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

“气候模型预测了21世纪极端降水的普遍加剧，这与观察到的趋势一致(Westra等人。2013年；Fischer&Knutti 2016年)，但区域变化模式存在很大的不确定性(Donat等人。2016年)阻碍了制定有效的洪灾适应战略。洪水对公共安全、生命和经济构成巨大挑战(Pielke And Downton 2000)，并在2017年气候变化风险评估(CCRA 2017)中被确定为英国的首要任务和风险。短时(次日)极端降雨引起的山洪暴发特别危险，并造成人员伤亡(Archer和Fowler 2016)，因为它们在没有任何预警的情况下发生。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。这些被认为与不同的驱动因素有关--大规模大气环流的变化和热力学(通常发生在当地范围内的温度和湿度)的变化。该项目提供了机会，利用新的全球高分辨率观测仪和卫星降水数据集以及极高分辨率对流气候模型的输出来审查其中一些问题，以探讨已确定的驱动因素今后可能如何变化。将发展的技能取决于所采取的方法，但可包括：大数据集的统计分析；空间建模(例如地理信息系统)；气候模型分析“。

"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"