Study On Dealiasing And Retrieval Assimilation Of Doppler Radar Radial Velocity

Numerous studies have shown that the assimilation of Doppler radar data can effectively improve the precipitation forecasting skills of numerical models for severe convective event,but the assimilation of radial velocity often has an unstable effect on model improvement due to various factors,which may lead to problems such as bias in precipitation location and bias in precipitation amount.First,this may be due to some quality problems in the radial wind data(e.g.,velocity ambiguity,etc.)and thus the model assimilates the wrong observations;second,the direct and retrieval assimilation of radial winds are subject to certain errors,thus affecting the assimilation effect;In addition,the effectiveness of the numerical model in absorbing the high temporal resolution observations also greatly affects the ability to generate better initial fields after assimilating the radial velocity,which in turn affects the precipitation forecast level.Aiming at the velocity ambiguity problem of Doppler weather radar in strong convective events such as strong wind,,this paper proposes a Doppler radial velocity dealiasing algorithm based on a numerical model multi-step revised background field,and the method effectively improves the quality of radial wind data.In this method,the model background field is transformed into radial velocity as a reference to carry out the first fuzzy detection and correction,then the background wind field is numerically corrected by using the corrected information,and finally the velocity deblurring in the velocity fuzzy region is realized.The experimental results show that only using the background wind field output by the numerical model as the reference value can not effectively achieve velocity deblurring in the severely blurred region,but the improved method can effectively correct the background wind field,so that the corrected background wind field can produce more mesoscale wind field characteristics more consistent with the actual atmosphere.Using the modified background wind field as the reference field for velocity deblurring,the velocity deblurring method is effective for both primary and secondary blurring of large area.To further investigate the effects of retrieval assimilation and direct radar radial velocity assimilation on model quantitative precipitation forecasts,this paper improves the experimental setup of retrieval,increases the number of retrieval radars and improves the quality of retrieval winds,and increases the frequency of assimilation and verifies the role of inversion wind assimilation in improving short-range precipitation forecasts.A two-step variational method is used to invert the quality-controlled radial winds from multiple radars into a high spatial and temporal resolution three-dimensional horizontal atmospheric wind field,and then the WRF(Weather Research and Forecasting Model)and 3Dvar(WRFDA)assimilation systems are used to compare the retrieval assimilation and direct assimilation of radial velocity on the model dynamical field,the water-matter field,and the adjustment of their effects on short-range precipitation forecasts.The results show that the radial wind retrieval assimilation and the direct assimilation have the same effect on the model dynamical field and the watermatter field,and on the improvement of the short-range precipitation forecast.The results show that the high-frequency assimilated radar reflectivity may cause the model dynamical field and water-matter field to deviate from the actual atmospheric state,and the direct or retrieval assimilation of radial velocity to constrain the dynamical field can improve the model precipitation forecast to a certain extent,while the retrieval assimilation can effectively improve the horizontal wind field and precipitation position of the model forecast.In order to further effectively assimilate higher frequency revieval wind information,the observed Nudging method was used to assimilate radar revieval wind,and the assimilation frequencies of 20 min,10 min and 5 min were compared to improve the model precipitation forecasts.The experimental results show that the high-frequency assimilation of revieval winds using the observation Nudging method improves the quantitative precipitation forecast significantly,and can effectively improve the model's dynamical field and water vapor transport,and the higher the assimilation frequency,the more obvious the improvement on the precipitation forecast.