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Assessing the influence of assimilating radar-observed radial winds on the simulation of a tropical cyclone
Authors:Yu-Kun Qian  Shiqiu Peng  Shun Liu  Shumin Chen  Ziqian Wang  Qilin Wan  Zitong Chen
Affiliation:1.State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology,Chinese Academy of Sciences,Guangzhou,China;2.University of Chinese Academy of Sciences,Beijing,China;3.Guangxi Key Laboratory of Marine Disaster in the Beibu Gulf,Qinzhou University,Qinzhou,China;4.SAIC/National Centers of Environmental Prediction,Camp Springs,USA;5.Department of Atmospheric Sciences/Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies,Sun Yat-sen University,Guangzhou,China;6.Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction/Guangzhou Institute of Tropical and Marine Meteorology,China Meteorological Administration,Guangzhou,China
Abstract:Observations by Doppler weather radar are crucial for nowcasting and short-time forecasting of severe weather events as they bring in refined information of the atmosphere. However, due to the inevitable noises and non-meteorological signals, they cannot be assimilated straightforwardly into a numerical model. In the present study, assimilation of the radial component of wind velocity observed by two Doppler radars is performed in the numerical simulation of Supertyphoon Rammasun (2014) just before its landfall. After several quality-control steps, the radar-observed radial velocities are de-aliased, noise-reduced and assimilated into the model to improve initial conditions for the high-resolution simulation. Results show that only when using global background error covariance matrix can the observational increment be properly assimilated into the model, correcting large-scale background steering flow and yielding a simulated track close to the observed one. However, little improvement is found in simulating the TC core-scale structures by the assimilation of radar velocity as compared to the radar-observed flow, primarily due to the insufficient spatial resolution of the model that may lead to the incorrect representation of the TC core structure and the rejection of some core-region observations during the data assimilation procedure. Moreover, assimilation-induced asymmetries consume a certain portion of mean kinetic energy, preventing the simulated Rammasun from axisymmetrization and thus intensification as compared with the non-assimilated experiment.
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