the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Jan 2024
Natural marine bromoform emissions in the fully coupled ocean-atmosphere-model NorESM2
Abstract. Oceanic bromoform (CHBr3) is an important precursor of atmospheric bromine. Although highly relevant for the future halogen burden and ozone layer in the stratosphere, the global CHBr3 production in the ocean and its emissions are still poorly constrained in observations and are mostly neglected in climate models. Here, we newly implement marine CHBr3 in the state-of-the-art Norwegian Earth System Model (NorESM2) with fully coupled ocean-sea-ice-atmosphere biogeochemistry interactions. Our results are validated with oceanic and atmospheric observations from the HalOcAt (Halocarbons in the Ocean and Atmosphere) data base. The simulated mean oceanic concentrations (6.61±3.43 pmol L-1) are in good agreement with observations in open ocean regions (5.02±4.50 pmol L-1), while the mean atmospheric mixing ratios (0.76±0.39 ppt) are lower than observed but within the range of uncertainty (1.45±1.11 ppt). The NorESM2 ocean emissions of CHBr3 (214 Gg yr-1) are in the range of or higher than previously published estimates from bottom-up approaches but lower than estimates from top-down approaches. Annual mean emissions are mostly positive (sea-to-air), driven by oceanic concentrations, sea surface temperature and wind speed, dependent on season and location. During low-productivity winter seasons, model results imply some oceanic regions in high latitudes as sinks of atmospheric CHBr3, because of its elevated atmospheric mixing ratios. We further demonstrate that key drivers for the oceanic and atmospheric CHBr3 variability are spatially heterogeneous. In the tropical West Pacific, which is a hot spot for oceanic bromine delivery to the stratosphere, wind speed is the main driver for CHBr3 emissions on annual basis. In the North Atlantic as well as in the Southern Ocean region the atmospheric and oceanic CHBr3 variabilities are interacting during most of the seasons except for the winter months where sea surface temperature is the main driver. Our study provides improved process understanding of the biogeochemical cycling of CHBr3 and more reliable natural emission estimates especially on seasonal and spatial scales compared to previously published model estimates.
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Status: final response (author comments only)
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RC1: 'Comment on esd-2024-3', Anonymous Referee #1, 01 Mar 2024
Booge et al. presented a modeling study of bottom-up emission estimates for marine bromoform using a fully coupled ocean-atmosphere Norwegian Earth System Model, NorESM2. I think this is well done effort and it is very nice to see a comprehensive new bromoform emission estimate from a fully coupled ocean-atmosphere ESM. This study makes a great addition to the existing bromoform emission estimates, both bottom-up and top-down, and with further progress into the new era of a changing climate system. I support this paper to be accepted for publication in ESD, but I do have a few comments that should be addressed before the paper is published.
- Page 7, L199-213. I think it would be more helpful to the readers if you can use a simple schematic diagram to illustrate these set of equations 16-18 that balance the oceanic, atmospheric concentrations, production, and flux. These terms are all inter-linked and the equations are practically identical, except the subscripts. The current way of trying to explain the relationships between these terms using just equations and text is not an optimal way, in my view.
- Section 3.2, L257-273. It is very distracting to read through all these mean, 25th, 75th percentiles, min and max. It also makes things harder when I want to compare the numerical values between observations and model output. I would suggest that you use 25th &75th values as subscript & superscript for the mean values. If you really want to include the min and max, you can add them in the same way (sub & sup) with in parenthesis.
- Data availability and open data policy. I clicked on the link to https://halocat.geomar.de. It does not seem to me that these data are publicly available. The “click to join” link seemed to only let you submit an observation dataset, but nowhere on this page allows one to get access to data or even register to get an account to get access to data. This clearly does not meet open data policy that every journal is trying to abide by!
- L515-518. I fully agree. It would be very interesting to see if you can use NorESM2 in a future climate and see how winds, SSTs, and the ocean-atmosphere balance change CHBr3 emissions. I look forward to seeing future studies from the authors on this topic.
Minor comments:
- Maybe it is more accurate to say annual mean fluxes, instead of emissions. When it is emission, it implies that it must be from ocean to atmosphere. Sinks is the corresponding term when flux values are negative, therefore from atmosphere to ocean.
- Just say “winter”, instead of “winter seasons”. Short and adequate.
- This is not a correct statement. The most important organic compound for atmospheric bromine is CH3Br, not CHBr3. But you can say it is “one of the most important …”
- L33-34, you already said tropics at the beginning, you don’t need to say “tropical” in the second half.
- L101-104, you need to describe what each term is in Eqn (2). I couldn’t find descriptions of Si(OH)4 and KSi(OH)4phy.
- I think you may be confused in terms of when to use “e.g.”.The Latin abbreviation for “for example” is e.g., which stands for “exempli gratia.”. For instance, L297-298 “Averaging data over time or space leads to lower values (e.g. gas emissions)” is not a correct way to use e.g. Gas emissions is not an example of lower values. L305, for example, (e.g. North and South Pacific) should be moved to after surface oceans.
Besides, “e.g.” should always be italic and with a “,” after it. Make sure you look through all the e.g. in the text and fix when not appropriate.
- L324-327. Move North Atlantic, tropical West Pacific, and Southern Ocean to the end of the first sentence.
- Change but also -> and
- I think you can simply say “winter emissions” here, instead of “the emissions from the ocean to the atmosphere during winter seasons”. The current phrase is long and unnecessary. Emissions only occur from ocean to the atmosphere in this context.
Citation: https://doi.org/10.5194/esd-2024-3-RC1 -
AC1: 'Reply on RC1', Dennis Booge, 03 Apr 2024
The comment was uploaded in the form of a supplement: https://esd.copernicus.org/preprints/esd-2024-3/esd-2024-3-AC1-supplement.pdf
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RC2: 'Comment on esd-2024-3', Anonymous Referee #2, 02 Mar 2024
The manuscript by Booge et al. presents the first coupled ocean-atmosphere model in which bromoform is dynamically modelled in both the ocean and the atmosphere, opposite to previous studies in which prescribed concentrations in at least one compartment were used. The authors compare their modelled concentrations with available observations and assess environmental drivers for natural bromoform emissions from the ocean. They conclude that the remaining discrepancy between top-down and bottom up emission estimates likely result from coastal fluxes.
The paper is an important contribution to the field and will likely have a large impact by presenting the first fully-coupled dynamic model for natural bromoform emissions from the ocean. The study therefore fits the scope of the journal and I recommend it for publication, after some minor comments have been addressed.
Main comments:
Concerning the comparison between model and data: I think the authors could make more use of the potential of the model to guide further research on the marine cycling of bromoform by discussing remaining residuals. The discussion of errors ends with “discrepancies between model results and observations also point to missing process understanding, which helps to improve our understanding of the biogeochemical cycling of CHBr3.” To which missing processes does the spatial and temporal distribution of remaining residuals point to? If modelled ocean concentrations are systematically too high everywhere in the ocean (Fig. 3a), are rather production rates too high or consumption rates too low (i.e. can the spatial and temporal distribution of residuals help to narrow this down)? I suggest to make the error and residual analysis more quantitative by using error metrics or 1:1 scatter plots and systematically discuss which processes may be missing, need an improved parameterization in the model or may need further experimental studies to describe rates and their dependencies.
Driving factors of bromoform on regional and temporal scales:
- This section is very long but remains rather descriptive and partly hard to read due to the data listed in the text. While shortening the descriptive part by transferring some data to a table to enhance readability, the discussion could be more streamlined and point to overall findings and implications from this analysis.
- Some parts of the section about the model climatology already discuss the driver of seasonal variation of CHBr3 concentrations, e.g. in relation to higher biological production (l. 223) or atmospheric mixing ratios (l. 235). Later on, biological production is not discussed in the section about drivers. It would make sense to bundle discussion about seasonality in one place.
Global emission estimates:
- Is the higher emission estimate mainly the result of the larger production rate (which is 2.38 times larger, resulting in 2.82 times larger emissions than Stemmler et al., 2015? ), as written in l. 436ff? The discussion could be more specific here.
Minor comments:
Title of section 2.5: suggestion “Calculation of drivers influencing bromoform concentrations and emissions”
l. 246: suggestion: “…although with a lower magnitude.”
Fig. 5. Please change x-axis label, I assume it should be month of year, not day of year?
Fig. 6. Isn’t panel a and d as well as c and f transporting the same information (just x and y axis flipped)? I assume that this is the case because ocean concentrations correlate to (i.e. "drive") atmospheric mixing ratios and vice versa, but it is a bit confusing to show the same data and relationship twice.
l. 442: something is missing in this sentence. Account for 44% of what?
Citation: https://doi.org/10.5194/esd-2024-3-RC2 -
AC2: 'Reply on RC2', Dennis Booge, 03 Apr 2024
The comment was uploaded in the form of a supplement: https://esd.copernicus.org/preprints/esd-2024-3/esd-2024-3-AC2-supplement.pdf
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AC2: 'Reply on RC2', Dennis Booge, 03 Apr 2024
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