This manuscript proposes an approach to handle the non-Gaussian error distribution of reflectivity OmBs (dBZ), which adopts the idea of the symmetric error model in all-sky radiance data assimilation. This work demonstrates that the symmetric error model built by the rainrate predictor, can improve the Gaussianity of OmB distribution, by using six-month composite reflectivity data and simulated products. Moreover, the reflectivity OmBs present a more complicated error model that can be fitted by a three-piecewise function, compared to the satellite radiances, since the radar reflectivity is often discontinues. This manuscript is well structured and could be a valuable contribution to the radar and data assimilation communities. I have several comments as below. I’d like to recommend minor revision to this manuscript.

1. This work compares two OmB data, the maximum composite and the reflectivity at 1 km. Results show that two OmB data have similar features, such as horizontal distributions and PDFs. The rainrate derived from the reflectivity at 3 km is then used to build the symmetric error model of the maximum composite. However, the maximum composite and reflectivity at 1 km and 3 km, respectively, could be different. The correlations between the derived rainrate and the maximum composite (or/and the reflectivity at 1 km) are needed d to clarify the potential inconsistent usages of data.

1. There various types of data used in this work, especially with different horizontal resolutions (e.g., the 5-km CMPAS and 3-km WRF products). Thus how the interpolation performed to deal with the inconsistent resolutions needs clarification. It is possible that the interpolation increases the OmB variances. The authors emphasize that all data are collected in mountainous areas. Does the interpolation consider the effects of terrain? Moreover, how about the resolution of CVMR and CAPPI used in this study?

1. The reflectivity OmBs highly depend on the forward operator. More elucidations about the forward operator are needed, in order to clarify how the OmB is derived.

1. Figure 8, it is interesting that the logarithmic rainrates (Figure 8c) has a different distribution than the rainrates (Figure 8a) and CMPAS rainrates (Figure 8b), for the magnitudes of rainrates larger than 10 mm h^-1. Why the three-piecewise fitting function for the logarithmic rainrates does not capture the decrease trend for those magnitudes larger than 10 mm h^-1?