Study Uses Numerical Model with Explicitly Incorporated Aerosols to Simulate Severe Convective Storm
The representation of aerosols in numerical weather prediction models is often overlooked despite the crucial role they play in all stages of cloud lifecycle.
To analyze this role and contribute to a deeper understanding of cloud physics and microclimate, Mladjen Ćurić from the University of Belgrade, Serbia and a collaborator of Prof. Linda Zou, a first cycle awardee of UAE Research Program for Rain Enhancement Science (UAEREP) and professor at the Khalifa University, worked on a project that investigated the differences between an explicit and implicit treatment of aerosols in the Weather Research and Forecasting (WRF) – Advanced Research WRF (WRF-ARW) model.
The study investigated a severe mesoscale convective system with supercells that struck west and central parts of Serbia on July 21, 2014. This geographical region is extremely prone to severe thunderstorms and identified as the second most favorable area in Europe for development of significant thunderstorms.
The Aerosols Explicitly (WRF-AE) model accurately captured the transportation of dust from North Africa over the Mediterranean and to the Balkan region. On smaller scales, both WRF-AE and Aerosols Implicitly (WRF-AI) models displaced the locations of clouds situated above west and central Serbia towards the southeast and under-predicted the maximum values of composite radar reflectivity.
The differences between the modelled results were further compared against satellite imagery, Doppler radar measurements and surface observations.
The study found that convective clouds in the WRF-AE case are wider and more spread out than in the aerosols implicitly case where individuality of convective cells is evident.
Both models under-predicted the composite radar reflectivity and over-predicted surface precipitation, but in two different manners.
The WRF-AE results demonstrated the necessity of simultaneous presence of aerosols and strong convection for developments of deep clouds with heavy precipitation and hail.
While the study revealed a few advantages of explicit modelling of aerosols in numerical weather prediction models, the results also show that this method, although being more physically realistic, does not necessarily provide more accurate results in all instances.
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