General Comments

This is a well-written and scientifically rigorous manuscript that addresses the spatiotemporal scales of mode water transformation in the Sea of Oman. The authors combine Argo climatologies with high-resolution underwater glider observations to investigate the relative roles of isopycnal and diapycnal processes in modifying mode water volume and properties. The methodological framework, based on σ–τ coordinates, is innovative and provides new insight into how mesoscale eddies influence transformation rates.

I commend the authors for the clarity of their writing, the thoroughness of their analysis, and the careful integration of climatological and glider datasets. The paper convincingly demonstrates the added value of high-resolution glider observations for capturing episodic and small-scale processes that are missed in climatologies. The conclusions about eddy-driven intensification of both diapycnal and isopycnal transformations are compelling and make a valuable contribution to our understanding of mode water variability.

Overall, this is an excellent paper that makes a valuable contribution to the field. I recommend publication after the authors consider the following specific and technical comments.

- Joe Gradone

Specific Comments

Line 10: The second sentence of the abstract is a bit of a beast to read. I only became oriented once making it to the end where you state “deeper oxygen minimum zone”. I suggest moving the word “deeper” to the first mention of the oxygen minimum zone and then consider breaking this sentence up into two sentences.

Line 13-14: Initially, when I read the abstract, I was questioning how you could do this analysis on a 3-day temporal scale with a monthly climatology. The use of glider data in the analysis is clear in the main paper. I suggest maybe something like “higher resolution underwater glider observations” to distinguish the difference.

Line 81: Observations projected onto an orange line, not a blue line, correct?

Line 82: Is 2 km horizontally not a bit too fine for glider data?

Figure 1e: I recognize there is a lot of information on this plot but as someone who is colorblind, I cannot fully understand what is going on. The red dotted line is difficult to see and the white and pink lines blend together.

Line 184: Text says Figure 1e-g, but those subplots do not exist in Figure #1

Line 186: Define what mintier means here, not necessarily standard oceanographic knowledge. You define it well on line 201, so just consider some language to that effect here.

Figure 5: If this a pain, don’t sweat it, minor comment here. It would help to further orient the reader if you could make panels c, f, and i have the 24.5 isopycnal surface approximately in line with the depth where the hatching stops in the corresponding plots to the left.

Figure 5 cont.: I cannot tell the difference between the colored bars for “diapycnal”, “isopycnal”, and “exchange” in panels c, f, and i.

Figure 5 cont.: Helpful for the reader if you could put either a title or a small line of text, sort of like a legend, showing j-l correspond to diapycnal, isopycnal, and exchange, though the change in colors will also likely help this a ton.

Lines 316: Since the exchange term is computed as a residual, uncertainties in isopycnal and diapycnal terms will propagate directly into this estimate. Could you expand on how robust this separation between mixing and advective exchange is, and whether the relative magnitudes may be sensitive to error?

Line 365: Consider rewording/expanding to include a more general term, such as tracers. Maybe adopt the wording from line 398-399.

Technical Comments

Line 84: I would expect a 6 km running mean to filter out submesoscale variability. With the Rossby radius of deformation at this latitude (O) 20 km, can you comment on whether this reduces your ability to resolve the lower end of the mesoscale as well?

Line 87: An equation would be nice for both EKE calculations.

Line 88: Can you elaborate/clarify on what you mean re: “anomalies of the dive-averaged currents derived from the glider flight model”? Anomaly relative to what?

Line 100: A 200 km buffer from the across-Gulf transect for remapping seems very wide.

Line 122: The spice coordinate captures the isopycnal change more so than using potential density as a coordinate, no? Consider rewording this sentence.

Line 190: I am a little confused at how the thinning of mode waters results in a densification, but the signs of both the isopycnal and diapycnal transformation are negative (Line 192-193), implying a reduction in density.

Timescale of transformation of mode water section: I found the inclusion of both the climatological analysis and the higher resolution glider data on the same plots in Figure 2 to be a lot to unpack. Similarly, while I think the title of this section is a nice description, the first paragraph could use some additional language to highlight the time period it refers to. Similar to how the second paragraph highlights how the glider data allows for a higher resolution analysis. I don’t necessarily think the two paragraphs warrant their own section, but the differences in the findings are noteworthy enough to warrant additional descriptive text, at a minimum. Initially, I was going to suggest breaking Figure 2 up into two different figures, but I do find the comparison to the climatology to be helpful. The additional text in the results section will likely make the figure more digestible.

Line 368: While I understand a large aspect of the importance of Arabian Sea mode waters is their influence on subsurface oxygen concentration, I find the discussion around your results in the context of prior oxygen-focused literature to be too direct, as it does not actually utilize any oxygen data in your analysis. Simply, the last sentence of the first paragraph in the Discussion section can either be reworded or expanded to better reflect which aspect of Jutras et al. (2025)’s study your results expand. Then, more explicitly, how one might infer the resulting changes/implications in oxygen concentration from your findings. It is clear how your findings are focused on shorter timescale changes in mode waters, but I find this important paragraph in need of larger clarification.

General comments

This study uses a water mass transformation framework to investigate drivers of mode water volume change in the Sea of Oman. The variables used to define water masses are potential density and spice which allows the mode water volume budget to be decomposed into isopycnal transformation, diapycnal transformation and an exchange flux across the boundary of the region considered. The methods are applied to a dataset derived from ARGO floats to produce a climatology, and data from a high resolution glider, with the aim of investigatingdrivers of volume changes on shorter timescales. The water mass transformation methods used in this study have not previously been applied to higher temporal resolution data making this an important study for people who may wish to carry out similar analysis in the future.

The key findings indicate that the climatology produced from ARGO floats smooth out mode water volume changes on shorter timescales. Specifically, the presence of mesoscale eddies greatly enhances isopycnal transformation, which is then followed by diapycnal transformation, over time periods shorter than a week. Such periods of high variability are not captured in the climatology produced from the ARGO data. The need for higher resolution sampling is highlighted so that shorter periods of high variability in volume changes of mode water, particularly due to the presence of mesoscale eddies, are captured. This is important both for understanding what is happening the ocean, as well as the parametrisation of such processes in models.

Overall this is a high quality and well written study that I think the community will benefit from provided the comments below (see attached pdf) are addressed with a particular focus on improving the explanation of the water mass transformation framework in section 2.2.

Josef Bisits

This study employs glider transect observations from the Sea of Oman to quantify diapycnal and isopycnal mixing within the mode water layer across multiple timescales. The authors compare these estimates with monthly climatologies derived from Argo float data, demonstrating the limitations of coarser temporal resolution in capturing mixing variability. Their analysis underscores the need for additional glider-based field campaigns and direct turbulence measurements. The higher-resolution glider observations provide a more complete characterization of mixing processes under both eddy and non-eddy conditions, revealing that 40–60% of transformation variability is obscured by climatological averaging.

The novelty of this work lies in its use of high-frequency observational data to estimate mode water transformation rates, offering an observational perspective that complements traditional climatological approaches. I recommend this manuscript for publication. It presents a rigorous and well-articulated analysis that advances understanding of mode water transformation processes and remains accessible to readers less familiar with water mass transformation frameworks.

L44: What is the volume, what is the residence time? Provide relevant values for quick mental reference for readers.

L48-50: What does respiration within the water mass mean? Can you be more explicit; for ex., does respiration in this context mean physical transport of the MW? If so, how does transport within the WM lead to oxygen changes if the WM is defined to be a homogenous parcel?

L53-55: If you can't provide explicit values for volume and residence time, then in that first sentence maybe quickly mention the poorly constrained nature of that info.

L60: Can you elaborate on why you chose potential density as your coordinate? I don't know what "natural" means here. You explain spice well in L63, please apply this level of explanation for why you chose sigma as your other coordinate - why not neutral density?

L69: Strong motivation for this paper!

L73: Great list of questions, organized!

L82: typo: "at"

Fig 1a: Grey dashed line that float data are projected onto...does that mean farthest points on the map are also projected onto that line? The farther ends have little to no float data, and some cross shelf from 100-1000m, is it representative of the space (in x,y and z) MW would expect to occupy?

Fig 1d: stability of upper 100m highly variant esp during the transition from spring to summer. Flips sign sometime in Feb/Mar. What determines the shape of that seasonal spiral (when tracking the vertices of the thermohaline stability)?

Fig1e: Grey lines are very hard to discern, please consider a different color that will pop out from the noisy background (cyan?). Can you tell from this view of the chances the MW will be subducted or mixed back up into the surface? Perhaps the time of year indicates the likelihood skewed towards mixing with deeper water masses?

L122: Can you say the information succinctly instead of saying the rest of this sentence? 

L129: why formation and not transformation? it is the sum of formation and destruction (i.e. transformation). Later in L131 you say it's the convergence/divergence represented by the sum, so to also consider destruction/divergence it is more apt to say transformation.

L134: What about the southeast part?

L138: good summary statement

Eq1.1: (looking for clarification here) Sum of (sigma bins x cumulative product of spice bins x sigma velocity)?

L151: what assumptions?

L162: Do you mean that you used ERA5 temp/salt data to find isotherms/isohalines that outcropped and used those values to identify the classes on your sigma-tau plot? If so, can you say that to be clear?

L184: There are no panels for Figure 1 (f) and (g)

L185: Reference Figure 2 in this sentence.

L195: cite please

L200: typos - 2f; "transf."

Fig2: (a) and (b) order should be switched in this figure along with the corresponding changes in text.

Fig2e: "Denser" "lighter" should be inside the panel, it is visually busy/confusing the way it is currently placed. Same for "spicier" "mintier"

Fig 2f: Make sure the colors chosen for the lines are accessible to readers with color vision deficiencies

L220: Can you explain why you integrated over spice class for isopycnal transformation and potential density for diapycnal transformation? This goes back to my comment in L60

L234-241: Very cool calculation to justify high sampling frequency!

L246: Figure 1a used gray for argo climatology and orange for glider - i suggest flipping the colors here (or in fig 1) to be consistent with the colors representing which dataset

L283: spell it out since this is the first mentioning in captions

L284: The small yellow diamond is hard to see, can you choose a different color (like, cyan or hot pink).

L285: typo

L295: Paragraph explanation of fig 5 should come before the referencing of fig 5. Before L278.

Fig6: Perhaps this figure would be helpful to the reader before the other figs. consider placing this schematic as your fig 1 or 2.