How will the persistence and intensity of preciptiation events change in the future?

“气候模型预测，与观测到的趋势一致，21世纪极端降水将普遍加剧（Westra et al. 2013; Fischer & Knutti 2016），但区域变化模式的巨大不确定性（Donat et al. 2016）阻碍了制定有效的洪水适应策略。洪水对公共安全、生活和经济构成了巨大挑战（Pielke and Downton 2000），在2017年气候变化风险评估（CCRA 2017）中，洪水被确定为英国的首要任务和风险。短时间（低于每日）极端降雨引发的山洪特别危险，会造成死亡（Archer和Fowler 2016），因为它们发生时几乎没有预警。因此，预测气候变化将如何改变降水模式对社会至关重要，如果我们使用基于事件的分析，检查降雨发生的间歇性，并将其与陆地上这些降雨事件的强度联系起来，我们可能能够更好地理解预测变化的驱动因素。这些变化被认为与不同的驱动因素有关——大尺度大气环流的变化和热力学的变化（经常发生在局部尺度上的温度和湿度）。该项目提供了利用新的全球高分辨率观测测量和卫星降水数据集以及非常高分辨率对流的输出来研究其中一些问题的机会，使气候模式能够探索已确定的驱动因素在未来可能如何变化。将发展的技能取决于所采取的方法，但可能包括：大型数据集的统计分析；空间建模（例如地理信息系统）；气候模式分析”

"Climate models project a general intensification of extreme precipitation during the 21st century, consistent with observed trends (Westra et al. 2013; Fischer & Knutti 2016) but large uncertainties in regional patterns of change (Donat et al. 2016) hamper the development of efficient adaptation strategies for flooding. Flooding presents a formidable challenge to public safety, life and the economy (Pielke and Downton 2000) and was identified as the top priority and risk for the UK in the 2017 Climate Change Risk Assessment (CCRA 2017). Flash floods from short-duration (sub-daily) rainfall extremes are particularly hazardous and responsible for fatalities (Archer and Fowler 2016), as they occur with little warning. Predicting how climate change will alter precipitation patterns is thus crucial for society and we may be able to better understand the drivers of predicted changes if we use an event-based analysis, examining intermittency in rainfall occurrence and linking this through to the intensity of these rainfall events over land. These are thought to be linked to distinct drivers - changes to large scale atmospheric circulation and changes in thermodynamics (temperature and humidity that often occurs at a local scale). This project provides the opportunity to examine some of these issues using new global high resolution observational gauge and satellite precipitation datasets and outputs from very-high resolution convection permitting climate models to explore how the identified drivers might change in the future. The skills that would be developed depend on the approach to be taken but could include: statistical analysis of large datasets; spatial modelling (e.g. GIS); climate model analysis"