###### Abstract
This algorithm was implemented in the variational doppler radar analysis system (VDRAS) [10] and was shown to improve the success rate of dealiasing by 2.6% in an experiment using reference winds without radar data assimilation. However, our recent experiences with the algorithm showed that, in cases of strong horizontal shear, the algorithm could have the serious issue of spreading the dealiasing errors over time due to the continuous cycling of interactive data assimilation and the dealiasing procedure. In addition, the online dealiasing algorithm must wait for a data assimilation cycle to finish before the dealiasing of the radar radial velocity to be used for the next cycle can commence. In comparison, an offline algorithm solely based on the continuity of the radial velocity observations has the advantage of faster computations and does not have the issue of error spreading over time. [PERSON] and [PERSON] [7] first developed a one-dimensional continuity check algorithm to dealias the aliased radial velocities in each separate radial using only radial observation information. Some two-dimensional continuity check algorithms [11; 12; 13; 14; 15; 16; 17; 18; 19] which check both the radial and azimuthal directions were exploited following [PERSON] and [PERSON] [7]. Based on the two-dimensional dealiasing scheme, [PERSON] and [PERSON] [20] evolved a four-dimensional dealiasing scheme by including observations in different elevation scans and different volume scans. In recent years, Doppler radar networks have been implemented in many developing countries. These radar networks often have unique quality control challenges due to excessive noise contaminations, and hence, traditional dealiasing algorithms may not work as well as expected. [PERSON] et al. [17] (HE2012 hereafter) developed an improved two-dimensional continuity check for the dealiasing algorithm for S-band China radar network (CINRAD) observations, named the CINRAD improved dealiasing algorithm (CIDA). An original characteristic of CIDA was the utilization of a new scheme to choose a first reference radial near zero-line observation where the radar radial velocity gates are almost impossibly aliased. Furthermore, CIDA replaced the use of wind profile products and radiosonde observations with a multi-pass dealiasing process, which improved the dealiasing result of isolated aliased echoes and missing data. [PERSON] et al. (2019) (HE2019 hereafter) introduced the dealiasing algorithm ADTH (Automated Dealiasing for Typhoon and Hurricane), which was developed based on the CIDA algorithm for dealiasing typhoon and hurricane systems. The ADTH algorithm tested 789 volumes and 7981 radial velocity elevation fields, all observed from S-band radars stations in two hurricane and four typhoon cases. These six cases had radial velocities that were severely aliased for a large percentage of the constant-elevation scans, and some included challenging dealiasing situations with multiple aliased radial velocities due to strong wind speeds. Examinations of the CIDA algorithm with 14 cases of squall line, typhoon, and heavy rain observations from the CINRAD network displayed an advanced performance compared to the NEXRAD (Next Generation Weather Radar) algorithm for the U.S. radar network. Even though HE2012 has made important contributions towards our objective of developing a robust and fully automated radial velocity dealiasing algorithm that can be applied for operational data assimilation, the problem of whether the algorithm is familiarly suitable for radar observations from different operational networks still exists. Additionally, HE2012 tested CIDA only on CINRAD S-band radar systems and used only one chosen volume observation for each weather case, with a total of 14 cases. The ADTH employed algorithm in HE2019 has proved the good performance of dealiasing more than 12 h of continuous observation for hurricanes and typhoons.