COntinental COnvective OrganisatioN and rainfall intensification in a warming world: Improving storm predictions from hours to decades (COCOON)
Lead Research Organisation:
UK CENTRE FOR ECOLOGY & HYDROLOGY
Department Name: Hydro-climate Risks
Abstract
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.
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.
