Simulation of a severe convective storm using a numerical model with explicitly incorporated aerosols
Autor: | Mladjen Ćurić, Djordje Romanic, Miloš Lompar |
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Rok vydání: | 2017 |
Předmět: |
Atmospheric Science
Mesoscale convective system 010504 meteorology & atmospheric sciences Severe weather Meteorology Microphysics 0208 environmental biotechnology Weather forecasting 02 engineering and technology computer.software_genre 01 natural sciences 020801 environmental engineering 13. Climate action Weather Research and Forecasting Model Climatology Convective storm detection Weather modification Environmental science Precipitation computer 0105 earth and related environmental sciences |
Zdroj: | Atmospheric Research. 194:164-177 |
ISSN: | 0169-8095 |
Popis: | Despite an important role the aerosols play in all stages of cloud lifecycle, their representation in numerical weather prediction models is often rather crude. This paper investigates the effects the explicit versus implicit inclusion of aerosols in a microphysics parameterization scheme in Weather Research and Forecasting (WRF) – Advanced Research WRF (WRF-ARW) model has on cloud dynamics and microphysics. The testbed selected for this study is a severe mesoscale convective system with supercells that struck west and central parts of Serbia in the afternoon of July 21, 2014. Numerical products of two model runs, i.e. one with aerosols explicitly (WRF-AE) included and another with aerosols implicitly (WRF-AI) assumed, are compared against precipitation measurements from surface network of rain gauges, as well as against radar and satellite observations. The WRF-AE model accurately captured the transportation of dust from the north Africa over the Mediterranean and to the Balkan region. On smaller scales, both models displaced the locations of clouds situated above west and central Serbia towards southeast and under-predicted the maximum values of composite radar reflectivity. Similar to satellite images, WRF-AE shows the mesoscale convective system as a merged cluster of cumulonimbus clouds. Both models over-predicted the precipitation amounts; WRF-AE over-predictions are particularly pronounced in the zones of light rain, while WRF-AI gave larger outliers. Unlike WRF-AI, the WRF-AE approach enables the modelling of time evolution and influx of aerosols into the cloud which could be of practical importance in weather forecasting and weather modification. Several likely causes for discrepancies between models and observations are discussed and prospects for further research in this field are outlined. |
Databáze: | OpenAIRE |
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