General comments:

This paper briefly describes the implementation of synthetic float capabilities in E3SMv2, then presents insights gained from the synthetic floats in several case studies. The manuscript is interesting and well written. However, even though I loathe gatekeeping based on journal scope, I do question whether the current form of the manuscript is suited for GMD as a development and technical paper. I would suggest more discussion about how the floats were implemented in the model and an evaluation of related development topics, like how much using the floats impacts the computational cost and whether it scales with the number of floats or the number of output variables saved, and also a more quantitative rather than qualitative evaluation of the model simulation accuracy. 

Specific comments:

Lines 80-83: It should be clearer here that only the MPAS-O and -Seaice components are being used, and not the coupled land or atmosphere. This is stated in Section 2.2, but introducing the atmosphere and land components here gives the wrong impression that they are being used.

Section 2.2: For reproducibility and meeting interests of GMD readers, this section should provide more details about the model, particularly other components of the forcing like river runoff, atmospheric deposition, and atmospheric CO2 concentration if they are included in the forcing. 

First paragraph of Section 3.1: I think this paragraph buries the lede. It begins by discussing where 1000 m velocities are high and low in the model, and then showing that these Eulerian velocities are similar to those derived from the Lagrangian floats. Only then does it note that the model velocities are 2--3x lower than estimated from actual Argo floats. These seems to me to be a critical bias, and the impacts of it should be discussed and not glossed over. 

Section 3.1 in general: it would be good to have more quantitative comparisons between the model results and the Argo obs or between the model Eulerian/Lagrangian results. For Fig. 3, for example, it would be nice to know some combination of correlation, mean or mean bias, and RMSE. In addition to the speed it might also be good to know how accurate the current directions are, using something like the difference in direction.

Figure 5 and the associated text took a lot of time for me to understand, and I'm not entirely sure I still do. Maybe explicitly spelling out how the two values (daily, 10-daily) are being compared would be helpful (for example, maybe the x-axis of 5a would better be labeled as something like "% by which daily sampled trajectory is longer than 10-day sampled"). Also some clarity on how a longer trajectory means a lower velocity might help. 

Section 3.3.1: I don't understand why we're comparing monthly Eulerian model output with daily synthetic observations when, as summarized in the first paragraph of this section, it's more common to have daily Eulerian model output and sporadic observations.

Section 3.3.4: Is there any nuance to how the bloom timing is defined or is it just the day of year of the peak biomass?

Minor suggested edits:

Introduction: "e.g." is used very often 

Line 25: "have already permitted" -> "has already permitted"

Line 54: "uncertain" or "unknown" may be a better choice than "less clear"

Lines 120--121: This could explicitly state that "away from continental shelves and slopes" means "> 2000 m", at least according to the caption of Fig 2a. 

Line 193: "ascertain knowledge of" -> "know" or "understand"

Line 240: "any difference in the spatiotemporal variability"; difference compared to what?

In its current form, the manuscript is centered around a method for Lagrangian synthetic observation that is needed and will be welcome in the community. However, the paper needs more narrative focus and, therefore, requires substantial revision to be ready for publication. The paper's flow is non-standard in that there is never a summary of the research question and many of the described methods are saved for individual case studies. The text never mentions what these case studies will be until the results are described. This left me with a general frustration and a lack of context for the work. The individual case studies also felt scattershot and vaguely incomplete (the details of which can be found in the specific comments). Is this paper trying to quantify the skill of the Lagrangian method it introduces? Is this paper trying to quantify the skill of the E3SMv2 model? How do the case studies relate to the gaps posed in the introduction? There is a good scientific story here, but the writers need to work harder to find it. 

Specific Comments:

Line 1: ,and, more recently

Line 18: the greater than 

Line 24: deployment of more than 50 floats - Please recheck. SOCCOM has almost deployed 300 floats to date. 

Line 35: also Gille 2003 - Statistical behavior of ALACE floats at the surface of the Southern Ocean

Line 43: Also the BGC implementation plan 

Line 59: These have been estimated in chamberlain et al 2023 - Optimizing the Biogeochemical Argo Float Distribution

Line 68: Daily might be too slow to capture the long tails of wind driven flux which seem to be very important.

Line 71: As I understand it, this is the point of your method. I think you need to expand the reasoning behind this considerably to sharpen your argument.

Line 78: "we will present its utility for the ... research questions with several case studies" I still dont understand what the research question is, or how the method you are describing addresses those questions. You have done a good job summarizing some important gaps in our understanding of BGC modeling and BGC Argo observations. I encourage you to wrap this introduction up in a tighter bow.

97: This seems like a bad thing. Why did you make this choice? What are the impacts of this choice on velocity estimates? 

Figure 2: above “number of floats deployed per latitude, there are 2 scales. I do not understand what is being shown here

Line 106: So sea ice biogeochemistry is not the same as open ocean biogeochemistry? Why did you make this choice? What are its impacts? 

Line 110: recommend defining z-star levels for context

Line 119: This is an unstructured grid and you are deploying at every third vertex? This needs more explanation. Is the density of seeded floats inhomogeneous? Why did you make this choice? 

Line 135: At this point, I now know that you are going to use a BGC model with lagrangian observations, but I still dont understand what your research question is or how you intend to use these langrangian observations or why you would want to. Methods section has done a good job describing the WHAT of your analysis. Needs to be expanding to include the HOW.

Line 135: I recommend being more specific in your evaluation criteria. Something like Evaluation of synthetic float temperature, salinity, and velocity.

Line 136: Which synthetic float data? BGC profiles should be identical to the Eulerian model, unless I am missing something very fundamental.

Line 142: The case studies that you go through in this paper are never summarized in either the introduction or methods. This is problematic for 2 reasons, first I dont have context for where you are going with this analysis, second there are some details here that have never been explained. How do you calculate your lagrangian based velocities? Davis 1998 showed that there could be biases in these results if you arent careful with your distributions. 

Figure 3: The point of this plot is to intercompare velocities derived from different estimates, as such I strongly recommend changing to same colorscale. 

Line 147: Recommend making units of all three colorbars identical for easier comparison

Line 155: Assuming that E3SMv2 is perfect. This is a big assumption.

Line 159: Could spatial sampling be an issue as well?

Line 161: So, you are assuming a perfect model t-s distribution? Didnt you just mention that ACC currents are wrong by a factor of 4 and the gulf stream is too shallow. 

Line 167: I dont understand this conclusion or even the point of this section. Are you testing the model against Argo? Are you testing the subsampled lagrangian points against the model? I think you are missing a logical step. First, you need to validate the model against observation. Then you need to validate your subsampling against the model. 

Line 177: 50% too low? 

Line 180: What is the baroclinic rossby deformation radius at these latitudes? Do you think the model is resolving the eddy distribution accurately considering the resolution of your model?

Line 185: Another bias that needs mention is the at times 70 km grid cell resolution you are using to calculate these results. Based on the substantial low-bias in figure 3, I suspect that your velocity field is far too smooth. 

Line 190: Its not the readers job to imagine more applications. It is the writers job to tease the scientific story out of the results. 

Figure 6: In general the text and figures are too small for me to understand what the point of this figure is

Figure 6: Maps showing the ratio of the seasonal amplitude of nitrate

between the daily snapshots from the synthetic floats and the monthly mean Eulerian output at those model grid cells which are sampled by

a float each day over any full calendar year between 2012 and 2017. Please rephrase. This does not make sense to me. 

Line 200:, and by profiling floats,

Line 201: floats offer an advantage in temporal coverage over gliders?

Line 205: Figure 6

Line 215: What is the sensitivity of this estimate to float distribution and sampling fequency. 

Line 217: Absolute variability is smallest in the deep. Perhaps it would be illuminating to explain why you are using this metric? 

Line 221: What exactly are you testing and why? Yes, temporal averaging smooths out high frequency variability. Why did you need to use Lagrangian particles for this result?

Line 225: This should go in the introduction as it frames your work. Dont save it for the end.

Line 231: Why not compare 10 day float BGC sampling to 1 day float BGC sampling?

Figure 7: What is a subregion?

Figure 7: recommend moving description of method used for calculation to methods 

Line 248: These are not metrics that I am familiar with and I do not understand the specifics of the calculation. I recommend putting a description of this analysis in the methods section and expanding it. 

Line 259: I believe there is a hidden assumption in using NRMSE as a metric to quantify the number of floats required to reproduce the modeled field and that is the covariances are known perfectly. Typically, they are not. I think this should be mentioned. 

Line 267: The analysis presented so far is about resolving seasonal means, not trends. I agree that more sensors will always help, but I think it is important to clearly make this distinction. 

Line 285: how does this compare to wong and riser 2011?

Line 301: With a greater than 1/3 degree model, you are likely missing a lot of eddy activity in the high latitude. How might that impact your results? 

FIgure 9: Again, I recommend moving method descriptions from figure caption to methods section.

Line 333: were synthetic float observations staggered? or did they all sample on the same day every 10 days?

Line 339: Recommend looking at Ford 2021

Line 347: also Gille 2003

Line 365: The model has a 70km grid at the largest. I think you are parameterizing a lot more than internal wave dynamics.

Line 381: This distinction became more clear to me throughout the paper, but should be highlighted in the introduction.