Uncertainties in climate change prediction and modelling

Abstract

As models become increasingly complex and integrated, uncertainty among model  parameters, variables and processes become critical for evaluating model outcomes and  predictions. A framework for understanding uncertainty in climate modelling has been  developed by the IPCC and EEA which provides a framework for discussion of uncertainty  in models in general. Here we report on a review of this framework along with the results  of a survey of sources of uncertainty in livestock and grassland models. Along with the  identification of key sources of uncertainty in livestock and grassland modelling, the  survey highlighted the need for a development of a common typology for uncertainty.  When collaborating across traditionally separate research fields, or when communicating  with stakeholders, differences in understanding, interpretation or emphasis can cause  confusion. Further work in MACSUR should focus on improving model intercomparison  methods to better understand model uncertainties, and improve availability of high  quality datasets which can reduce model uncertainties.