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A CSAG PhD student, Hussen Seid Endris has had a publication accepted by the Journal of Climate.  The paper investigates the performance of a suite of ten Regional Climate Models simulating the historical climate of East Africa and as such falls under the CORDEX Africa activities  Significant results are that the models are generally able to capture the climatology and seasonality of the regions in question and some models are also able to capture the response to large scale sources of variability, namely ENSO and the Indian Ocean Dipole (IOD).  The paper concludes that RCMs have some skill in the region and could be used to explore regional responses to future climate change in the East African region, a region that is highly vulnerable to changing climate patterns.

Read the full publication (early online release)

Abstract:

This study evaluates the ability of ten Regional Climate Models (RCMs) from the COordinated Regional climate Downscaling Experiment (CORDEX) in simulating the characteristics of rainfall patterns over Eastern Africa region. The seasonal climatology, annual rainfall cycles, interannual variability of RCMs output have been assessed over three homogeneous sub-regions against a number of observational datasets. We further assess the ability of the RCMs in simulating large-scale global climate forcing signals by compositing the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events. We find that most RCMs fairly simulate the main features of the rainfall climatology over the three sub-regions and also reproduce the majority of the documented regional responses to ENSO and IOD forcings. At the same time our analysis shows significant biases in individual models depending on sub-region and season, however the ensemble mean has better agreement with observation than individual models. In general, our analysis has demonstrated that the multi-model ensemble mean simulate Eastern Africa rainfall adequately and can therefore be used for the assessment of future climate projections for the region.

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