One of main benefits of a dual polarization radar is improvement of quantitative rainfall estimation. In this paper, performance of two representative rainfall estimation methods for a dual polarization radar, JPOLE and CSU algorithms, have been compared by using data from a MOLIT S-band dual polarization radar. In addition, this paper presents evaluation of specific differential phase (Kdp) retrieval algorithm proposed by Lim et al. (2013). Current Kdp retrieval methods are based on range filtering technique or regression analysis. However, these methods can result in underestimating peak Kdp or negative values in convective regions, and fluctuated Kdp in low rain rate regions. To resolve these problems, this study applied the Kdp distribution method suggested by Lim et al. (2013) and evaluated by adopting new Kdp to JPOLE and CSU algorithms. Data were obtained from the Mt. Biseul radar of MOLIT for two rainfall events in 2012. Results of evaluation showed improvement of the peak Kdp and did not show fluctuation and negative Kdp values. Also, in heavy rain (daily rainfall > 80 mm), accumulated daily rainfall using new Kdp was closer to AWS observation data than that using legacy Kdp, but in light rain(daily rainfall < 80 mm), improvement was insignificant, because Kdp is used mostly in case of heavy rain rate of quantitative rainfall estimation algorithm.