## 5 Conclusions  
An improved velocity dealiasing named algorithm ADDA was presented and evaluated in this paper, which was then further prepared with the aim of future applications for radar data assimilation. The skill of the ADDA algorithm was examined for seven severe convective cases, including hurricanes, typhoons and continental convective cases observed by either S-band or C-band radars from three different operational networks, with a total of 849 volumes and 7463 tilts of data. The selected cases were all seriously aliased for a large percentage of the tilts, and some tilts contained challenging situations with multiple-aliased radial velocity gates due to strong wind speeds or small radar Nyquist co-intervals. The new ADDA included five modules, which were devised to remove noise, to select the properly first reference radial, to preserve the real convective shear regions, to determine and revise the aliased velocities with a two-direction multiple-pass method and to redress the wrong dealiasing results with local error checks. The choice of the first reference radial close to the zero line guarantees that the ADDA scheme begins with the velocity gates that are less likely to be aliased. The G-VAD scheme, with the information of the radial velocity gradient in the second module, was illustrated to help enhance the accurateness of first reference radial selections in typhoon and hurricane cases, where twice-folded situations occur quite regularly. It was also shown that module 3, in which a three-step scheme to discriminate between the real weather shear and the aliased shear was applied, was effective for keeping the vigorous convective regions intact and preventing erroneous dealiasing. The two-way multiple-pass dealiasing scheme employed in module 4 enhanced the dealiasing accuracy, especially when aliased gates appeared close to large regions of missing observed gates. Furthermore, we found that the linear least-square error checks along the radar's radial direction and quadratic least-square error check along radar azimuthal direction added in the last module removed the remaining dealiasing errors in the typhoon and hurricane cases. The statistical dealiasing results of the ADDA scheme, with metrics including pod, far, and csi, illustrated that the improved ADDA scheme performs better than the CIDA scheme for seven cases, with the most obvious advancements for the Haikou Typhoon Rammasun case and the Taiwan Typhoon Fanapi case, and for the squall line case observed by the CINRAD Guangxi S-band radar. The advanced dealiasing resulted from the more accurate selection of the first reference radial and the ability of the scheme to preserve the physical shear associated with vigorous convection. The success rate of ADDA for S-band radar stations was above 96% in terms of POD. The skill of ADDA for the CINRAD C-band radar was lower but reasonably good, given the challenges associated with these C-band radar systems. ADDA is currently being implemented for the data assimilation systems of the variational Doppler data analysis system (VDRAS) and the weather research and forecasting data assimilation system (WRFDA), as radar quality control software systems. Both systems have operational capabilities, so ADDA can be operationally running. ADDA can be run automatically, with human interaction required only when a hurricane approaches the radar, in which case the G-VAD in module 2 and the linear and quadratic local fits need to be turned on. To make ADDA fully automated, a hurricane detection algorithm is needed, which will be one of our future projects. All authors made great contributions to this article. Conceptualization, G.H. and J.S. ; methodology, G.H. and L.Z. ; software, Z.Y. and L.Z. ; validation, G.H., J.S. and Z.Y. ; formal analysis, J.S. ; writing--original draft preparation, G.H. and J.S. ; writing--review and editing, G.H. and J.S.