The manuscript provides impact assessment of massive GNSS-RO observation on UKMO’s NWP system. The first half of the manuscript discusses the cause and solution of the forecast score degradation due to the introduction of large volumes of data, while the latter half presents how forecast score changes with the increasing number of observations. Observing System Experiments (OSEs) show that simply increasing the number of observations degrades forecast scores especially at troposphere. Sensitivity experiments employing 1D-Var show that observations at lower stratosphere induce change in the troposphere. OSEs with modulated refractivity observation operator coefficients, which aims to reduce the observation- background biases, show improved performance as the number of assimilated observations increase.

The manuscript provides comprehensive analysis on the impact of massive GNSS-RO observation on NWP system which also gives insight into essential role of GNSS-RO observation. The manuscript is definitely very dense and rich in information based on numerous OSE results. I think the content of the manuscript is very variable to the community and suggest publication after some revisions that might help to clarify the following points:

1. It seems that Figure 6 and its description/discussions are not consistent. Please provide more explanation on the figure and how you interpretate it.
2. While Figure 22 to 25 shows RMSE rises as observation number increases, section 4.3 states that RMSE decreases as observation number increases. It is confusing and I suggest that taking consistency between the explanations and the figure. Also please add explanations on “change in the RMSE scorecard”.
3. In section 2.4 (line 178), it is stated that “change in tropospheric geopotential heights are likely due to a systematic reduction in the atmospheric pressure”, whereas section 2.2 (line 130) states that “An adjustment to the atmospheric state below the observation will alter the modelled height of the observation”. Since these sentences both explain same thing, ensuring consistency among these sentences will make it easy for the reader to follow the argument

Other suggestions:

1. line 40: CGMS is not a sub-body of WMO.
2. line 105. Figure 1 does not provide information about bias change. It is beneficial to present figure on bias change for the reader to follow the argument.
3. line133: Looking again at 2 => Looking again at Figure.2
4. line 134: Add citation for “golden region”.
5. Section 2.4 : It would benefical for the reader to present figure how O-B statiscs changes by modulating foreward operator coefficent.

The manuscript presents a nice study on the impact of large numbers of real

GNSS-RO data on the MetOffice NWP system in the context of the ROMEX project,

and shows some interesting lessons that can be learned with such a large

dataset.  It is well readable and mostly very clear, nevertheless it might

need explanations in some places to address readers outside of the

radio-occultation community or who are not familiar with NWP systems or data

assimilation for NWP.

Futhermore the manuscript could be slightly improved by addressing the minor

issues and needed clarifications as discussed below.

- Page 2, line 40: CGMS is not a subgroup of WMO, but a "multi-lateral

  coordination and cooperation across all meteorological satellite operators

  in close coordination with the user community such as WMO, IOC-UNESCO, and

  other user entities" (text taken from https://cgms-info.org/about-cgms/)

- Page 4, line 90ff: the description of the NWP system could be slightly more

  specific.  Analyses every 6 hours?  Which forward model used for GNSS-RO?

  There are several implementations, and technical details like refractivity

  expression etc. are of interest.  (It seems clear to me that bending angle

  is used, but some centres use refractivity.)  A reference, ideally also

  outlining the modeling of observation error would be great.

  (Section 2.4 does discuss refractivity in passing.)

  Did the authors make initial assumptions about data quality from different

  missions?  Some NWP centres choose not to assimilate all data equally, and

  the authors themselves noted (line 342) that using data from a particular

  mission showed a degradation of the scores.

  Line 91: Not really important, but does the lowest model layer have a

  full-level height of 20m, or is it the actual depth of that layer?

- Line 102ff: when presenting forecast scores, always specify against which

  "truth" the verification is performed.  Neither the text nor the caption of

  figure 1 explain the observation type being used (radiosondes)?

  The caption also refers to surface observations (SYNOP), but I cannot find

  related entries in the figure.

- Line 116 and figure 2:

  - does the figure show the mean error for all observations processed, or

    has a quality control been applied?

  - there are several spikes (or wiggles) of varying amplitude visible in the

    plot.  What is the origin of these spikes?  Interpolation of observations

    or of model equivalent?  E.g. the region between 15 km and 20 km is so

    noisy that the reader can hardly guess the average bias.

    The spikyness also varies a lot with latitude band (fig.15).  Can this

    have an effect on the results shown in fig.16?

  - does this spiky behavior also occur in the forward operator used in the

    variational assimilation?  If so, does it affect the modeling of error

    (background / observation)?

- Page 8, line 134: the "golden region" may be colloquially known to experts

  in the field, but either a reference or a less colloquial description would

  help the non-experts.

- Line 148: "This shows a large reduction in the forecasts ..."

  The reduction is shown here for *bias*.

  It appears that geopotential bias is globally averaged (without stating

  so).  Is this effect seen similarly in the extratropical hemispheres?

  Regarding the quantification of the reduction: this is against ECMWF

  analyses!  While it is numerically fine, one could also argue that analysis

  biases are more consistent after the adjustment.  On the positive side,

  the *global drift* of bias during forecast seems much reduced.

- Page 15, section 2.5: please specify a "typical" (or reference) lead time

  of background forecasts.

- Line 21: "... fit to the independent observations ..."

  What does "independent" refer to here?  Does this express that these

  observations were not assimilated, and the set of observations in fig.12

  is different from those in fig.11?

- Page 25, line 319: "... whereas the ECMWF system has little bias".

  Everybody may argue that this is true to a good extent, but some would

  rather say "... presumably has a smaller bias", or similar.

- Line 320ff: "This may be partly due to the model ..."

  I find the description of the treatment of variables in the forward

  operator very confusing and not helpful.  Could issues in the forward

  operator also explain the mean error patterns seen in fig.2/fig.15, or is

  there a relation?

- Page 26, line 346ff: reference or personal communication?

- Page 26, section 4.2: please specify the background lead time.

- Page 28, line 371ff: the text here and the caption of figs.22-25 are not

  consistent.  The text refers to a change in RMSE, where the reader expects

  a decrease if the systems improves (similarly to fig.21 for the (O-B)

  statistics), while the figure captions refer to the "RMSE scorecard", where

  an increase denotes better results.  Can the authors please resolve this?

- Page 30, line 388: "differences in locations of the verifying data points"

  It is not the locations alone but data density and spatial sampling that

  skews the verification against observations where each profile is both used

  and counted, while verification against analyses is less affected.  I

  recommend to reformulate slightly.