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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/nhess-2020-146
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-146
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  06 Jul 2020

06 Jul 2020

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This preprint is currently under review for the journal NHESS.

Typhoon rainstorm simulation with radar data assimilation in southeast coast of China

Jiyang Tian1,2, Ronghua Liu1,2, Liuqian Ding1, Liang Guo1,2, and Bingyu Zhang1,2 Jiyang Tian et al.
  • 1China Institute of Water Resources and Hydropower Research, Beijing, 100038, China
  • 2Research Center on Flood & Drought Disaster Reduction of the Ministry of Water Resources, Beijing, 100038, China

Abstract. As an effective technique to improve the rainfall forecast, data assimilation plays an important role in meteorology and hydrology. The aim of this study is to explore the reasonable use of Doppler radar data assimilation to correct the initial and lateral boundary conditions of the Numerical Weather Prediction (NWP) systems. The Weather Research and Forecasting (WRF) model is applied to simulate three typhoon storm events in southeast coast of China. Radar data from Changle Doppler radar station are assimilated with three-dimensional variational data assimilation (3-DVar) model. Nine assimilation modes are designed by three kinds of radar data (radar reflectivity, radial velocity, radar reflectivity and radial velocity) and three assimilation time intervals (1 h, 3 h and 6 h). The rainfall simulations in a medium-scale catchment, Meixi, are evaluated by three indices including relative error (RE), critical success index (CSI) and root mean square error (RMSE). Assimilating radial velocity with time interval of 1 h can significantly improve the rainfall simulations and outperforms the other modes for all the three storm events. Shortening the assimilation time interval can improve the rainfall simulations in most cases, while assimilating radar reflectivity always leads to worse simulation as the time interval shortens. The rainfall simulation can be improved by data assimilation as a whole, especially for the heavy rainfall with strong convection. The findings provide references for improving the typhoon rainfall forecasts in catchment scale and have great significance on typhoon rainstorm warning.

Jiyang Tian et al.

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Jiyang Tian et al.

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Latest update: 23 Oct 2020
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Short summary
Typhoon always comes along with heavy rainfall, which lead to great loss. The aim of this study is to explore reasonable use of Doppler radar data assimilation to correct the initial and lateral boundary conditions of the Numerical Weather Prediction (NWP) systems for typhoon rainstorms forecast at catchment scale. The results shows that assimilating radial velocity with time interval of 1 h can significantly improve the rainfall simulations and outperforms the other assimilation modes.
Typhoon always comes along with heavy rainfall, which lead to great loss. The aim of this study...
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