Tropical Land-Surface Precipitation: Gridded Monthly and Annual Climatologies

(Version 1.01)

produced and documented by

Michelle Johnson, Kenji Matsuura, Cort Willmott, and Petra Zimmermann
(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


Archive (Version 1.01) created May 1, 2003


Five sources of station data were used to produce these gridded monthly total precipitation (P) climatologies. The sources were: the Global Historical Climatology Network (GHCN version 2)(Peterson and Vose, 1997); the National Center for Atmospheric Research (NCAR) daily India data; Sharon Nicholson's archive of African precipitation data (2001); Webber and Willmott's (1998) South American monthly precipitation station records; and the station climatologies from Legates and Willmotts (1990) archive. Please also see the README file for Tropical Land-Surface Precipitation: Gridded Monthly and Annual Time Series (1950-1999).


Our traditional interpolation algorithm is based on the spherical version of Shepard's distance-weighting method (Shepard, 1968; Willmott et al., 1985). Over the period from 1950-1999, each month's station observations were spatially interpolated to a 0.5 degree by 0.5 degree of latitude/longitude grid, where the grid nodes were centered on 0.25 degree. The number of nearby stations that influenced 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 precipitation fields. A more robust neighbor finding algorithm, based on spherical distance, also was used.

Using a climatology available from a relatively dense network of stations also can increase the accuracy of spatially interpolated time series of monthly climate variables. Employing Climatologically Aided Interpolation (CAI) (Willmott and Robeson, 1995), a monthly P at each time-series station can be differenced from a climatologically averaged P for that month which is available at or can be interpolated to the time-series station location. Traditional interpolation then can be performed on the station differences to obtain a gridded difference field. Finally, the gridded difference field can be added to interpolated estimates of the climatology at the same set of grid points.

CAI was used to estimate our monthly total precipitation fields. For the background climatology, two station climatologies were merged. The first was calculated at those of our precipitation time-series stations which had at least five years of observations for each month (within the period 1960-1990). The second was the monthly station P climatology of Legates and Willmott (1990). Only those Legates and Willmott stations which were not collocated with our own 1960-1990 station climatology were included in the background climatology for CAI. The interpolated monthly P values at each grid node were averaged over the fifty-year period (1950-1999) to obtain climatological averages for each month.


To indicate (roughly) the spatial interpolation errors, station-by-station cross validation was employed (Willmott and Matsuura, 1995). One station is removed from the station network at a time, and then precipitation is interpolated to the removed station location from the surrounding nearby stations. The difference between the interpolated station value and the observed 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 precipitation field. These monthly cross-validation errors then were averaged over the fifty years (1950-1999) to obtain an average monthly and annual cross-validation error at each grid node.


Average monthly and annual total precipitation (for the years 1950 - 1999) on a 0.5 by 0.5 degree grid. The format of each record is
Field Columns Variable Fortran Format
1 1 - 8 Longitude (decimal degrees)
2 9 - 16 Latitude (decimal degrees)
3-14 17 - 112 Average Monthly Total Precipitation (mm, Jan - Dec)
15 113 - 120 Mean Annual Total Precipitation (mm)

Average cross-validation errors associated with monthly and annual total precipitation on a 0.5 by 0.5 degree grid. The format of each record is
Field Columns Variable Fortran Format
1 1 - 8 Longitude (decimal degrees)
2 9 - 16 Latitude (decimal degrees)
3-14 17 - 112 Mean Cross-Validation Errors for Monthly Total Precipitation (mm, Jan - Dec)
15 113 - 120 Mean Cross-Validation Errors for Annual Total Precipitation (mm)


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.

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(12), 2837-2849.

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.