We invite contributions describing the advances in model benchmarking, evaluation and verification for land surface model and data assimilation simulations and systems including: (1) Challenges and issues of land surface model benchmarking, availability and accuracy of observational datasets, (2) The use of novel, standardized model benchmarking, identification and verification metrics and tools, (3) The use of techniques and metrics beyond the traditional deterministic approaches (such as ensemble diagnostics, probabilistic verification measures), (4) The use of model identification measures to differentiate the performance of different models, (4) multi-model and ensemble diagnostics to characterize predictive uncertainties. In particular, we seek contributions that lead towards the definition and refinement of standardized measures of model performance for the land surface community.