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Data Assimilation of Weather Radar and LIDAR for Convection Forecasting and Windshear Alerting in Aviation Applications

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Abstract

In this paper, variational data assimilation techniques to retrieve 3-dimensional wind fields from weather radars and LIDAR are discussed. The retrieved wind field from the 3-dimensional variational (3DVAR) technique applied to the weather radar data are found useful to delineate the mesoscale features leading to the convective development in a rainstorm event that brought significant lightning and thunderstorms near the Hong Kong airport and heavy precipitation over the territory. Impacts in improving analysis and forecast of a non-hydrostatic NWP model are also obtained through the data assimilation of wind retrieval data as additional observations in the model analysis. To capture the low-level windshear due to complex wind flow around the Hong Kong airport, 3DVAR and 4DVAR techniques are applied to LIDAR data. The performance of the wind retrieval algorithms and results of case studies will be illustrated. It is found that the wind fields obtained are useful to depict salient features of terrain-induced airflow disturbances at HKIA, such as mountain waves and vortices in a gustnado event.

Keywords

  • Pearl River Estuary
  • Hong Kong
  • Weather Radar
  • Virtual Potential Temperature
  • Gust Front

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-642-35088-7_22
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Correspondence to Wai Kin Wong .

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Wong, W.K., Chan, P.W. (2013). Data Assimilation of Weather Radar and LIDAR for Convection Forecasting and Windshear Alerting in Aviation Applications. In: Park, S., Xu, L. (eds) Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35088-7_22

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