Some Comments on the Evaluation of Model Performance

TLDR

Fox (1981) examined quantitative model‑performance evaluation and argued that Pearson’s correlation is often misleading. The paper proposes a revised set of performance statistics. The authors introduce a core set of difference and summary univariate indices and illustrate their use by comparing two monthly evapotranspiration models. The comparison of the two evapotranspiration models demonstrates the applicability of the proposed evaluation method.

Abstract

Quantitative approaches to the evaluation of model performance were recently examined by Fox (1981). His recommendations are briefly reviewed and a revised set of performance statistics is proposed. It is suggested that the correlation between model-predicted and observed data, commonly described by Pearson's product-moment correlation coefficient, is an insufficient and often misleading measure of accuracy. A complement of difference and summary univariate indices is presented as the nucleus of a more informative, albeit fundamentally descriptive, approach to model evaluation. Two models that estimate monthly evapotranspiration are comparatively evaluated in order to illustrate how the recommended method(s) can be applied.