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• W4308239187 abstract "Abstract Radar data assimilation is an important method to improve the performance of numerical models in severe convective weather. In this study, the statistical relationships between the radar reflectivity intensity and the latent heat release intensity and humidity are calculated based on Weather Research and Forecasting (WRF) model forecast results. Then, they are used to convert the radar reflectivity observation data into the virtual observation of the temperature and humidity. Finally, these data are continuously assimilated to the initial field of the WRF model using the ensemble Kalman filter to simulate a warm-sector squall line process. The results show that the temperature and humidity in the strong radar echo area are adjusted after the radar reflectivity data are assimilated, and new convective echoes can be excited quickly in a short time. The indirect assimilation of the radar reflectivity data can effectively improve the forecast skills of both the warm-sector squall line and the influence time of the squall line. After the assimilation, the forecast results of the influence time of the squall line on the downstream regions are basically consistent with the observations. At the same time, the forecast skills of the squall line intensity and the surface gust intensity are improved. The forecast results of the experiments with different influence radii are all better than those without radar reflectivity assimilation. When the influence radius is smaller, the improvement lasts longer. When the influence radius is larger, the improvement is more significant in the now-casting period with a shorter duration. The simulation skill of this squall line is high with an influence radius of 25 km. In addition, the assimilation of the virtual observation of both the temperature and humidity can improve the forecast skill of the squall line, especially the virtual observation with the assimilation of the humidity." @default.
• W4308239187 created "2022-11-09" @default.
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• W4308239187 date "2022-11-05" @default.
• W4308239187 modified "2023-09-26" @default.
• W4308239187 title "Influence of the indirect assimilation of radar reflectivity data using the ensemble Kalman filter on the simulation of a warm-sector squall line" @default.
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• W4308239187 doi "https://doi.org/10.1007/s00703-022-00934-1" @default.
• W4308239187 hasPublicationYear "2022" @default.
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