The rationale for using multi-model ensembles in climate change projections and impacts
research is often based on the expectation that different models constitute independent …

The results of the sixth phase of the coupled model intercomparison project (CMIP) are
currently being analyzed and will form the basis of the IPCC Sixth Assessment Report. Since …

End users studying impacts and risks caused by human-induced climate change are often
presented with large multi-model ensembles of climate projections whose composition and …

An ensemble of models can be interpreted in two ways. The first treats each model as an
approximation of the true system with some random error. Alternatively, the true system can …

Multi-model ensembles are commonly used in climate prediction to create a set of
independent estimates, and so better gauge the likelihood of particular outcomes and better …

Multimodel ensembles are the main way to deal with model uncertainties in climate
projections. However, the interdependencies between models that often share entire …

Obtaining multiple estimates of future climate for a given emissions scenario is key to
understanding the likelihood and uncertainty associated with climate-related impacts. This is …

Recent coordinated efforts, in which numerous general circulation climate models have
been run for a common set of experiments, have produced large datasets of projections of …

Recent coordinated efforts, in which numerous climate models have been run for a common
set of experiments, have produced large datasets of projections of future climate for various …

As the number of models in Coupled Model Intercomparison Project (CMIP) archives
increase from generation to generation, there is a pressing need for guidance on how to …