C and N models intercomparison - benchmark and ensemble model estimates for grassland production

Uncertainties in the response of crop and grassland models can be attributed to differences in the structure of different models. This has urged for benchmarking actions at an international level, where estimation of process-oriented epistemic uncertainties is done by running several models simulating the same physical and management conditions (ensemble modelling) so as to generate expanded envelopes of uncertainty (e.g. Asseng et al., 2013). Simulations of the agricultural C and N fluxes, in particular, are inherently uncertain because driven by complex interactions (e.g. Sándor et al., 2016) and there is also considerable spatial and temporal variability in the measurements. In this context, the Integrative Research Group of the Global Research Alliance (GRA) on Agricultural Greenhouse Gases promotes a coordinated activity across multiple international projects (e.g. C-N MIP and Models4Pastures of the FACCE-JPI, https://www.faccejpi.com) to benchmark and compare simulation models estimating C-N related outputs (including greenhouse gas emissions) from arable crop and grassland systems (http://globalresearchalliance.org/e/model-intercomparison-on-agricultural-ghg-emissions). Consistent with ongoing modelling actions, this study presents some preliminary results on the uncertainty of outputs from 12 grassland models while exploring model differences when calibration is performed with increasing data resources.