Land Impacts on Mesoscale Convective Systems

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.