Research On The Impact Of Ground-based Vertical Observation Network Data On Numerical Forecasting

A large number of observations assimilated can effectively improve the results of model forecast.However,there are significant differences in the effects of different observations on the forecast.It is one of the most challenging diagnostics in numerical models to reasonably evaluate the contribution of observations to the forecast.In order to deeply understand the quality of observation data and its impact on numerical weather prediction,the quality of wind profile radar(WPRD)observation obtained by Mega City Project in Beijing in 2019 was evaluated.Based on the WPRD and ground-based microwave radiometer(MWR)data in September 2019,the experiments of the impact of observations on the 12h forecast of WRF model are carried out by using the adjoint-based forecast sensitivity to observation(FSO)method,then the contribution of wind,temperature and humidity observations to the 12h forecast was analyzed,and the observation system experiments(OSEs)were carried out to verify the results.The results show that:(1)The quality of WPRD observation in Beijing area in 2019 is good,the root mean square error of observation is about 2?4 m/s.And the quality of observation at 00 UTC is better than that of observation at 12 UTC,while the quality of observation on cloudy and rainy days is better than that of observation on sunny days.(2)The results of the evaluation study of FSO linear approximation accuracy show that the FSO linear approximation is better when the model grid with high level horizontal resolution and the background field and analysis field with significant increment are used as the initial field in the limited model area.(3)In general,the observations(MWR,WPRD,Sound,Synop and Geoamv)assimilated all play a positive role in reducing the 12h forecast error of WRF model.Among them,MWR observation has the greatest impact on the forecast,the improvement of wind field observation of WPRD on forecast is better than that of wind field observation of Sound,which are basically consistent with the results of OSEs.(4)Among the network observation stations in Beijing,the WPRD observation and the MWR observation of Daxing station have better improvement on the forecast.Among the U and V observation of WPRD and temperature and specific humidity observation of MWR,the positive contribution value of V observation and temperature observation to the forecast is higher,and the effect of improving the forecast is better.(5)The observation of WPRD and MWR at most levels are positive contribution to forecast,and the positive contribution of temperature observation is mainly below 800 hPa near the ground.This may be due to the observation error of temperature below 800 hPa is smaller,and the forecast is more sensitive to low-level temperature observation,so the positive contribution of temperature observation to forecast is the most significant below 800 hPa.