Articles | Volume 23, issue 2
https://doi.org/10.5194/nhess-23-847-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/nhess-23-847-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Feb 2023
Research article |
| 27 Feb 2023
| 27 Feb 2023
Improving the predictability of the Qendresa Medicane by the assimilation of conventional and atmospheric motion vector observations. Storm-scale analysis and short-range forecast
Diego S. Carrió
CORRESPONDING AUTHOR
School of Geography, Earth and Atmospheric Sciences, The University of Melbourne, Parkville, VIC, Australia
ARC Centre of Excellence for Climate Extremes, Melbourne, VIC, Australia
Meteorology Group, Department of Physics, Universitat de les Illes Balears, Palma, Spain
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Cyclone Ianos of September 2020 was a high-impact but poorly predicted medicane (Mediterranean hurricane). A community effort of numerical modelling provides robust results to improve prediction. It is found that the representation of local thunderstorms controlled the interaction of Ianos with a jet stream at larger scales and its subsequent evolution. The results help us understand the peculiar dynamics of medicanes and provide guidance for the next generation of weather and climate models.
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Short summary
Short summary
The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
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Short summary
The accurate prediction of medicanes still remains a key challenge in the scientific community because of their poor predictability. In this study we assimilate different observations to improve the trajectory and intensity forecasts of the Qendresa Medicane. Results show the importance of using data assimilation techniques to improve the estimate of the atmospheric flow in the upper-level atmosphere, which has been shown to be key to improve the prediction of Qendresa.
The accurate prediction of medicanes still remains a key challenge in the scientific community...
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