Air Temperature and Precipitation: Monthly and Annual Climatologies

(Version 3.01)

produced and documented by

Cort J. Willmott and Kenji Matsuura
(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 3.01) created January 31, 2000

DATA SOURCES:

Global Historical Climatology Network (GHCN version 2) and Legates and Willmott's (1990a and b) station records of monthly and annual mean air temperature (T) and total precipitation (P) were used to produce this archive. The time period evaluated was 1950 through 1996. The total number of GHCN stations used was 7280 for air temperature, and 20,782 for precipitation. However, the actual number of GHCN stations available for each year varies from about 1600 to 5400 for air temperature and from about 1100 to 14,800 for precipitation. The number of stations (and oceanic grid nodes) taken from the Legates and Willmott archive was 24,941 for air temperature, and 26,858 for precipitation, respectively. Our DEM-assisted Legates and Willmott archive (Willmott, Matsuura and Legates, 1998, Version 2.01) was used as the background field for the Climatologically Aided Interpolation (CAI) (see below).

SPATIAL INTERPOLATION:

Our traditional interpolation algorithm is based on the spherical version of Shepard's distance-weighting method (Shepard, 1968; Willmott et al., 1985). Station averages of monthly 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). Using digital-elevation-model or DEM-assisted interpolation, station air temperature is first "brought down" to sea level at an average environmental lapse rate (6.0 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.

Using a climatology available from a relatively dense network of stations can also increase the accuracy of spatially interpolating monthly climate variables. Employing Climatologically Aided Interpolation (CAI) (Willmott and Robeson, 1995), a monthly climate variable at each station is differenced from a monthly climatological average available at or interpolated to the station location. Traditional interpolation then is performed on the station differences to obtain a gridded difference field. Then, the gridded difference field is added to the estimates of climatology at the same grid points. Our air-temperature climatology was created using DEM-assisted interpolation while our precipitation climatology was traditionally interpolated.

Both DEM-assisted interpolation and CAI were employed to estimate these monthly fields. An average environmental lapse rate of 6.0 (deg C/Km) was employed, rather than the 6.5 (deg C/Km) figure that was used in earlier applications, because some of our recent research suggests that 6.0 is closer to the true, global average. Each grid-point climatological average was obtained as the average of the 564 interpolated monthly values available at the grid node for the period from 1950 through 1996.

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. The time-averaged cross-validation errors then were interpolated to the grid nodes to create our climatologies of the cross-validation errors.

ARCHIVE STRUCTURE:

cai_temp.clim:
Average monthly and annual air temperature, representing the period 1950 - 1996, 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 - 112 Mean Monthly Air Temperature (deg C, Jan - Dec)
12F8.1
15 113 - 120 Mean Annual Air Temperature
F8.1

cai_temp.cv.clim:
Cross-validation errors associated with cai_temp.clim. 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 - 112 Mean Cross-Validation Errors for Monthly Air Temperature (deg C, Jan - Dec)
12F8.1
15 113 - 120 Mean Cross-Validation Errors for Mean Annual Air Temperature (deg C)
F8.1

cai_precip.clim:
Average monthly and annual total precipitation, representing the period 1950 - 1996, 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 - 112 Average Monthly Total Precipitation (mm, Jan - Dec)
12F8.1
15 113 - 120 Mean Annual Total Precipitation (mm)
F8.1

cai_precip.cv.clim:
Mean Cross-validation errors associated with cai_precip.clim. 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 - 112 Mean Cross-Validation Errors for Monthly Total Precipitation (mm, Jan - Dec)
12F8.1
15 113 - 120 Mean Cross-Validation Errors for Annual Total Precipitation (mm)
F8.1

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.

Willmott, C. J. and S. M. Robeson (1995) Climatologically Aided Interpolation (CAI) of Terrestrial Air Temperature. International Journal of Climatology, 15, 221-229.