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Contents
A Topographic and Climate Database for AfricaA topographic and climate database for Africa has been developed by the Centre for Resource and Environmental Studies (CRES) using the software ANUDEM and ANUSPLIN respectively. A CD containing the data (CRES_AFR_01) is available for a minimal cost. Last revision to this document:26 September 1995
Authors:M.F.Hutchinson, H.A.Nix, J.P.McMahon, and K.D.Ord, Centre for Resource and Environmental Studies, Australian National University, Canberra ACT 0200, AUSTRALIA.
This document:README.TXT on CRES_AFR_01
IntroductionThis document describes 85 files on CRES_AFR_01 making up a database consisting of:
The DEM and the climate grid files were created using spatial analysis and interpolation techniques developed by the Centre for Resource and Environmental Studies (CRES) at the Australian National University. The DEM was created using the elevation gridding ANUDEM procedure (Hutchinson 1988,1989). The climate grids were obtained by first fitting topographically dependent climate surfaces to point climate data using procedures in the ANUSPLIN package (Hutchinson 1991, Hutchinson and Gessler 1994). The surfaces were then interrogated using elevations from the DEM using the ANUCLIM package (McMahon et al. 1995). Both elevation and climate data were subjected to comprehensive error detection and correction procedures based on ANUDEM and ANUSPLIN. Accurate geocoding (longitude, latitude and elevation) of climate station data was completed by CRES for many stations. Complete descriptions of the topographic and climate are being prepared (Hutchinson, Nix, McMahon and Ord, in prep).
Topographic DataTopographic data were digitised by CRES from 1:1M scale air navigation charts covering the entire continent, augmented by miscellaneous maps at larger scales in areas where data on the air navigation charts were sparse. The data digitised from these maps consisted of: 1. All spot heights. 2. Selected points on elevation contours. All significant corners on contours, consistent with an eventual final grid resolution of approximately 1 minute of longitude and latitude, were selected. Thus points on contours were not sampled at spacings closer than 1 minute. 3. Selected stream lines. All streams which could be resolved on an eventual final grid resolution of 1 minute of longitude and latitude were selected. Only very minor streams on the 1:1M air navigation charts were omitted. The standard error of the DEM ranges between about 20 and 150 metres, depending mainly on terrain roughness.
Climate DataMonthly mean values of rainfall, daily minimum temperature and daily maximum temperature at a sufficient spatial density to support reliable spatial interpolation were compiled. In addition to data already obtained by CRES from miscellaneous sources, monthly climate data were acquired from research agencies including CIMMYT, FAO, East Anglia Climate Research Unit, CSIRO Division of Forestry, Texas A&M University and from the national meteorological services of Djibouti, Gambia, Ghana, Kenya, Malawi, Morocco, Nambia, Rwanda, Seychelles, Sudan, Tanzania, Uganda and Zaire. Data were collected over all available years of record to maximise spatial coverage, subject to the condition that rainfall averages were for at least five years of record. Most data were collected between about 1920 and 1980 for both temperature and rainfall, so the fitted climates grids can be interpeted as estimates of standard means for the period 1920 to 1980. The number of accurately geocoded stations for which monthly mean climate data were obtained were as follows:
The error of the climate grids depends mainly on the accuracy of the underlying climate surfaces. In using the DEM to calculate the climate grids, the stated errors in the DEM of up to a few hundred metres make only a minor additional contribution to errors in the climate grids. The standard errors of the temperature are about 0.5 degrees centigrade. The standard errors of the rainfall grids range between about 5 and 15 per cent, depending on data density and the spatial variability of the actual monthly mean rainfall.
AcknowledgmentsFunding for the project was provided by the Australian International Development and Assistance Bureau. Digitising and checking of topographic and climate data formed the major portion of the work required to produce this data base. In this the authors gratefully acknowledge many willing contributors, including Fareeha Ibrahim, Helen Neave, Christy Sanders, Joseph Tabone and Karen Weinman.
ReferencesHutchinson,M.F. 1988. Calculation of hydrologically sound digital elevation models. Third International Symposium on Spatial Data Handling, International Geographical Union, Columbus, 117-133. Hutchinson,M.F. 1989. A new procedure for gridding elevation and stream line data with automatic removal of spurious pits. Journal of Hydrology 106: 211-232. Hutchinson,M.F. 1991. The application of thin plate splines to continent-wide data assimilation. In: J.D.Jasper (ed), Data Assimilation Systems. BMRC Res. Rep. No. 27, Bureau of Meteorology, Melbourne, 104-113. Hutchinson,M.F. 1995. Interpolating mean rainfall using thin plate smoothing splines. International Journal of Geographic Information Systems 9: 385-403. Hutchinson,M.F. and Gessler,P.E. 1994. Splines - more than just a smooth interpolator. Geoderma 62: 45-67. McMahon,J.P., Hutchinson,M.F., Nix,H.A. and Ord,K.D. 1995. ANUCLIM User's Guide. Draft Report, Centre for Resource and Environmental Studies, Australian National University, Canberra. Hutchinson,M.F., Nix,H.A., McMahon,J.P. and Ord,K.D. (in prep). The development of a topographic and climate data base for Africa.
Contents of CD - CRES_AFR_01
Feedback WelcomeYour comments and feedback on the documentation and the data itself are invaluable to us. Please mail your comments to Michael Hutchinson |
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