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

当今大气和气候科学中一些最紧迫的问题集中在雷暴如何对大气环境的变化作出反应。极端降雨将如何随着气候变化而变化？内部风暴过程和动力学是如何影响这些变化的？这一挑战在（亚）热带地区最为紧迫。在这些地区，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景气，人口的抵御能力较低。为了估计和规划未来的风暴影响，我们需要了解和模拟风暴动力学将如何响应（并且已经响应）大气变化，以及是否存在内部的动力学机制，可能会加剧极端降雨，而不仅仅是与温暖大气中水分增加有关的纯粹热力学考虑。在大多数受影响地区，MCSs为农作物、牲畜和人类提供了至关重要的供水，贡献了总降雨量的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，这种情况只会恶化。然而，尽管MCSs具有重要的社会意义，我们仍然不知道为什么特别是它们的亚日极端降雨量经常超过预期强度。外部（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）的相对重要性仍然不清楚，这也妨碍了我们估计全球变暖效应的能力。气候模式对驱动因素贡献的评估到目前为止还不存在，因为传统的粗分辨率~100公里的全球气候模式在表示MCS尺度范围内的过程方面存在重大困难，它们既不能明确地解决这个问题，也不能令人满意地参数化，即它们没有“看到”MCS。然而，在过去十年中，在使用高分辨率（<10公里）区域对流允许（CP）模式进行气候预测方面取得了快速进展。与中分辨率模式相比，CP模式无需依赖对流参数化，可以产生更真实的峰值降雨强度，并且可以模拟真实的MCSs。然而，即使是最先进的CP模式仍然在1-10公里的“灰色地带”运行，在那里内部风暴环流只得到部分解决。忽视子电网过程的后果仍在调查中，缺点需要仔细审查。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，我的项目调查了对流的规模（连续的云屏蔽，嵌入的对流核心规模，上升气流大小）如何影响陆地上的MCS极端降雨和寿命。基于地球观测数据，我的工作将发现大陆对流组织的规模是否在过去20-30年内发生了变化，以及确定这种趋势的关键过程是什么。这也将探讨MCS与陆地特征和大气环境的相互作用是否作为对流尺度的函数而变化。我将进一步用已确定的过程挑战CP模型，并开发基于过程的模型基准方法，测试CP模型在捕捉未来气候中的降雨强化机制方面的可信度。这些发现将用于试验改进风暴临近预报的方法，以及改进基于多种证据线的未来MCS极端降雨估计的方法，这些证据线至关重要地包括对流尺度。因此，我的项目将使我们对全球变暖如何驱动对流尺度变化，降雨和尺度如何联系，以及尺度信息是否可以改善天气到气候时间尺度的极端降雨预测的理解发生变化。

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.