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| 11 Jul 2025
Intermediate-complexity Parameterisation of Blowing Snow in the ICOLMDZ AGCM: development and first applications in Antarctica
Abstract. Recent regional model findings suggest that the aeolian erosion of surface snow is a significant contribution to the overall Antarctic surface mass balance (SMB) through ice crystals sublimation and export outside of the ice sheet. Such findings raise the question of the relevance of accounting for such a process also in global climate models. This study presents the development of an intermediate-complexity parameterisation of blowing snow for the ICOLMDZ atmospheric general circulation model, the atmospheric component of the IPSL Coupled Model. The parameterisation is designed to be a trade-off between physical complexity and applicability in a general circulation model, with constrains on numerical cost and stability. The parameterisation is evaluated with in situ observations using limited-area simulations over Adélie Land. The model exhibits satisfactory results in terms of summer wind speed, temperature and intensity of blowing snow fluxes. In winter, blowing snow intensity and occurrences are overestimated close to the coast, concurring with a positive wind speed bias. In terms of blowing snow occurrences throughout the year, ICOLMDZ exhibits comparable performance with the regional atmospheric model MAR. Boundary-layer moistening and cooling as well as changes in surface radiative fluxes due to blowing snow crystals are also quantified in the simulations. Global simulations at standard global climate model resolution are carried out to investigate how the Antarctic surface mass balance is modified with the activation of the blowing snow parameterisation. Results show an overall decrease of the net snow accumulation in the escarpment region due to surface snow erosion and an increase along the coast due to blowing snow deposition and increase in precipitation.
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CEC1: 'Comment on egusphere-2025-2871- No compliance with the policy of the journal', Juan Antonio Añel, 28 Jul 2025
Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.htmlYou have archived your code on servers not suitable for scientific publication (e.g., a svn in jussieu.fr and GitLab sites). You must store all the assets necessary to replicate your manuscript in a suitable repository, from the ones listed in our policy. Also, you have not published the output data from your simulations, and you must do it. Therefore, the current situation with your manuscript is irregular.
Please, publish your code and data in one of the appropriate repositories and reply to this comment with the relevant information (link and a permanent identifier for it (e.g. DOI)) as soon as possible, as we can not accept manuscripts in Discussions that do not comply with our policy.
Also, remember to include a modified Code and Data Availability sections in a potentially reviewed manuscript, containing the information of the new repositories.
I must note that if you do not fix this problem, we can not continue with the peer-review process or accept your manuscript for publication in our journal.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2025-2871-CEC1 -
RC1: 'Comment on egusphere-2025-2871', Anonymous Referee #1, 12 Aug 2025
Review of manuscript egusphere-2025-2871: ‘Intermediate-complexity Parameterisation of Blowing Snow in the ICOLMDZ AGCM: development and first applications in Antarctica’ by Vignon et al.
This study aims at developing and evaluating a parameterization of wind-driven snow transport for global climate simulations using the atmospheric general circulation model ICOLMDZ. The parameterization approach is similar to that in the regional atmospheric model MAR. However, the mass mixing ratio of blowing snow is a separate prognostic variable to distinguish blowing snow from precipitation. Additionally, a double-implicit numerical method is proposed to compute blowing snow sublimation, leading to stable and accurate results despite the large time step needed for global simulations. Using a limited-area simulation over one year, the blowing snow parameterization is compared with in-situ measurements of blowing snow (FlowCapt sensors) and standard meteorology at two Antarctic sites. The frequency and timing of blowing snow events are similarly well reproduced as in the MAR model although the modeled event frequency differs from the measured one by a factor of two in some months. A direct quantitative comparison of the horizontal mass flux of blowing snow is not possible as the measurements cover the lowest one or two meters of the atmosphere while the first grid level of the model is at a height of approximately 8 m. Nevertheless, the authors extrapolate linearly the measured mass fluxes to estimate the vertically averaged mass flux in the layer corresponding to the first model layer, at least at one site. By comparing this estimate with the model result at the first grid level, they conclude that the modeled particle mass flux has a reasonable order of magnitude. Finally, the authors use a model set-up for global simulations and show that blowing snow clearly decreases (increases) the surface mass balance in the escarpment zone (at the coast) of East Antarctica.
General comments
This paper addresses relevant questions as blowing snow is a wide-spread and frequent phenomenon in Antarctica and other snow-covered regions. The text is generally well structured. The results are well illustrated by figures and mostly discussed appropriately.
(1) As emphasized by the authors, however, a quantitative validation of the modeled intensity of blowing snow is very challenging due to the coarse vertical grid resolution. I see the following problems with the model-measurement comparison and consequently with the conclusion that the ‘[blowing-snow flux] amplitude is also fairly well reproduced’ (l.456):
(a) The horizontal mass flux of blowing snow does not decrease linearly with height. The authors mention the exponential decay in the saltation layer (l. 313). In the suspension layer, the mass flux is also expected to decrease non-linearly with height as the particle concentration can be approximated by a power-law function (e.g., Gordon et al., 2009; Mann et al., 2000; Sigmund et al., 2025) and the wind speed and particle speed profiles by logarithmic functions. Therefore, the linear extrapolation used in the present study appears inappropriate.
(b) The authors consider the mass flux of blowing snow simulated at the first grid level as ‘a mean value over the full first model layer’ (l. 309). However, as the mass flux decreases non-linearly with height, the mass flux at the first grid level (center of the grid layer) is expected to be lower than the mean value over the first grid layer. Even if the observation-based mean value over this layer was accurate and the same value was modeled at the first grid level, it would imply an overestimation of the particle mass flux and concentration in the model, which would propagate to higher grid levels through the diffusion-sedimentation equation.
(c) l. 271 – 273: Did the measurement sites experience net snow accumulation and did the lower FlowCapt sensor get burried gradually during the course of the year?
(2) To improve the model-measurement comparison and increase the confidence in the blowing snow parameterization, I have the following suggestions:
(a) Instead of extrapolating the measured mass fluxes, one could estimate model-based vertical profiles of blowing snow concentration and wind speed between the snow surface and the first grid level, using the parameterization assumptions and findings from the literature. For example, the particle concentration can be interpolated between the saltation-suspension interface and the first grid level, using a power-law function of height (e.g., Gordon et al., 2009) or a logarithmic profile as implied by the bulk flux parameterization for the vertical blowing snow flux at the lower boundary (Eq. 5). By multiplying the particle concentration and wind speed profiles, it is possible to estimate the mean particle mass flux over the layer covered by the FlowCapt sensor(s) and achieve a more consistent model-measurement comparison.
(b) If the FlowCapt sensor was partially burried and changes of surface elevation were monitored,, it would be best to scale the FlowCapt measurement of the partially-burried sensor to obtain the particle mass flux vertically averaged over the wind-exposed part of the sensor. The model-based estimate can be averaged over the same height range, which changes with time.
(c) Recently, Nishimura et al. (2024) published almost three months of blowing snow profile measurements at Mizuho Station, East Antarctica, which had been partly analyzed in Nishimura and Nemoto (2005). The profile was measured using four snow particle counters. As the uppermost sensor was at a height of 9.6 m, this dataset offers an excellent opportunity to evaluate more directly the modeled mass flux at the first grid level.
I recommend major revisions to take these suggestions into account and address the following comments. With revisions, the study has the potential to become a valuable contribution to the research field.
Specific comments:
(3) l. 41-45: It would be worth to mention the paper of Saigger et al. (2024), which describes an intermediate-complexity parameterization of blowing snow in the WRF model. Please also provide examples on how an intermediate-complexity parameterization differs from more complex ones.
(4) l. 101: The vertical transport of blowing snow does not only occur through turbulent diffusion but also sedimentation. Although the individual terms of the prognostic equation for blowing snow are presented later, I propose to add the prognostic equation for qb (combining the left-hand-sides of Eqs. 6, 8, 13 and the advection term) to better guide the reader.
(5) l. 113: Should (rho_i/rho_s0 – rho_i/rho_s) be an exponent as in Amory et al. (2021)? Otherwise, the threshold friction velocity is not u_*t0 but zero for new snow (rho_s = rho_s0).
(6) l. 143: Is an exponent missing in Eq. 3 and is the associated citation of Pomeroy (1989) correct? Both is inconsistent with the corresponding description of MAR below Eq. 5 in Amory et al (2021).
(7) l. 179: ‘radius r_b’: Do you assume a constant particle radius at all heights? This should be clearly stated and the value of the radius should be specified.
(8) l. 180: In the cited publications, I could not find Eq. 8 but only similar equations. When trying to derive Eq. 8, I arrived at a slightly different equation. In contrast to Rutledge and Hobbs (1983), the ventilation factor seems to be missing; or is it included in the terms A’ and B’? Where does pi in the denominator come from? I assume that the final units should be kg kg-1 s-1; is the air density in the numerator needed?
(9) l. 197: When rearranging Eq. 10 to obtain Eq. 11, did you forget the fraction 6 rho / (rho_b pi r_b^2 (A’+B’)) ?
(10) l. 207 – 209: How does the time scale tau_m affect the simulation? As this time scale is 10 min or lower and the typical time step is 15 min, the blowing snow particles melt and evaporate within one time step in the considered situation. Does tau_m influence the radiative effect of blowing snow in the time step?
(11) l. 265: Can you describe the terrain surrounding the measurement sites? This might be relevant for the comparison of modeled and measured wind speeds.
(12) l. 286 – 288: The sentence sounds like you use a weighted average to combine observed and modeled SMB into a final estimate. After checking Agosta et al. (2019), however, I assume that you perform a weighted average of SMB observations that fall into the same ICOLMDZ grid cell. Please clarify. Apart from that, if an observation spans a longer period than the 5-year simulation period, do you only use the observations during the simulation period or the whole observation period?
(13) l. 292: ‘simulated roughness length’: Prescribed roughness length would be a better wording if it is a constant value for snow and ice surfaces as stated in l. 70.
(14) l. 367 – 369: For D47, the agreement between modeled and measured RH (Fig. 3f) is not discussed. It should at least be mentioned that lower RH values in the model compared to the measurements can be expected at D47 as the first model level is above the measurement height at this site.
(15) l. 397: ‘the simulated frequency is more realistic in July, August and December at D47’: In July and August, this may, at least partly, be due to an overestimation of wind speed.
(16) l. 412: ‘turbulent latent heat flux’: I assume this refers only to the flux at the surface and does not include blowing snow sublimation, right?
(17) l. 423: ‘a few tens of K’ should be a few tenths of K if you mean a fraction of 1 K (?)
(18) l. 432 – 434: Does the blowing snow parameterization lead to an improved agreement with the SMB measurements? Or is a direct comparison not meaningful?
(19) l. 442: ‘no overall increase in large-scale precipitation’: Do you expect that large-scale precipitation would increase if blowing snow particles were considered as ice-nucleating particles in cloud formation?
(20) l. 456: ‘the moistening effect of the surface layer is underestimated’: This conclusion is not sufficiently discussed. You mention in l.368 that ‘the model fails to capture periods of saturation [at D17]’ but is it clear that this is due to an underestimation of blowing snow sublimation? Or could there be other reasons such as an overestimation of air temperature?
(21) l. 457: ‘During winter, wind speed, snow flux amplitude and occurrences at D47 are well simulated’: This statement contradicts l. 394 – 395: ‘the July value [of the blowing snow flux intensity] - very close to the FlowCaptTM measurements between 0 and 1 m - is likely overly strong’.
Technical corrections:
(22) Typo in short summary: ‘Simulations avec evaluated using measurements in Antarctica.’
(23) l. 99: ‘specific content of blowing snow particles in suspension qb’: I suggest to provide units (kg kg-1) or call it the mass mixing ratio to be more precise.
(24) l. 113: Equation number is missing
(25) Caption of Fig. 6: averahed should be averaged
(26) l. 151: U should be defined in the text below Eq. 5.
(27) Caption of Fig. 1 (4th line): T, P, and RH_i should be defined here as they have not been defined in the main text yet. A full stop is missing after ‘converge)’.
(28) l. 205: The ‘reference curve’ should also be explained in the main text, not only in the figure caption.
(29) l. 208: I assume that T in Eq. 12 is air temperature but it is not defined in the text.
(30) Figure 5: Black and blue dots are difficult to distinguish. Can you use different colours or show separate plots for model and measurement results?
(31) l. 397: ‘despite but underestimated’: Please check meaning and grammar.
(32) Caption of Fig. 8: ‘Net surface radiative flux’ should be net shortwave surface radiative flux. The dash-dotted line in panel e should be explained. Please mention the sign convention for the surface turbulent fluxes (positive = downward?).
(33) l. 422: a reference to Fig. 9b is missing
(34) l. 480 – 483: Please check the grammar.
(35) l. 671: There is a typo: ‘dOI:’
References (apart from those listed in the manuscript)
Gordon, M., Savelyev, S., & Taylor, P. A. (2009). Measurements of blowing snow, Part II: Mass and number density profiles and saltation height at Franklin Bay, NWT, Canada. Cold Regions Science and Technology, 55(1), 75–85. https://doi.org/10.1016/j.coldregions.2008.07.001
Nishimura, K., & Nemoto, M. (2005). Blowing snow at Mizuho station, Antarctica. Phil. Trans. R. Soc. A. 363, 1647–1662. https://doi.org/10.1098/rsta.2005.1599
Nishimura, K., Sigmund, A., Melo, D. B., & Lehning, M. (2024). Profile measurements of snow transport and micrometeorology at Mizuho Station in Antarctica [Dataset]. EnviDat. https://doi.org/10.16904/envidat.540
Saigger, M., Sauter, T., Schmid, C., Collier, E., Goger, B., Kaser, G., Prinz, R., Voordendag, A., & Mölg, T. (2024). A Drifting and Blowing Snow Scheme in the Weather Research and Forecasting Model. Journal of Advances in Modeling Earth Systems 16, e2023MS004007. https://doi.org/10.1029/2023MS004007
Sigmund, A., Melo, D.B., Dujardin, J., Nishimura, K., & Lehning, M. (2025). Parameterizing Snow Sublimation in Conditions of Drifting and Blowing Snow. Journal of Advances in Modeling Earth Systems 17, e2024MS004332. https://doi.org/10.1029/2024MS004332
Citation: https://doi.org/10.5194/egusphere-2025-2871-RC1 -
RC2: 'Comment on egusphere-2025-2871', Anonymous Referee #2, 13 Aug 2025
The following is a review of “Intermediate-complexity Parameterisation of Blowing Snow in the ICOLMDZ AGCM: development and first applications in Antarctica” By Étienne Vignon and others.
This manuscript describes the integration and evaluation of a blowing snow parameterization for Antarctica. Blowing and drifting snow on the surface of ice sheets, particularly Antarctica, has been shown to be a nontrivial contribution to surface mass balance. However, representation of this process is included in few regional-scale models used to estimate ice sheet surface mass balance. This study is novel in that it investigates the utility and computational burden of including an intermediately complex parameterization of blowing and drifting snow into an atmospheric general circulation model (GCM) that has been recently modified to better capture near-surface winds. The authors present the model design and implementation, model evaluation, and impact on surface mass balance including discussion on thermodynamic and cloud effects due to the new model capabilities. Estimates of blowing snow show skill against observations in the test region of Adélie Land and are comparable to results from a regional climate model. Finally, the authors present results of global-scale simulations with and without blowing snow and show general climatological agreement with observations with respect to surface mass balance.
Overall, I find that the manuscript is organized and nicely written. Model assumptions are clearly articulated within the text. For the most part, I find the modeling procedure easy to follow and that the figures are of good quality. The paper focuses on describing the model and evaluation against observations, which is appropriate content for GMD. As a result, I am recommending it for publication after suggested edits. Specifically, I would like to see the authors expand the discussion to explicitly provide closing thoughts about some of the key motivating questions that are brought up in the paper introduction, specifically those related to whether blowing snow should be included in GCM’s. These are important questions that are touched upon early in the manuscript that make this study particularly engaging to the audience, and I think it would improve the paper to touch upon them again after the results are presented. Please see more detailed comments below.
Questions and suggestions:
Line 27 and Line 447: I agree, the past research and this study raises this important question. It would really help round the paper out if the authors explicitly gave an opinion of the answer to this with respect to their results and what is presented in the discussion. In my view, the statement does not have to be strongly conclusive of final in any way (considering the uncertainties that are discussed) but since the important questions is raised, it would strengthen the paper to have it addressed directly within the text.
Line 33 and Line 446: It is clearly noted that transport of mass off the continent is an important part of the quantification of SMB by the model, and that including wind-blown snow could represent this discrepancy. Including some statistics about how much snow is estimated to be transported off the continent in the global runs would be very helpful for the reader to grasp if the process is significant to the GCM simulations. One suggestion is to make direct comparison with these estimates of percent change from other studies that are referenced in the paper, to offer insight into how important the process is in the GCM. (This suggestion ties in strongly with the above L27 comment).
Line 122: Does snowfall accumulated here also include snow that is deposited (sedimentation?). It is unclear from the text if the snow being deposited is feeding back to this aging estimation. Perhaps a rephrasing of this paragraph and specifying what is meant by snowfall accumulation would help with the confusion.
Line 225: Is the snow age “reset” from a different value when it snows? Or is it just “set” to 0 for new snow when it snows? This wording is a bit confusing, especially since the statement above suggests that if snow falls and it happens to be eroded then the densification equation is used. But in this specific case, would the value be 0 even though it snowed but did not actually accumulate? This might just be a question of the terms used for the different ways snow can accumulate, and I suggest using precise wording and definition for each. As noted above, maybe a rephrasing of the entire paragraph would help.
Lines 126-129: This last sentence is also awkward and difficult for the reader to follow.
Line 211: Similar to the above questions, does this end up getting treated the same as precipitation in some way? What is “precipitation” consisting of? How does deposited snow feed back into the densification equation?
Line 352: Could you add a comment on if we should expect that the parameterization significantly affects wind or temperature? Is this surprising at all?
Lines 391-392: Figure 6e does not appear to show that there is an overestimation of flux during these months. Perhaps I am misunderstanding the comment and if so, please rephrase.
Lines 431-432: Do you think this is associated with the spatial resolution that you needed to run with? Or do you think there is physics that is missing to capture these winds? Please add a brief comment to this effect in the text.
Line 434: Here you state that the differences should be considered negligible locally. In the same vein as my earlier questions about the significance of blowing snow and its continental-scale magnitude, I suggest the authors bring the implications of this result back up in the discussion. It seems to be an important conclusion to this work. Is this value negligible locally but more significant continentally?
Figure 10: Caption – please specify in the caption the difference between “observed SMB values” in a) and SMB observations in b). My understanding from the text is that they are different because the grey dots in a) are the points of the observations themselves and the circles in a) are those positions interpolated onto the GCM grid. This would make sense why there are many more circles in a) closer to the pole. But it seems like there still should be way more circles in a) in Thwaites and Ross area. Are the grey also showing the locations of observations that do not meet the criteria of use? If so, those observation locations should probably be removed from b). It is also unclear why there are values off the coast of Ronne when there are no grey dots in b) near those locations. Please clarify this in the text and in the caption.
Figure 10 and Line 440: The plots here are a little confusing, because there are many SMB values outside of the continent. I realize that is might be where the blowing snow is depositing, but for this case in b), is precipitation outside of the ice sheet being considered for both the with and without blowing snow simulations? (I suspect maybe yes since there are negative values for b) outside of the ice sheet.) Or are the values outside of the ice sheet only AIS-sourced values (i.e. wind-blown and not atmospheric precipitation). In that case, can the values outside really be considered true SMB? I guess it is also possible that the GCM ice sheet grid extends past the black coastline boundaries drawn on the figure. Please try to revise the text and caption to be clearer about what is being shown.
Figure 11: I have a similar confusion to the above, over Fig. 11 which shows (precipitation – erosion). What is “precipitation” in this context? Presumably it is the blowing snow deposition? Most likely, clarifying the text and caption for each figure would alleviate most of the confusion.
Minor edits:
Line 45: This statement is awkward, please rephrase. Maybe use “constraints” instead of “constrains”?
Line 104: “in” -> of
Line 159: “authors” -> authors’
Lines 306-307: precipitation “is” diagnosed? “prevent” -> “prevents us”? In general, this sentence is awkward. Please rephrase for clarity.
Line 313: “follows”
Line 317: “measures” -> measurements (?)
Line 323: “event” -> events
Line 344: “month” -> the month
Line 391: “first model” -> the first model
Line 393: “at” -> during (?)
Line 423: Should this be “tenth of K”? A few tens of K seems very large.
Line 424: Antarctic
Citation: https://doi.org/10.5194/egusphere-2025-2871-RC2 -
RC3: 'Comment on egusphere-2025-2871', Anonymous Referee #3, 17 Aug 2025
This study aims to incorporate blowing snow physics in ICOLMDZ global climate model to improve the representation of Antarctic SMB. The manuscript is well-written and structured. The study is appropriate and fits within the scope of GMD and timely. However, the main novelty of the paper wrt 'intermediate-complexity' blowing snow parameterisation for a GCM needs more explanation, justification, and rewriting. The authors mention that increasing the grid resolution near the surface would 'unreasonably increase' the computational cost, however contrary to the approach used in typical RCMs, it appears that in the current approach the authors also run the blowing snow model at atmospheric heights (all model levels) where there would be no blowing-snow, which is also computationally not efficient. In addition, it appears there are few inconsistencies wrt to the parameterisations and observations, which need to be addressed before the manuscript is accepted for publication.
The manuscript would also benefit from proof-reading. There are multiple typographical errors in very important places, which makes it a little difficult to read.
Major comments:
1. Line 100: It is not clear to me what exactly author's mean by intermediate-complexity, please elaborate in comparison with other implementations in meso-scale models.
2. Line 115: What's the justification for the use of threshold friction velocity of 0.211 m/s? In Gallee (2001) u*t0 is a variable (Eq. 3 in Gallee 2001) and subsequent implementations in RACMO and other models use this (although with some assumptions wrt snow dendricity etc). Using a constant u*t0 would influence the quantity of blowing snow in the model. Where is this number coming from, please justify.
3. Equation 3 seems incorrect, it must be 0.08345u*^1.27 (Pomeroy and Male 1992, Eq. 37). What exactly was implemented in the code?
4. Line 204: Are the idealized simulations performed within the global model run or is it an offline run? And what is the 'oscillating behaviour' being talked about here?
5. Line 216: Agree, but there is no description about the particle sizes considered in the study which is a critical parameter influencing the blowing snow flux. Please include that in the revised paper.
6. Fig 3: Elevation changes due to snow deposition makes the acoustic tubes submerged and the flux might not be representative of the average flux at 1 m and 2m. Did you account for the elevation changes? For explanation, see Amory (2020) and Gadde and van de Berg (2024) Eq. 11.
7. Figure 5: Why was this not plotted for D17? Please include the figure in revised manuscript for consistency.
8. Line 375 and Figure 5: Blowing snow flux has non-zero value at lower velocities when compared to the observations, this perhaps has to do with the assumption of constant threshold friction velocity of 0.211 m/s.
9. Line 487-488: Is the blowing snow variable defined at all the model levels i.e. 95 model levels for the LAM run and 60 model levels for the bigger run? This seems like an overkill. Observations and meso-scale simulations are pretty consistent that the blowing snow phenomenon is mostly a lower boundary layer phenomenon. See Palm et al. 2017, RACMO results from Gadde and van de Berg (2024) (Fig. 5b). Gadde and van de Berg (2024) use only 16 grid points for the blowing snow model, with finer grid near the surface and results show good agreement with the observations without significant computational overhead. Please add in the discussion reason for not taking the standard approach of including the physics comparing it with your approach.
10. Add the computational cost of Blos vs No-Blos simulations.
Minor comments:
1. Line 45 : climate global run's constrains -> global climate run's constraints
2. Line 26: (- that we will hereafter combine into the single denomination of blowing snow for convenience -) too wordy - rephrase with 'hereafter blowing snow'.
3. Line 113: Density terms need to be an exponent according to Gallee (2001)?? Equation number is also missing.
4. Line 295: closet -> closest
5. Line 345: resp.???
6. Line 423: tens of K? or few tenths of K?
7. Line 510: While you mention that the code can be downloaded freely from the LMDZ website, it seems it is really not that straightforward. I tried to have a look at the blowing snow parameterisation, but could not figure out where to download the svn version that you used.
If possible, please share the code/physics modules used in an easily accessible public repository for the benefit of the readers.Citation: https://doi.org/10.5194/egusphere-2025-2871-RC3
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