the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Disentangling the impact of air-sea interaction and boundary layer cloud formation on stable water isotope signals in the warm sector of a Southern Ocean cyclone
- 1Institute for Atmospheric and Climate Science, ETH Zürich, Zurich, Switzerland
- 2Geophysical Institute, University of Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
- 1Institute for Atmospheric and Climate Science, ETH Zürich, Zurich, Switzerland
- 2Geophysical Institute, University of Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
Abstract. Stable water isotopes in marine boundary layer water vapour are strongly influenced by the strength of air-sea fluxes. Air-sea fluxes in the extratropics are modulated by the large-scale atmospheric flow, for instance by the advection of warm and moist air masses in the warm sector of extratropical cyclones. A distinct isotopic composition of the water vapour in the latter environment has been observed over the Southern Ocean during the 2016/17 Antarctic Circumnavigation Expedition (ACE). Most prominently, the secondary isotope variable deuterium excess (d = δ2H−8·δ18O) shows negative values in the cyclones’ warm sector. In this study, three mechanisms are proposed and evaluated to explain these observed negative d values. We present three single-process air parcel models, which simulate the evolution of δ2H, δ18O, d and specific humidity in an air parcel induced by decreasing ocean evaporation, dew deposition, and upstream cloud formation, respectively. Simulations with the isotope-enabled numerical weather prediction model COSMOiso , which have previously been validated using observations from the ACE campaign, are used to (i) validate the air parcel models, (ii) quantify the relevance of the three processes for stable water isotopes in the warm sector of the investigated extratropical cyclone, and (iii) study the extent of non-linear interactions between the different processes. This analysis shows that we are able to simulate the evolution of d during the air parcel’s transport in a realistic way with the mechanistic approach of using single-process air parcel models. Most importantly, we find that decreasing ocean evaporation, and dew deposition lead to the strongest d decrease in near-surface water vapour in the warm sector and that upstream cloud formation plays a minor role. By analysing COSMOiso backward trajectories we show that the persistent low d observed in the warm sector of extratropical cyclones are not a result of material conservation of low d. Instead, the latter Eulerian feature is sustained by the continuous production of low d values due to air-sea interactions in new air parcels entering the warm sector. These results improve our understanding of the relative importance of air-sea interaction and boundary layer cloud formation on the stable water isotope variability of near-surface marine boundary layer water vapour. To elucidate the role of hydrometeor-vapour interactions for the stable water isotope variability in the upper parts of the marine boundary layer, future studies should focus on high resolution vertical isotope profiles.
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Iris Thurnherr and Franziska Aemisegger
Status: final response (author comments only)
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RC1: 'Comment on acp-2022-12', Anonymous Referee #1, 24 Mar 2022
This is a well-written and comprehensive article that help understanding processes leading to negative water vapor d-excess observed in surface air during the ACE campaign, within the warm sector of an extra-tropical cyclone, south of South Africa.
The authors combine regional atmospheric modelling with water isotopes (COSMOiso simulation) together with 3 single-process air parcel models to understand the drivers of observed changes in water vapor isotopic composition.
They show that regions of low d-excess in surface water vapor are created by decreasing ocean evaporation and dew deposition at the ocean surface. Low water vapor d-excess close to the ocean surface is assessed to result from local air-sea interactions and to overwrite the advected d-excess signal.
I think this article allows better quantification and understanding of processes driving d-excess signal in near-surface ocean water vapor. In addition, the article structure guides the reader toward a good understanding of the authors’ conclusions. I found this article very pleasant to read, with adapted figures. Consequently, I recommend this article to be published with minors revisions detailed bellow.Minor comments
L37 : 2RVSMOW2.2 : typo? is the final .2 right?
L169 : « αe » is not described in the text (even if I agree it’s a standard notation)
L177 : « supplement Fig.S3 » cited first, why not S1 ?
Re-number all supplement figures.L177-178 : « The simulation is initialized with qa,0=5 g kg−1 (and, thus, hs=0.5 because qs=10.0 g kg−1 at 14°C), âq=10−3·(qs − qa), δ2Ha,0=−137 ‰ and δ18Oa,0=−19.5 ‰ »
Why this choice ?
How is chosen the âq factor 10−3? Does it have an influence on the results ?APMdew
L235-236 : « The simulation is initialised with hs=1.1, which means that qa,0=6.8 g kg−1, âq=8·10−4·(qs −qa), δ2Ha,0=−98 ‰, and δ18Oa,0=−13 ‰ »
Again, why this choice? End of APMevap ? (seems yes from Figure 4, but with different hs)
Why âq=8·10−4·(qs −qa) ?Figure 3.h : I was confused at the begining between (h) above the purple line and hs in gray, maybe it’s just me, it’s clear for me now.
APMray
L269-270 : « Ta,0=8°C (which gives qa,0=6.7gkg−1), âSST=1°C, δ18Oa,0 = −15.0‰ δ2Ha,0 = −98‰ »
Again, can you briefly explain why you choose these values ? (I can guess end of APMevap from Fig. 4)Figure 4 : This scheme highlights very well what you do in Section 3. Maybe you could move it at the beginning of Section 3 together with a small introduction of the APM and 3 example simulations presented after. It would help the reader to better understand the link between the 3 APMs, and also between the 3 examples (e.g. choice of start values in the examples).
Figure 5 : Use a continuous colormap for potential temperature, unless you can justify the threshold at 294 K to separate warm and cold sectors?
Is Θe the same as θe in the text ?
« The white contours show that warm temperature advection mask. » Add information of the definition of this mask, or refer to the text.L304 : « sharp gradients in THE » What is THE? TPE = θe ? or not?
L305 : Define θe in the text
Figure S1 / Figure S2 / hs in Figure S4: Rainbow-like colormaps are to be proscribed for continuous variables, use a continuous colormap instead.
https://www.climate-lab-book.ac.uk/2014/end-of-the-rainbow/
https://mycarta.wordpress.com/2012/10/14/the-rainbow-is-deadlong-live-the-rainbow-part-4-cie-lab-heated-body/L317 : « A good agreement of measured and simulated hs and qa can be seen (Fig. 6). » I cannot see qa in Fig. 6. Can you add air temperature in Fig. 6 too ?
L318-320 « The simulated precipitation compares well with the measurements except for the few hours around 00 UTC on 26 December 2016, during which enhanced precipitation is simulated, while no precipitation has been measured. »
Why focus on the 26 December 2016 00 UTC when model-observation differences are way larger from 26/12 12h ?
Model mostly underestimate precipitation, I don’t understand the focus on the very show period when it is the opposite?
I would say that the first peak is well represented but the second peak is off (lower precipitation, and too late ?)L340 Is Θe the same as above, i.e. θe, i.e. equivalent potential temperature at 900 hPa ?
L354-356 « Furthermore, the back-trajectories arriving in region CF, were located in region WF 48 h before arrival also coming from a region of high d with values above 20 ‰ (Fig.7a and supplement Fig. S4). »
For CF, Fig. 7a shows low d 48h before as in Fig.S4. In Fig. S4, high d for CF is around 72h before? -
RC2: 'Comment on acp-2022-12', Anonymous Referee #2, 11 Apr 2022
Thurnherr and Aemisegger provide a detailed, well-written manuscript that seeks to investigate the process-level causes of low vapor d-excess observed during the 2016/17 Antarctic Circumnavigation Expedition. They apply three single-process models representing impacts on isotope ratios from (a) ocean evaporation, (b) dew formation and deposition, and (c) upwind distillation, and demonstrate that these three processes follow diagnostic pathways in d18O/d-excess space. They then also compare the results from their process models to a regional NWP model simulation including isotopes to validate these models. Taken together, they suggest a larger than previously appreciated role for dew formation over the ocean for altering the d-excess of near-surface water vapor, particularly in the warm sector of extratropical cyclones.
Their analysis is rather detailed, and the process modeling provides interesting insights into the evolution of d-excess in near-surface water vapor. This paper represents a nice contribution, and only have a handful of suggestions for revision below.
Line-by-line notes
- L. 36 – there appears to be an extra ‘2’ in the denominator for R here.
- L. 44-46: might be good to cite a few of the observational studies that dew formation is a non-equilibrium process (e.g., Deshpande et al., 2013; Wen et al., 2012), since condensation processes are still (often) thought of as equilibrium to first order.
- L. 61-62: d can also change purely due to equilibrium effects when the Rayleigh f is very low (e.g., Bony et al., 2008; Dütsch et al., 2017)
- L. 104: which laser spectrometer was used and how was it calibrated?
- L. 115: could the authors clarify what explicit treatment of deep convection means (i.e., is this model non-hydrostatic)?
- L. 136-137: These seem to be fairly unusual choices for the isotope ratio of the ocean, could the authors clarify how these values were chosen? This is of particular note for this manuscript as it could be in part responsible for producing evaporation fluxes with a lower d-excess than might be expected. For example, using values for SMOW (δ18O = 0‰, δ2H = 0‰), the water undergoing evaporation has a d-excess of 0‰, but an ocean initial condition of (δ18O = 1‰, δ2H = 1‰) has a d-excess of -7‰, which would seem to bring down the d-excess of the evaporative flux by ~7‰ as well.
- L. 169: there is often a lot of confusion regarding αk, often stemming from whether it is defined based on Di/D (and hence, αk < 1) or D/Di (hence αk > 1) (e.g., Benetti et al., 2014), where Di is the diffusivity of the isotopologue with a substituted atom (2H or 18O). Obviously, both can be correct depending on how the equations are cast, but it may be worth specifying that you are referring to an αk value based on Di/D in your work, since the alternative definition is also widely used.
- L. 235: I think the supplemental figures are not numbered in text in the order they appear.
- L. 251-252: I think this sentence could be a bit more clear – clearly rainout could play a role in altering SWIs, but it’s not clear why you might expect to see these at the ocean-water interface if there has been substantial adiabatic lifting (presumably along isentropes, cf. (Bailey et al., 2019)?). Presumably this would be through mixing and/or subsidence, but it’s not made clear here.
- L. 304 – is THE a misrendered θe? (Also, there appears to be some inconsistency in case: a capital Θ is used in Fig. 5 and L. 340 instead of the lower-case θ used elsewhere)
- L. 437-441 – this is an interesting point! In addition to the mixing process here, I wonder if the more turbulent coupling between the surface and the near-surface atmosphere could have the effect of altering the ‘effective’ kinetic fractionation factor here as well and alter d independent of mixing, for example by changing the value of the exponent used on the ratio of diffusivities (eq. 5 in (Pfahl & Wernli, 2009), also (e.g., Gat, 1996; Mathieu & Bariac, 1996; Merlivat & Jouzel, 1979; Riley et al., 2002)
References
Bailey, A., Singh, H. K. A., & Nusbaumer, J. (2019). Evaluating a Moist Isentropic Framework for Poleward Moisture Transport: Implications for Water Isotopes Over Antarctica. Geophysical Research Letters, 46(13), 7819–7827. https://doi.org/10.1029/2019GL082965
Benetti, M., Reverdin, G., Pierre, C., Merlivat, L., Risi, C., Steen-Larsen, H. C., & Vimeux, F. (2014). Deuterium excess in marine water vapor: Dependency on relative humidity and surface wind speed during evaporation. Journal of Geophysical Research: Atmospheres, 119(2), 584–593. https://doi.org/10.1002/2013JD020535
Bony, S., Risi, C., & Vimeux, F. (2008). Influence of convective processes on the isotopic composition (δ18O and δD) of precipitation and water vapor in the tropics: 1. Radiative-convective equilibrium and Tropical Ocean–Global Atmosphere–Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE) simulations. Journal of Geophysical Research, 113(D19). https://doi.org/10.1029/2008JD009942
Deshpande, R., Maurya, A., Kumar, B., Sarkar, A., & Gupta, S. (2013). Kinetic fractionation of water isotopes during liquid condensation under super-saturated condition. Geochimica et Cosmochimica Acta, 100, 60–72.
Dütsch, M., Pfahl, S., & Sodemann, H. (2017). The Impact of Nonequilibrium and Equilibrium Fractionation on Two Different Deuterium Excess Definitions. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1002/2017JD027085
Gat, J. R. (1996). Oxygen and hydrogen isotopes in the hydrologic cycle. Annual Review of Earth and Planetary Sciences, 24, 225–62.
Mathieu, R., & Bariac, T. (1996). A numerical model for the simulation of stable isotope profiles in drying soils. Journal of Geophysical Research: Atmospheres, 101(D7), 12685–12696. https://doi.org/10.1029/96JD00223
Merlivat, L., & Jouzel, J. (1979). Global climatic interpretation of the deuterium-oxygen 18 relationship for precipitation. Journal of Geophysical Research, 84(C8), 5029. https://doi.org/10.1029/JC084iC08p05029
Pfahl, S., & Wernli, H. (2009). Lagrangian simulations of stable isotopes in water vapor: An evaluation of nonequilibrium fractionation in the Craig-Gordon model. Journal of Geophysical Research, 114(D20). https://doi.org/10.1029/2009JD012054
Riley, W. J., Still, C. J., Torn, M. S., & Berry, J. A. (2002). A mechanistic model of H218O and C18OO fluxes between ecosystems and the atmosphere: Model description and sensitivity analyses. Global Biogeochemical Cycles, 16(4), 42-1-42–14. https://doi.org/10.1029/2002GB001878
Wen, X.-F., Lee, X., Sun, X.-M., Wang, J.-L., Hu, Z.-M., Li, S.-G., & Yu, G.-R. (2012). Dew water isotopic ratios and their relationships to ecosystem water pools and fluxes in a cropland and a grassland in China. Oecologia,168(2), 549–561.
Iris Thurnherr and Franziska Aemisegger
Iris Thurnherr and Franziska Aemisegger
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