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<p>A 3-hourly radiosonde observation campaign was conducted around central Beijing from August 28 to September 2, 2016, capturing high-resolution meteorological data from urban and rural sites. This study investigates the impact of cyclic assimilation of radiosonde data using an analysis increment downscaling method on urban boundary layer forecasts and urban heat island (UHI) simulations. Results show that after three assimilation cycles, the root mean square errors (RMSE) for 2&#xa0;m temperature, 2&#xa0;m relative humidity, and 10&#xa0;m wind speed within the Beijing 6th Ring Road decreased by 54.09%, 4.93%, and 27.54% respectively, with significant reductions in temperature and humidity profile biases. The improved initial fields better reflected the three-dimensional distribution of meteorological variables, reducing boundary layer forecast biases. Forecast improvements lasted for 18–21&#xa0;h, enhancing inversion layer structure prediction and transitions to unstable stratification. After assimilation, RMSE decreased by18.27%, 17.49%, and 11.11% for 2&#xa0;m temperature, 2&#xa0;m relative humidity, and 10&#xa0;m wind speed during UHI event. The assimilation of 3-hourly radiosonde data was found to improve forecasts of the urban heat island’s horizontal distribution, intensity, and associated vertical circulation. Notably, the assimilation experiment captured urban-mountain interactions and UHI circulations under weak wind and stable conditions. This study indicates that the assimilation of 3-hourly radiosonde data holds significant potential and application value in improving urban boundary layer meteorological forecasts and UHI simulations.</p>

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Impact of 3-hourly radiosonde data assimilation on the simulation of urban boundary layer in Beijing

  • 期刊论文

  • 发表日期：

    2025年9月5日

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  • Linbin He,
  • Yizhou Zhang,
  • Xiang-Yu Huang,
  • Shiguang Miao,
  • Xinyu Zhang,
  • Chenggang Wang

摘要

A 3-hourly radiosonde observation campaign was conducted around central Beijing from August 28 to September 2, 2016, capturing high-resolution meteorological data from urban and rural sites. This study investigates the impact of cyclic assimilation of radiosonde data using an analysis increment downscaling method on urban boundary layer forecasts and urban heat island (UHI) simulations. Results show that after three assimilation cycles, the root mean square errors (RMSE) for 2 m temperature, 2 m relative humidity, and 10 m wind speed within the Beijing 6th Ring Road decreased by 54.09%, 4.93%, and 27.54% respectively, with significant reductions in temperature and humidity profile biases. The improved initial fields better reflected the three-dimensional distribution of meteorological variables, reducing boundary layer forecast biases. Forecast improvements lasted for 18–21 h, enhancing inversion layer structure prediction and transitions to unstable stratification. After assimilation, RMSE decreased by18.27%, 17.49%, and 11.11% for 2 m temperature, 2 m relative humidity, and 10 m wind speed during UHI event. The assimilation of 3-hourly radiosonde data was found to improve forecasts of the urban heat island’s horizontal distribution, intensity, and associated vertical circulation. Notably, the assimilation experiment captured urban-mountain interactions and UHI circulations under weak wind and stable conditions. This study indicates that the assimilation of 3-hourly radiosonde data holds significant potential and application value in improving urban boundary layer meteorological forecasts and UHI simulations.