The manuscript “Improvement in algorithms for quality control of weather radar data (RADVOL-QC system)” written by K. Ośródka and J. Szturc describes new version of a quality control algorithm designed for radar data of the Polish weather radar network POLRAD. The manuscript in details describes improvements of the current version of RADVOL-QC system in comparison with previous version published in 2014.

The manuscript describes in more detail new algorithms that focus on solving problems mainly due to the influence of wind turbines and RLAN signals, which increasingly negatively affect radar data. In addition to the description of individual algorithms, the manuscript also verifies the efficiency of the described algorithms. This verification is primarily visual. The article would benefit if the verification were performed in some "objective" way, but I am aware that it is not easy and I do not insist on this verification.

The algorithms are described but their parameter values are shown only in one case. It would be nice for readers and potential users of described algorithms to know specific values of thresholds used by the authors.

The article is well structured and is written clearly. It is obvious and well known that the authors have been interested in the given topic for a long time and they are experts in this field. I appreciate that the article is based on and solves real operational problems associated with the preparation of radar data. The topic is suitable for the selected journal and will be interesting for people using meteorological radars as they propose new tested algorithms.

I recommend improving the language of the text.

I recommend accepting the manuscript after miner revision.

Specific comments:

Line 71 – Please, reformulate “is assigned a single measurement”.

Line 74 – “,” should be after RADVOL QC.

Line 78 – I recommend explaining why data should be extrapolated to the Earth.

Line 117-118 – Could you describe in more detail “this in fact …algorithm”.

Line 141 – I do not consider “event” as an appropriate word in this context. Convective weather?

Line 204 – “significantly” is not suitable word in this context.

Line 232 – Could you clarify your statement about the threshold value?

Line 299-301 – Do you say that after this sentence the modified algorithms are described? It is not obvious to me.

Line 334 – When you speak about echo here and also in other parts of the text do you mean non zero reflectivity or reflectivity exceeding some threshold?

Line 399 – Please reformulate the sentence “If a …”.

Line 410-412 – I am not sure that I understand the meaning of the sentence. What is the first condition and when is the procedure stopped?

Line 420 – interpolated instead of interpolates.

The article "Improvement in algorithms for quality control of weather radar data (RADVOL-QC system)” by Katarzyna Ośródka and Jan Szturc presents some newly developed and enhanced algorithms and methods of filtering and quality evaluation of weather radar data in the RAVOL-QC software developed in the Polish Institute of Meteorology and Water Management, mainly focusing on non-meteorological echo identification. It describes two method using dual-polarization data and two method using single-polarization data. The manuscript addresses actual problems, especially the detection of wind turbines and RLAN interferences. It is well written, clear and the cited literature is relevant and actual. The paper can be considered as very useful for the weather radar scientific community to further enhance the usage of weather radar data. It fits very well the topic of the selected journal.

The rather subjective evaluation techniques, not well described threshold and parameter selection and the lack of mention about some possible annual variability can be considered as shortcomings of the article.

I recommend accepting the manuscript after minor revision.

Specific comments:

Line 62 - Maybe indicate, that the polarimetric radars are depicted by red circles in the map.

Line 136 – How were the “ground-truth” classes determined?

Line 169 – Does the membership functions depend on the time of year (summer vs. winter cases)?

Line 174 – How were the weights obtained – some evaluation algorithm or expert knowledge?

Line 193 – Does the effectiveness depend on the time of year?

Line 199 – Consider replacing “a lot of” by “several” or some similar term.

Line 205 – Maybe a picture without the SPIKE algorithm should be more appropriate.

Line 214, 255, 287 – QI chosen by expert knowledge? Why not lower?

Line 220 – Why was sd(Zdr) excluded?

Line 228 – Does the threshold values depend on the time of the year (snow vs. liquid precipitation)?

Line 223 – Fig. 6 vs. Fig. 4 - inconsistency about sd(Phidp) – In Fig. 4 is everything below cca. 22° considered as meteorological, in Fig. 6 the threshold is set to 10°. Is there a reason to use different thresholds in the two algorithm?

Line 216 – It seems to me from the paper, that the DP.TURBINE was not intentionally designed to detect wind turbines, it just turned out to be better at this type of obstacles, as it is stated later in the line 247.

Line 271 – Fig 8. Text labels in the picture are duplicated.

Line 439 – The verification of DP.NMET, TURBINE and SPIKE is presented only in forms of some case studies – no statistical evaluation is present.

Section 5 – As the aim of the paper is to present the newly developed and enhanced filtering algorithms, it can be interesting to compare the results in Fig. 12 and 13 where RADVOL-QC is used with and without the new algorithms to see the effect of the presented methods.