Articles | Volume 23, issue 2
https://doi.org/10.5194/nhess-23-847-2023
https://doi.org/10.5194/nhess-23-847-2023
Research article
 | 
27 Feb 2023
Research article |  | 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

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Aksoy, A., Dowell, D. C., and Snyder, C.: A multicase comparative assessment of the ensemble Kalman filter for assimilation of radar observations. Part I: Storm-scale analyses, Mon. Weather Rev., 137, 1805–1824, 2009. a
Anderson, J., Hoar, T., Raeder, K., Liu, H., Collins, N., Torn, R., and Avellano, A.: The data assimilation research testbed: A community facility, B. Am. Meteorol. Soc., 90, 1283–1296, 2009. a, b
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Anderson, J. L. and Collins, N.: Scalable implementations of ensemble filter algorithms for data assimilation, J. Atmos. Ocean. Tech., 24, 1452–1463, 2007. a, b
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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.
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