ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Improvement of Densely-Observed Radiosonde and Automatic Weather Station Data Assimilation on Numerical Simulation of Atmospheric Boundary Layer in Beijing Area
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Abstract:
Using the 3 h densely-observed radiosonde and the 1 h automatic weather station data obtained from Baolian, Chaoyang and Daxing stations in Beijing from 28 August to 2 September 2016, based on the WRF model and the WRFDA three-dimensional variational assimilation system, this paper conducts assimi-lation experiments on only assimilating densely-observed radiosonde data (S-DA), only assimilating automatic weather station data (A-DA), and simultaneously assimilating the above two types of data (M-DA), to investigate the improvement effect of the three data assimilation schemes in the numerical simulation of the boundary layer in the Beijing Area. The results show that in the vertical direction, the densely-observed radiosonde data play a core role in improving simulation results, which can reduce the root mean square errors of temperature, relative humidity, and wind speed within the boundary layer range by 65%, 61%, and 22%, respectively. The automatic weather station data also contribute to the simulation results in the vertical direction, but the improvement is small and the impact range is low. The results of the M-DA experiment are similar to those of the S-DA experiment. In the horizontal direction, the improvement effect of the assimilated automatic weather station data is mainly reflected in a wide range of impact. The effect of densely-observed radiosonde data has strong improvement, but the impact range is small. The advantages of combining the two types of data in the M-DA experiment can make the simulation results closer to the observation results. In terms of assimilation timeliness, the assimilation experiment has a relatively long effect on improving the thermal state within the boundary layer, and a relatively short effect on improving the humidity state and dynamic structure. Among them, the M-DA experiment can extend its effect for the thermal state up to 6 h in forecast, and its effect for the humidity and dynamic structure up to 3 h in forecast. In summary, the simultaneous assimilation of densely-observed radiosonde and automatic weather station data is more effective than assimilating one of the data only. The two types of data can complement each other’s shortcomings after assimilation, which can greatly improve the initial field of the model and thus improve the accuracy of boundary layer simulation results to a certain extent.
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