Mengis, Nadine; et al. (2018): Systematic Correlation Matrix Evaluation (SCoMaE) – a bottom–up, science-led approach to identifying indicators

Mengis, Nadine; Keller, David P.; Oschlies, Andreas (2018): Systematic Correlation Matrix Evaluation (SCoMaE) [&]ndash; a bottom[&]ndash;up, science-led approach to identifying indicators. In Earth Syst. Dynam. 9 (1), pp.[nbsp]15–31. DOI: 10.5194/esd-9-15-2018.

The example application of the SCoMaE method to Earth system model output forced by different CO2 emission scenarios reveals the necessity of reevaluating indicators identified in a historical scenario simulation for an accurate assessment of an intermediate–high, as well as a business-as-usual, climate change scenario simulation. This necessity arises from changes in prevailing correlations in the Earth system under varying climate forcing. For a comparative assessment of the three climate change scenarios, we construct and evaluate a common correlation matrix, in which we identify robust correlations between variables across the three considered scenarios.