COntinental COnvective OrganisatioN and rainfall intensification in a warming world: Improving storm predictions from hours to decades (COCOON)

变暖世界中的大陆对流组织和降雨强度：将风暴预测从几小时提高到几十年（COCOON）

• 批准号: NE/X017419/1
• 负责人: Cornelia Klein
• 金额: $ 94.32万
• 依托单位: UK CENTRE FOR ECOLOGY & HYDROLOGY
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FX017419%2F1
• 关键词: COntinental; COnvective; OrganisatioN; rainfall; intensification

Some of the most pressing questions in atmospheric and climate science today focus on how thunderstorms will respond to changes in the atmospheric environment. How will extreme rainfall change with climate change? And how do internal storm processes and dynamics affect these changes? Nowhere is the challenge more urgent than in (sub-)tropical regions where large thunderstorm clusters, so-called Mesoscale Convective Systems (MCSs) frequently cause severe weather and flooding, but population resilience is low due to poverty and staggering economies. To estimate and plan for future storm impacts, we need to understand and model how storm dynamics will respond (and are already responding) to atmospheric changes, and whether there are internal, dynamical mechanisms that may intensify rainfall extremes beyond purely thermodynamical considerations linked to increased moisture in a warmer atmosphere. In most affected regions, MCSs provide crucial water supplies for crops, livestock and people, contributing 50-90% to total rainfall but are likewise associated with severe weather that affects millions around the globe. A situation that will only worsen as temperatures continue to rise. And yet, in spite of the societal importance of MCSs, we still do not know why in particular their sub-daily rainfall extremes can frequently surpass expected intensities. The fact that the relative importance of external (e.g. atmospheric humidity, wind shear, temperature) and internal drivers (storm circulations, updraught speeds and size) of rainfall maxima remain unclear also hampers our ability to estimate global warming effects. Climate model assessments of driver contributions so far do not exist as conventional global climate models with coarse resolutions ~100km have major difficulties representing processes in the MCS scale range, which they can neither explicitly resolve nor satisfactorily parametrise, i.e. they do not 'see' MCSs. Over the last decade however, there have been rapid advances in the use of high-resolution (<10 km) regional convection-permitting (CP) models for climate prediction. Not having to rely on convective parametrisations, CP models produce more realistic peak rainfall intensities even compared to medium-resolution models, and can simulate realistic MCSs. However, even state-of-the-art CP models still operate in the "grey-zone" of 1-10km where internal storm circulations are only partly resolved. Consequences of the neglect of sub-grid processes are still under investigation and shortcomings need to be put under scrutiny.By combining earth observation data with emerging state-of-the-art CP climate model simulations, my project investigates how the scale of convection (contiguous cloud shields, embedded convective core scales, updraught size) affects MCS rainfall extremes and lifetimes over land. Based on earth observation data, my work will discover whether scales of continental convective organisation have changed within the last 20-30 years, and what processes are key to determining such trends. This will also explore whether MCS interactions with land features and atmospheric environments change as a function of convective scale. I will furthermore challenge CP models with the identified processes and develop process-based model benchmarking approaches, testing how trustworthy CP models are in capturing rainfall intensification mechanisms in a future climate. The findings will be used to trial methods for improved storm nowcasting and for improved estimates of future MCS rainfall extremes based on multiple lines of evidence that will crucially include convective scales. Thus, my project will bring a step-change in our understanding of how global warming drives convective scale changes, how rainfall and scales are linked, and whether scale information can improve extreme rainfall predictions on weather to climate timescales.

当今大气和气候科学中一些最紧迫的问题集中在雷暴将如何响应大气环境的变化。极端降雨量将如何随气候变化而变化？内部风暴过程和动态如何影响这些变化？没有什么地方比（亚）热带地区面临的挑战更紧迫了，那里的大型雷暴群，即所谓的中尺度对流系统（MCS）经常造成恶劣天气和洪水，但由于贫困和经济不稳定，人口的恢复能力很低。为了估计和规划未来的风暴影响，我们需要了解和建模风暴动力学将如何响应（并且已经响应）大气变化，以及是否存在可能加剧极端降雨的内部动态机制，超出与增加的纯粹热力学考虑有关的范围。温暖的气氛中的水分。在大多数受影响地区，MCS 为农作物、牲畜和人类提供重要的供水，占总降雨量的 50-90%，但同样与影响全球数百万人的恶劣天气有关。随着气温继续上升，这种情况只会变得更糟。然而，尽管 MCS 具有社会重要性，我们仍然不知道为什么它们的次日降雨量极端值经常超过预期强度。最大降雨量的外部驱动因素（例如大气湿度、风切变、温度）和内部驱动因素（风暴环流、上升气流速度和大小）的相对重要性仍不清楚，这一事实也阻碍了我们估计全球变暖影响的能力。迄今为止，还不存在对驱动因素贡献的气候模型评估，因为具有约 100 公里粗分辨率的传统全球气候模型在表示 MCS 尺度范围内的过程方面存在重大困难，它们既无法明确解决也无法令人满意地参数化，即它们无法“看到”MCS 。然而，在过去十年中，使用高分辨率（<10 公里）区域对流允许（CP）模型进行气候预测方面取得了快速进展。 CP 模型不必依赖对流参数化，即使与中等分辨率模型相比，也能产生更真实的峰值降雨强度，并且可以模拟真实的 MCS。然而，即使是最先进的 CP 模型仍然在 1-10 公里的“灰色地带”运行，其中内部风暴环流仅部分得到解决。忽视子网格过程的后果仍在调查中，并且需要仔细审查缺陷。通过将地球观测数据与新兴的最先进的 CP 气候模型模拟相结合，我的项目研究了对流规模（连续的云盾、嵌入式对流核心尺度、上升气流大小）影响 MCS 极端降雨量和陆地上的寿命。基于对地观测数据，我的工作将发现大陆对流组织的规模在过去20-30年内是否发生了变化，以及哪些过程是确定这种趋势的关键。这还将探讨 MCS 与陆地特征和大气环境的相互作用是否会随着对流规模的变化而变化。我还将进一步用已确定的过程来挑战 CP 模型，并开发基于过程的模型基准测试方法，测试 CP 模型在捕获未来气候中的降雨强度机制方面的可信度。研究结果将用于试验改进风暴临近预报的方法，并根据多种证据（其中关键包括对流规模）改进对未来 MCS 极端降雨的估计。因此，我的项目将在我们对全球变暖如何驱动对流尺度变化、降雨与尺度如何联系以及尺度信息是否可以改善天气与气候时间尺度的极端降雨预测等方面的理解上带来重大改变。