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- W2806963003 abstract "Abstract. Stratosphere-to-troposphere transport (STT) is an important natural source of tropospheric ozone, which can occasionally influence ground-level ozone concentrations relevant for air quality. Here, we analyse and evaluate the Copernicus Atmosphere Monitoring Service (CAMS) global and regional forecast systems during a deep STT event over Europe for the time period from 4 to 9 January 2017. The predominant synoptic condition is described by a deep upper level trough over eastern and central Europe, favouring the formation of tropopause folding events along the jet stream axis and therefore the intrusion of stratospheric ozone into the troposphere. Both global and regional CAMS forecast products reproduce the “hook-shaped” streamer of ozone-rich and dry air in the middle troposphere depicted from the observed satellite images of water vapour. The CAMS global model successfully reproduces the folding of the tropopause at various European sites, such as Trapani (Italy), where a deep folding down to 550 hPa is seen. The stratospheric ozone intrusions into the troposphere observed by WOUDC ozonesonde and IAGOS aircraft measurements are satisfactorily forecasted up to 3 days in advance by the CAMS global model in terms of both temporal and vertical features of ozone. The fractional gross error (FGE) of CAMS ozone day 1 forecast between 300 and 500 hPa is 0.13 over Prague, while over Frankfurt it is 0.04 and 0.19, highlighting the contribution of data assimilation, which in most cases improves the model performance. Finally, the meteorological and chemical forcing of CAMS global forecast system in the CAMS regional forecast systems is found to be beneficial for predicting the enhanced ozone concentrations in the middle troposphere during a deep STT event." @default.
- W2806963003 created "2018-06-13" @default.
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- W2806963003 date "2018-10-29" @default.
- W2806963003 modified "2023-09-30" @default.
- W2806963003 title "A deep stratosphere-to-troposphere ozone transport event over Europe simulated in CAMS global and regional forecast systems: analysis and evaluation" @default.
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