Four radar stations and a fleet of drones will track the turbulent inner workings of summer thunderstorms over southern England. The problem is that weather forecast models struggle to predict when these storms will unleash flash floods, large hail, or damaging winds, because the models cannot directly simulate the fine-scale turbulence and rain formation that drive them. Current approximations for these sub-grid processes produce large errors in storm intensity and lifetime, leading to unreliable severe weather warnings. The WOEST project will fill a critical observational gap by using four dual-polarisation Doppler radars to track precipitating cloud cores in real time, coordinating these scans with research aircraft flights, and deploying multiple drones to capture hourly profiles of temperature, humidity and wind in the lowest two kilometres of the atmosphere. An array of cloud cameras will reconstruct the three-dimensional motion of boundary-layer clouds. If successful, this multi-instrument dataset will allow scientists to evaluate and improve the turbulence parametrisations used in both global weather and climate models and high-resolution regional forecasts. The result could be more accurate predictions of hazardous convective storms and their impacts on infrastructure, agriculture and public safety.
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Mid-latitude summertime convection can lead to hazardous weather (flash flooding from extreme rainfall, large hail and damaging winds). However, accurate forecasting of convection is challenging due to the interaction of many processes, especially rain formation and turbulence, which interact over a wide range of scales. Recent studies have shown that model simulation results depend sensitively on the parametrisation schemes used to represent turbulent flow on sub-grid scales. For instance, a model configuration that parameterises the largest turbulent eddies may develop broader and longer-lived convective storms than a model configuration that treats these eddies explicitly. This discrepancy leads to biases in storm number, intensity and lifetime, hence to errors in severe weather warnings and the forecasts of the large-scale circulation. There is a critical lack of observations that capture the short time and length scales of turbulent processes in the atmosphere to help inform the improvement and development of turbulence parametrisation schemes. The Wessex Summertime Convection Experiment (WesCon) is designed to address this deficiency by combining FAAM aircraft measurements with a selection of ground-based remote sensing instruments and radiosondes. This research, WesCon - Observing the Evolving Structures of Turbulence (WOEST), complements WesCon by enabling frequent observations of the same turbulent structures at high resolution. In terms of moist convective turbulence, WOEST will radically advance observations of cloud dynamics by tracking precipitating cores of convective clouds and the turbulent regions embedded within them in real-time using four dual-polarisation Doppler radars. The radar scans will also be coordinated with the FAAM aircraft location to enable coincident observations. In terms of boundary-layer turbulence and variability, their evolution will be captured uniquely by multiple UAS, which will be coordinated to capture hourly profiles of temperature, humidity, and winds to study the small-scale variability in the lowest 2km of the atmosphere. Additionally, an array of cloud cameras will be used to reconstruct the 3D motion and evolution of boundary-layer clouds, to be related to the turbulent and dynamic evolution of the boundary layer as measured by remote sensing instruments such as lidar (to measure cloud bases and humidity profiles) and wind profilers. The observations gathered in WOEST will capture turbulent processes in the atmosphere at a range of fine spatial and temporal scales. Our multi-instrument approach will enable us to evaluate simulations of turbulence and dynamics in convective clouds and how the structure and evolution of the boundary layer influence moist convective turbulence at a range of scales, including at the process-level relating turbulence to the strength and size of updrafts. This will lead to a new understanding of the variability and evolution of the boundary layer in the context of the surrounding cloud field and the variability of turbulence and cloud dynamics. Such insights should lead to significant improvements within the sub-grid turbulence parametrisations that allow both km-scale global weather and climate simulations and sub-km-scale regional weather forecasts to more accurately predict the evolution and intensity of hazardous convective storms.
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