Elk–testing climate–carbon cycle models: a case for pattern–oriented system analysis

Abstract

Process–oriented models are a primary tool being used to project future states of climate and ecosystems in the Earth system in response to anthropogenic and other forcing. Coupled climate–carbon cycle models receive tremendous attention, especially in the context of the 5th assessment report of the IPCC (International Panel on Climate Change). However, intercomparison of model scenarios indicate large uncertainties regarding predictions of global interactions between atmosphere and biosphere. Rigorous scientific testing of these models is essential but very challenging, largely because it is neither technically nor ethically possible to perform global earth– scale experiments—we do not have replicate Earths for hypothesis testing. Hence, model evaluations have to rely on monitoring data such as ecological observation networks, global remote sensing, paleo proxy data, or small–scale manipulative experiments. Here, we critically examine strategies of how model evaluations should be performed. We put a particular emphasis on the representation of terrestrial ecosystems, where the two key problems are: 1. weak (or inconclusive) ‘validations’ which do not take advantage of all the relevant information in the observed data, and 2. apparent falsifications: “false alarms” likely to occur when individual system processes (in the model) are compared to the overall emergent system behaviour (of the observed world)