New publication: African climate change uncertainty in perturbed physics ensembles: implications of global warming to 4°C and beyond

James, R., Washington, R., Rowell, D.P. (2014) African climate change uncertainty in perturbed physics ensembles: implications of global warming to 4°C and beyond. Journal of Climate doi: 10.1175/JCLI-D-13-00612.1

Abstract

The importance of investigating regional climate changes associated with degrees of global warming is increasingly being recognised, but the majority of relevant research has been based on multi-model ensembles (MMEs) from the Coupled Model Intercomparison Project (CMIP). This has left two important questions unanswered: are there plausible futures which are not represented by the models in CMIP? And, how would regional climates evolve under enhanced global warming, beyond 4°C? In this paper, two perturbed physics ensembles (PPEs) are used to address these issues with reference to African precipitation. Examination of model versions which generate warming greater than 4°C in the twenty-first century shows that changes in African precipitation are enhanced gradually, even to high global temperatures, however there may be nonlinearities which are not incorporated here due to limited model complexity. The range of projections from the PPEs is compared to CMIP3 and CMIP5 revealing regional differences. This is partly the result of implausible model versions, but the PPE dataset can be justifiably constrained due to its size and systematic nature; highlighting an additional advantage over MMEs. After applying constraints, the PPEs still show changes which are outside the range of CMIP, most prominently strong dry signals in west equatorial Africa and the Sahel, implying that MMEs may underestimate risks for these regions. Analysis of African precipitation changes therefore demonstrates that regional assessments which rely on CMIP3 and CMIP5 may overlook uncertainties associated with model parameterisations and pronounced warming. More systematic approaches are needed for conservative estimates of danger.