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In the 10,000 km(2) San Pedro River watershed area in south-eastern Arizona, high-resolution spatial patterns of long-term precipitation and temperature were better reproduced by kriging climate data with elevation as external drift (KED) than by multiple linear regression on station location and elevation as judged by the spatial distribution of interpolation error. Mean errors were similar overall, and interpolation accuracy for both methods increased with increasing correlation between climate variables and elevation. Uncertainty in station locations had negligible effect on mean estimation error, although error for individual stations varied as much as 27%. Our future ability to examine spatial aspects of climate change at high spatial resolution will be severely limited by continuing closures of climate stations in this part of the United States. (C) 2003 Elsevier Science Ltd.