Land Impacts on Mesoscale Convective Systems

中尺度对流系统（MCSs）是世界上最强大的风暴之一，在许多地方是大风、闪电、山洪暴发和龙卷风等灾害的主要原因。在整个热带地区，mcs占极端降雨天数的80%。它们是由雷暴组织成一个数百公里宽的大型综合体造成的，这些雷暴在陆地上移动数小时，有时甚至数天，沿途造成异常的暴雨。它们在某些“热点”地区尤其普遍，包括阿根廷北部和印度、西非和中非以及美国大平原，在这些地区，温暖潮湿的空气和有利的风共同支持着它们的发展。在这些热点地区，迫切需要了解mcs将如何随着世界变暖而变化，以便建造适应气候变化的房屋、道路、桥梁和水坝。传统的气候模式缺乏足够的空间分辨率来真实地模拟这些风暴。然而，在过去的5年里，由于计算机能力的提高，高分辨率气候模型发生了一场革命。新的“对流允许模型”（cpm）可以代表mcs，并开始提供改进的预测和更好地理解mcs如何响应其环境。我们知道植被和土壤湿度的空间格局会影响气温、湿度和风的流动，而这些变化会影响强大的MCS在哪里（或者是否）发展。例如，热带森林和沙漠之间的差异控制了整个大陆的表面温度差异，通过有利的风条件创造了MCS热点地区。由于全球变暖，这些地表温差已经在增加，而且在短短35年里，西非最强烈的mcs增加了两倍，导致那里的山洪暴发急剧增加。我们也知道陆地表面会影响单个MCS轨迹。同样来自西非的证据表明，mcs被引导远离由以前的风暴造成的饱和土壤。这种反馈使得预测危险风暴的路径更加容易，尽管我们不知道这种影响在世界其他地区有多强。该项目将通过对卫星观测和cpm的分析，重点研究mcs如何受到土壤湿度和植被模式的影响。这项工作将发现陆地效应在世界不同热点地区有多强，以及决定这种强度的关键过程是什么。CPM实验将确定对mcs影响最大的地表斑块大小，范围从10到100公里。将对卫星数据进行分析，以发现最近土地利用变化（如灌溉、森林砍伐、城市化）的地区对MCS强度和寿命的影响。这项工作将探索，随着世界变暖，干湿地区之间的对比越来越强，土壤水分斑块和MCSs之间的反馈是如何变化的。这很重要，因为反馈可能会放大更极端降雨和更长的风暴间隔的趋势。确定的基于观测的土地和mcs之间的关系也将用于审查理论认识和评估快速出现的下一代cpm。这将包括对世界上第一个为期一年的陆地-大气-海洋CPM全球模拟的分析，该模拟能够捕捉mcs内公里尺度的运动。总的来说，该项目将通过来自世界各地的观测和模型研究，在了解陆地如何影响这种强风暴方面取得实质性进展。研究结果将为改进风暴灾害预测提供基础知识，为跨天气到气候变化时间尺度的决策提供信息。

Mesoscale Convective Systems (MCSs) are among the most powerful storms in the world, and in many places are the dominant cause of hazards such as high winds, lightning, flash flooding and tornadoes. Across the tropics, MCSs account for 80% of extreme rainfall days. They result from thunderstorms that organize into a single large complex hundreds of km wide, which travel across the land for hours, in some cases days, causing extraordinary downpours along their path. They are particularly prevalent in certain "hotspot" regions including Northern Argentina and India, West and Central Africa, and the US Great Plains, where a combination of warm, moist air and favourable winds support their development. In these hotspot regions, an understanding of how MCSs will change as the world warms is urgently needed in order to build climate-resilient homes, roads, bridges and dams. Conventional climate models lack sufficient spatial resolution to realistically simulate these storms. There has however been a revolution in high-resolution climate models over the past 5 years, enabled by increasing computer power. New "Convection Permitting Models" (CPMs) can represent MCSs and are starting to deliver improved predictions and better understanding of how MCSs respond to their environment.We know that spatial patterns in vegetation and soil humidity affect air temperature, moisture and wind flows, and that these changes can affect where (or indeed whether) a powerful MCS develops. For example, contrasts between tropical forests and deserts control surface temperature differences across the continents, creating MCS hotspot regions through favourable wind conditions. Those surface temperature differences are already increasing due to global warming, and have been implicated in a tripling of the most intense West African MCSs over just 35 years, contributing to a dramatic rise in flash flooding there. We also know that the land surface affects individual MCS tracks. Evidence, again from West Africa, shows that MCSs are steered away from the saturated soils created by previous storms. This feedback makes predicting the track of a hazardous storm easier, though we do not know how strong the effect is in other regions of the world.This project will focus on how MCSs are affected by patterns of soil moisture and vegetation, through analysis of both satellite observations and CPMs. The work will discover how strong land effects are across the different hotspots of the world, and what processes are key to determining that strength. Experiments with a CPM will identify the surface patch sizes, ranging from 10s to many 100s km, which have the biggest impact on MCSs. Satellite data will be analysed to detect how MCS intensity and lifetime have been affected in regions with recent land use change (e.g. irrigation, deforestation, urbanisation). The work will explore how, as the world warms, and contrasts between wet and dry areas get stronger, the feedback between soil moisture patchiness and MCSs is changing. This matters because the feedback may amplify trends towards more extreme rain and longer gaps between storms. Identified observation-based relationships between the land and MCSs will also be used to scrutinise theoretical understanding and to evaluate the fast-emerging next generation of CPMs. This will include analysis of the world's first year-long global simulation from a land-atmosphere-ocean CPM able to capture the kilometre-scale motions within MCSs.Overall, the project will make substantial advances in understanding of how the land affects this powerful type of storm, with observations and model studies from across the world. The results will provide underpinning knowledge to improve prediction of storm hazards, informing decision making across weather to climate change time-scales.