Abstract
Abstract Climate models are becoming evermore complex and increasingly relied upon to inform climate change adaptation. Yet progress in model development is lagging behind in many of the regions that need the information most, including in Africa. Targeted model development for Africa is crucial and so too is targeted model evaluation. Assessment of model performance in specific regions often follows a “validation” approach, focusing on mean biases, but if models are to be improved, it is important to understand how they simulate regional climate dynamics: to move from validation to process-based evaluation. This evaluation may be different for every region and requires local weather and climate expertise: a “one size fits all” approach could overlook important, region-specific phenomena. So which are the important processes in African regions? And how might they be evaluated? This paper addresses these questions, drawing on the expertise of a team of scientists from Central, East, southern, and West Africa. For each region, the current understanding of climate models is reviewed, and an example of targeted evaluation is provided, including analysis of moist circulations, teleconnections, and modes of variability. A pan-African perspective is also considered, to examine processes operating between regions. The analysis is based on the Met Office Unified Model, but it uses diagnostics that might be applied to other models. These examples are intended to prompt further discussion among climate modelers and African scientists about how to best evaluate models with an African lens, and promote the development of a model evaluation hub for Africa, to fast track understanding of model behavior for this important continent.
Highlights
Africa lags the rest of the world in climate model development
As part of phase 6 of CMIP (CMIP6), there wealth of relevant expertise in African meteorological is a drive to advance evaluation through the routine services and universities, with many scientists focus- deployment of community-based analysis tools to ing on observations or weather time scales who have document and benchmark model behavior (Eyring the potential to contribute to climate model develop- et al 2016b)
The bias in SON extends to the west of Central Africa, and almost the entire Congo basin is drier than Global Precipitation Climatology Project (GPCP) during DJF, there is large observational uncertainty for this region (Washington et al 2013)
Summary
The presence of strong land–atmosphere interactions (Koster et al 2004; Taylor et al 2013), large aerosol emissions from arid regions (Engelstaedter et al 2006; Allen et al 2013), influences from global ocean basins (Folland 1986; Rowell 2013), and prominent modes of interannual and interdecadal rainfall variability (Giannini et al 2008) exacerbates the challenge. Some of these features and systems are poorly understood as a result of limited access to readily available observations (Fig. 1) and research attention. There are growing efforts to bolster African climate science (Shongwe 2014), to run and evaluate regional and variable-resolution models over
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