ABSTRACT: Future warming in West Africa will have a detrimental effect on the communities living there. To support assessments of climate change impacts, we propose a method for refining regional temperature projections and demonstrate its application to West Africa for the mid-21st century. Our focus is on characterising uncertainty more comprehensively by considering projections of global warming. We calculate a transformation between a frequency distribution of global warming values derived from the Coupled Model Intercomparison Project phase 5 (CMIP5) models and a broader published probability distribution of global warming developed by the Met Office. The latter draws on perturbed parameter ensembles of simpler climate models to account for uncertainties related to the atmosphere, ocean, carbon cycle and aerosol processes that are not well characterised by the CMIP5 ensemble. Noting that West African warming is highly correlated with global warming in the CMIP5 ensemble, and that a significant portion of the uncertainty in projected West African warming arises from the uncertainty in global warming, we then apply the same transformation to CMIP5-derived distributions for warming in different regions of West Africa. The resultant regional warming distributions have longer tails than distributions estimated directly from the CMIP5 ensemble. Our results imply that CMIP5-based assessments of temperature-sensitive applications may underestimate the probability of large (and small) impacts. Our method could be used to refine temperature projections for other regions of the world in which regional temperature changes are highly correlated with global mean temperature changes.

中文翻译：

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完善对西非未来温度变化的预测

摘要：西非未来变暖将对居住在那里的社区产生不利影响。为了支持对气候变化影响的评估，我们提出了一种改进区域温度预测的方法，并展示了其在21世纪中叶对西非的应用。我们的重点是通过考虑全球变暖的预测来更全面地描述不确定性。我们计算了从耦合模型比对项目第5阶段（CMIP5）模型得出的全球变暖值的频率分布与由Met Office开发的更广泛的全球变暖概率分布之间的转换。后者利用较简单的气候模型的扰动参数组合来解决与大气，海洋，CMIP5集成无法很好地表征碳循环和气溶胶过程。注意到西非变暖与CMIP5总体中的全球变暖高度相关，并且预计西非变暖的很大一部分不确定性是由全球变暖的不确定性引起的，因此我们将相同的变换应用于源自CMIP5的变暖分布在西非的不同地区。所得的区域变暖分布的尾部比直接从CMIP5集成估计的分布更长。我们的结果表明，对温度敏感应用的基于CMIP5的评估可能低估了大（小）影响的可能性。