Influence Of Encrypted Sounding Data Assimilation On Numerical Simulation Of Boundary Layer In Beijing Area

The atmospheric boundary layer is an important channel for atmospheric heat,momentum,and various materials to transport up and down.The processes of strong convective weather and pollutant transmission that occur in the boundary layer greatly affect human life and attract more and more scholars' attention.However,because the atmospheric boundary layer has the characteristics of small spatial scale,rapid time change,and sensitivity to the underlying surface,the current numerical simulation results are not satisfactory.Data assimilation is an important way to improve numerical simulation results.This paper uses the3 h intensive radiosonde data that were simultaneously conducted at the three stations of Baolian,Chaoyang and Daxing in Beijing from 08:00 on August 28 th to 08:00 on September2 nd 2016,using WRF and its three-dimensional variational assimilation system,a numerical simulation experiment was carried out on the atmospheric boundary layer in the Beijing area to study the impact of the assimilation of intensive radiosonde data on the numerical simulation of the boundary layer in the Beijing area.The results turn out:? The background field error covariance matrix of the WRF-3DVAR system is not suitable for high-resolution simulation objects.The simulation of the atmospheric boundary layer requires high spatial resolution,and Beijing's topography is undulating and the underlying surface is complex.Only the reconstructed background field error covariance matrix suitable for the simulation area can accurately and reasonably reflect the multivariate relationship.The interaction relationship between the two to further improve the simulation results.The atmospheric boundary layer simulation requires high spatial resolution,and Beijing's topography is undulating and the underlying surface is complex.Only the reconstructed background field error covariance matrix suitable for the simulation area can accurately and reasonably reflect the interaction relationship of multivariate to further improve the simulation results.?In a single assimilation simulation test,the analysis field formed by assimilation is closer to the observation result than the background field,and can better show the thermal,humidity and dynamic characteristics of the real atmosphere in the boundary layer.Respectively compared with the background field,the root mean square error of analysis field of potential temperature,specific humidity,zonal wind,meridional wind and wind speed is reduced by 86%,59%,24%,44%,19%,which reflects the strong correction effect of assimilation.The prediction effect of the assimilation of the dense sounding data is the best within 6 hours of model integration,after which the size and scope of the assimilation gradually weaken.The relatively small number of stations for intensive radiosonde data in the spatial horizontal direction is one of the reasons that the assimilation has a significant improvement effect in the analysis field,but the effect is difficult to last for a long time.?In the cyclic assimilation simulation test,the simulation results of the assimilation test are closer to observations,and the thermal and humidity conditions of the atmosphere in the boundary layer have been greatly improved,and the dynamic characteristics have been improved less.It can effectively simulate the urban heat island circulation structure and the low-level jet stream in the suburban boundary layer.The assimilation test has significantly improved the meteorological elements in the boundary layer,with specific humidity being the most important,followed by potential temperature.The root mean square errors of the two have been reduced by 46% and 27%.Because of the terrain of Beijing is complex,the improvement of wind is small,and the reduction of the root mean square error is within 10%,and the assimilation effect is difficult to maintain for a long time.However,it has made progress for the complex terrain near-surface wind that is difficult to simulate accurately.The cyclic assimilation of intensive radiosonde data can adjust the low-level dynamic characteristics of the model and the necessity of simulating near-surface winds.