Comparison of Interpolation Methods for Spatial Distribution of Monthly Precipitation in the State of Pernambuco, Brazil

Abstract

In the quest for a best approach to estimate the spatial distribution of monthly precipitation for the state of Pernambuco, Brazil, this work tests different versions (choices of parameters and functions) of seven interpolation methods, totaling 26 distinct interpolation schemes. The performance of each method in estimating monthly precipitation was evaluated through a set of seven measures of performance evaluation through a cross-validation procedure. It was found that the trend surface analysis yielded the best overall interpolation results, followed by natural neighbor method, inverse distance weighting, and kriging. Performance ranking of all 26 methods is provided. Moreover, in order to assess the regional performance quality of the best identified method (trend surface analysis) in estimating monthly precipitation, a spatially explicit error analysis was also performed for each of the evaluation measures. Finally, temporal evolution of the error evaluation measures of the best performing methods is presented in order to demonstrate the seasonal impact of interpolation.