the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 13 Jan 2025
Global air-sea heat and freshwater fluxes constrained by ocean observations
Abstract. A substantial portion of the transport of heat and freshwater in the climate system occurs through the ocean. Heat and fresh water enter the ocean as air-sea fluxes, which are typically estimated based on observationally constrained ‘reanalyses’ of the atmosphere. However, these estimates are uncertain, with broad differences in space and time between different products, and do not align with estimates of integrated ocean temperature and salinity. As a result, inferred global heat and freshwater transport, including transport trends, remain unclear. In this work, we use a novel water mass-based inverse modelling method, the Optimal Transformation Method (OTM), to reconcile reanalysis-based changes in surface heat and freshwater fluxes with changes in observed ocean temperature and salinity. We present estimates of air-sea surface fluxes since the 1970s, derived from reanalysis products ERA5, JRA-55 and COREv2, which are adjusted to be physically consistent with observation-based 3D ocean temperature and salinity products EN4 and IAP. OTM adjusts air-sea surface fluxes in a consistent manner, thereby also enabling estimation of meridional heat and freshwater transports. Inferred mean meridional heat transport is relatively consistent, and aligns with independent ocean transport observations and the spread of estimates from historical reconstructions from the 6th Climate Model Intercomparison Project. Mean freshwater transport and trends in both heat and freshwater transport are less consistent. Either a narrowing of the range of estimates provided by reanalyses and/or additional constraints to OTM (in addition to the thermodynamic constraints currently provided) are therefore still needed.
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RC1: 'Comment on essd-2024-545', Sjoerd Groeskamp, 14 Feb 2025
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Review of “Global air-sea heat and freshwater fluxes constrained by ocean Observations”
Authors: Sohail and Zika
Review by Sjoerd Groeskamp
Recommendation: Major Revisions.
This paper uses a previously developed inverse method (by the same authors), called the Optimal Transformation Method (OTM) to estimate the correction needed for air-sea freshwater and heatfluxes, to have an improved global balance and related air-sea flux products. The method uses fundamental ocean thermodynamical constraints that are available from readily available observations of T&S and air-sea fluxes. Given a beginning and end-state of the ocean volume in S&T space, and air-sea T&S fluxes, they calculate the required mixing between water masses. The residual is then used to calculate the required adaptation of surface fluxes to obtain the final water masses from the initial water masses. The inversion is done in T&S coordinates and translated back into geographical coordinates. The method is applied to different combination of gridded hydrography’s and air-sea flux products. This study is used to understand if the method performs as expected, to see where adaptations need to be made to surface fluxes and to understand how this impacts meridional heat transport.
I believe this work is of interest because air-sea fluxes are notoriously hard to estimate due to a lack of observational constraints. This method aims to further constraint estimates of air-sea fluxes (where we could otherwise not), using thermodynamical constraints that can be applied to observation of the ocean state and have implications for the overlaying air-se fluxes. In that sense, I welcome the line of work by these authors, and I think this paper is a worthwhile continuation of that work that intends to improve air-sea flux estimates and study how, why and where they lack information. All in all, I thus recommend publication of this work, but only after some extra work related to both improving the method, discussing or assessing uncertainty of the method and related to clarifying exactly what happens. These improvements are also needed for reproducibility. In addition, a better explanation is needed what the advance is of this paper compared to previous work by the authors. Below are my specific comments that include specification of the more general comments above.
Comments related to the method
It is not exactly clear what the advances are compared to Zika and Sohail 2023. This should be made clear.
Eq. 6 – Can you specify what is meant with adjacent regions? Are they touching each other? These are specifically horizontal right?
What about “adjacent water masses” in the vertical. You don’t want surface waters to mix with bottom waters directly and skip the water in between. Is there a constraint applied for this?
L93 - It is clearly discussed in the manuscript that the weighing factor influences the result. However, there is no quantification how it does so. It is discussed that, for example, consistency in adjustment in the SO can be due to this weighing factor. This is unfortunate, because I thought the consistency in adjustment would be exactly what would provide a solid argument for the use of this method. Is there a way to quantify the impact of modelers choices of the weighing factor and teas out the useful results from modeling choices?
The current choice of the weighing factors seems a clever one, but perhaps a broader discussion of what its impacts are is also helpful. Imagine doing no weighing for example.
More general than the weighing factor, the result of an inverse method can depend strongly on modelers choices and constraints. For example, that of the BSP and a-priori knowledge. Some of this is studies by having multiple products, but a discussion and possibly quantification of the influence of the modelers choices on the result can be improved and is maybe essential for interpreting the results.
Section 2 - The result of gij will be sensitive to weighing, BSP and given constraints. But also, to input datasets. This will result in imperfect mixing between water masses and related gij and eventually changes in Q^adjust. I guess this comes back to the sensitivity question before. Because how does this influence the results?
How is shortwave radiation depth penetration included? Groeskamp and Iudicone 2018 showed it has a huge impact on Watermass transformation. This means that the vertical distribution of SWR changes the thermodynamic state of the ocean below the surface. This effect should be included in Qij and will impact which water masses (and how much) need to be mixed, and thus eventually the resulting gij and Q^adjust.
Other comments
L73 – What is BSP? Can you give a quick explanation? Is it based on equal mass partitioning or so?
Eq. (2)-(6) – As with Eq 6, it would be great if you can add one sentence behind each equation, what the constraint implies.
L90 - Space between Ai and
L100 and before and after - I had to go back and read Zika en Sohail 2023 to understand the OTM. Now in principle this is not a problem, but I guess some more explanation of what is going on would be really helpful for some readers. Also, in reading that paper and then going back to this paper, I was not 100% how this works. Am I correct that you first do an inversion with the given air-sea fluxes (Q^prior), which then provides gij. Then this gij is used to calculate Qij in Eq(1), from which Q^adjust is obtained as Q – Q^prior? Anyway, I think some clarification is warranted, especially as there is no Q^adjust (the thing you ultimately want to know) in your cost function.
Figure 9 and 10 are key figures, but it does not show how the adjustment improves the results. This is the key point of the paper and I think this figure should somehow show the improvements made with the OTM. Also, please highlight the zero line (thick black line or so).
L248 - figure 7e and f
Comments fig 7 and around - The goals is for the surface fluxes to be adjusted thermodynamically and such that they have smaller biases when integrated globally. If I’m correct, global warming requires 0.3W/m2 warming. Why not include this in the inversion as a constraint?
On that note, do the adjustments lead to lower globally integrated air-sea flux biases? Can you provide a number that shows the globally integrated results?
Fig 7 has changing y axis, which is somewhat misleading in the comparison. Maybe have a panel or SM-figure where all green lines are in one panel?
Figure 8 was really confusing to read. There are multiple things stacked on each other, but sometimes not. It is hard to compare the flux products to each other and it is hard to separate the basins. I think an alternative way should be found to present this information.
L-287 – two times adjusted
L375 – The inverse method is no longer novel I think, it seems there are several papers quoted using this.
Reading the conclusion, I realized I was not exactly sure how the adjustment to the air-sea fluxes is added over time. If you calculate the adjustment over, say 6 years, you linearly add it over that period? Is this done at all?
Citation: https://doi.org/10.5194/essd-2024-545-RC1
Data sets
Adjusted ERA5, COREv2 and JRA-55 products constrained by ocean observations Taimoor Sohail and Jan D. Zika https://doi.org/10.5281/zenodo.14004938
Model code and software
Adjusted ERA5, COREv2 and JRA-55 products constrained by ocean observations Taimoor Sohail and Jan D. Zika https://doi.org/10.5281/zenodo.14004938
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