the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
From small scale variability to mesoscale stability in surface ocean pH: implications for air-sea CO2 equilibration
Abstract. One important aspect of understanding ocean acidification is the nature and drivers of pH variability in surface waters on smaller spatial (i.e., areas up to 100 km2) and temporal (i.e., days) scales. However, there has been a lack of high-quality pH data at sufficiently high resolution. Here, we describe a simple optical system for continuous high-resolution surface seawater pH measurements. The system includes a PyroScience pH optode placed in a flow-through cell directly connected to the underway supply of a ship through which near-surface seawater is constantly pumped. Seawater pH is measured at a rate of 2 to 4 measurements min-1 and is cross-calibrated using discrete carbonate system observations (total alkalinity, dissolved inorganic carbon and nutrients). This setup was used during two research cruises in different oceanographic conditions: the North Atlantic Ocean (December–January 2020) and the South Pacific Ocean (February–April 2022). Our findings reveal fine-scale fluctuations in surface seawater pH across the North Atlantic and South Pacific Oceans. While temperature is a significant abiotic factor driving these variations, it does not account for all observed changes. Instead, our results highlight the interplay between temperature, biological activity, and water masses on pH. Notably, the variability differed between the two regions, suggesting differences in the dominant factors influencing pH. In the South Pacific, biological processes appeared to be mostly responsible for pH variability, while in the North Atlantic, additional abiotic and biotic factors complicated the correlation between expected and observed pH changes. Although surface seawater pH exhibited fine-scale variations, it remained relatively stable over a 24-hour cycle due to reequilibration with atmospheric CO2. Thus, for the regions and time periods studied, ocean basin-scale analyses based on discrete samples collected during traditional research cruise transects would still capture the necessary variability for global CO2 cycle assessments and their implications.
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CC1: 'Comment on egusphere-2024-2853', Christopher Sabine, 25 Nov 2024
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General Comments:
This is a well written and well documented manuscript, but I am concerned about the accuracy of the measurements and the robustness of the conclusions. Based on the final corrected pH plots in figure 3, it looks like the pH changes along the two transects were very minimal. The authors calculate that the largest influence on pH over a 24-hour cycle is temperature, with an occasional hint of a biological signal. This really isn’t a surprise. These variations are occurring in both time and space, so it is impossible to quantitatively separate the effects. The authors conclude, “…although the processes responsible for these pH variations are well-understood, high-resolution data highlight the challenge of identifying a dominant factor at the fine-scale due to their complex interplay.” This makes me question what is the point of this manuscript? Perhaps the authors can do a better job of explaining what is new and novel about this work.
Specific Comments:
Lines 256-257: How do the authors define unreasonable drift patterns? This approach sounds very subjective.
Lines 259-263: The authors are correcting the measured pH values to pH calculated from TA and DIC, but how do they know the calculated values are correct? Which constants were used for the calculations? Is there no direct measurement of pH to validate the corrections? What about the two-point calibrations described in the methods? Were these calibrations not helpful? How frequently were they done?
Figure 3: Some of the pH changes are very large and the final pH curves look nothing like the raw data. If all the calculated pH values are used to adjust the underway pH measurements, then what confidence do we have that the values in between the calibrations are correct? Are there any independent pH measurements that were not used for calibration that we can use to assess accuracy?
Line 265-279: It seems a bit circular to use TA to adjust the pH values, then turn around and use TA together with the pH to calculate the other parameters. How do the Lee et al. TA values compare to the measured values? Are these uncertainties smaller than if the authors simply took all the measured TA and DIC values to calculate the other carbon parameters?
Line 382: This is not a traditional use of the term water mass. One does not normally think of water masses as surface features because external forcing (warming/cooling, precipitation/evaporation, etc.) can make water properties quite variable, compared to traditional subsurface water masses that have stable properties that can be defined and tracked as they move into the ocean interior. I understand what the authors are trying to say, but I think a different term for waters with different properties needs to be used.
Line 392: This section is focused on the influence of T and S on pH, which seem to have signals that are less than 0.01. I am wondering how robust these signals are if the raw pH values had to be corrected by ~0.4 units (fig 3) and the uncertainties in the final values are around +/-0.01 (fig 4 and 5). How do the authors know these are signals and not just noise that they are interpreting?
Line 414: I do not understand this statement about the waters having lower thermal inertia. What do the authors mean? Lower than what? Water has a low thermal inertia compared to the air, but the sentence is trying to explain why there is a diurnal temperature signal in the surface water. The deeper waters do not have a higher heat capacity, they are just removed from the forcing.
Line 635-637: This sentence seems to convey the essence of this manuscript: However, although the processes responsible for these pH variations are well-understood, high-resolution data highlight the challenge of identifying a dominant factor at the fine-scale due to their complex interplay. What is the take home message that you are trying to convey? It sounds like there isn’t much point in doing these high-resolution measurements.
Citation: https://doi.org/10.5194/egusphere-2024-2853-CC1
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