the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 03 Jul 2024
Disentangling the chemistry and transport impacts of the Quasi-Biennial Oscillation on stratospheric ozone
Abstract. The quasi-biennial oscillation (QBO) in tropical winds perturbs stratospheric ozone throughout much of the atmosphere via changes in transport of ozone and other trace gases and via temperature changes that alter chemical processes. Here we separate the temperature-driven changes using the Department of Energy’s Energy Exascale Earth System Model version 2 (E3SMv2) with linearized stratospheric ozone chemistry. E3SM produces a natural QBO cycle in winds, temperature, and ozone. Our analysis defines climatological QBO patterns of ozone for the period 1979–2020 using both nonlinear principal component analysis and monthly composites centered on QBO phase shift. As a climate model, E3SM cannot predict the timing of the phase shift, but it does match these climatological patterns. We develop an offline version of our stratospheric chemistry module to calculate the steady-state response of ozone to temperature and overhead ozone perturbations, assuming that other chemical families involved in ozone chemistry remain fixed. We find a clear demarcation: ozone perturbations in the upper stratosphere (above 20-hPa) are predicted by the steady-state response of the ozone column to the temperature changes; while those in the lower stratosphere show no temperature response and are presumably driven by circulation changes. These results are important for diagnosing model-model differences in the QBO-ozone responses for climate projections.
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RC1: 'Comment on egusphere-2024-1927', Anonymous Referee #1, 29 Jul 2024
Review of “Disentangling the chemistry and transport impacts of the Quasi-Biennial Oscillation on stratospheric ozone” by Xie et al.
The authors derive a new QBO index. They then use observations and tailored versions of two global models to investigate the relative impacts of photochemistry and transport on the response of stratospheric ozone to the QBO.
Major comments:
- While it is certainly important to understand the processes that contribute to the response of ozone to the QBO, the question addressed in this paper is quite limited and the answer has been known for decades. The authors’ goal is to determine the relative roles of chemistry and transport. However, they do not address what chemistry (i.e., which reactions; what leads them to change with the QBO) and what transport (meridional or vertical advection, diffusion due to wave breaking) are responsible. Instead, their assumptions seem to be that all photochemical effects are caused by temperature-dependent rates of ozone loss and all transport is due to the vertical component of the transformed Eulerian mean circulation. Beyond this, the important cross-over possibilities (i.e., transport of one reactant affects the photochemistry of another that is differently affected by transport) seem not to have been considered.
- Using simplified, constrained, or nudged models can often be a valuable tool for probing causative mechanisms. However, this paper does not present a clear motivation for why these model constraints were used in the present case. Overall, the paper is lacking in motivation for the specific modeling experiments that were set up. What can we learn from these simulations that we would not learn from either a middle atmosphere chemical transport model or a GCM with interactive chemistry? Moreover, additional evidence is needed to show that processes omitted due to their assumptions, such as neglect of full Ox chemistry, are not important.
- As a related comment, the authors do not take advantage of the simplified and controlled nature of their simulations to perform additional testing of mechanisms. For example, the last paragraph of Section 5.3 speculates about which differences in the setup of the different models might account for differences in the results. Why not actually test these?
- The derivation of a new QBO index is interesting. I especially appreciate Figure 1a, which displays the temporal development nicely. I would have been interested to see how well this index is able to capture the QBO interruptions of 2016 and 2020. My concern about this index is that its description needs work. It appears in the figure captions as “0 is centered on the month when QBO transits from QBOe to QBOw (determined by when current QBO index<0 and next QBO index>0). The QBO phase is determined by 5S-5N average of the zonal wind.” It's confusing because of the mention of the month when the QBO transits as if there was a single transit month rather than a different month at each pressure. Please take care to use language that distinguishes between the QBO winds and the QBO index. Perhaps something like this would be clearer: “The x-axis is the QBO index, defined by Eq. (1).” Also, please label the axis, e.g. “QBO index”.
Additional comments
- Supplemental figures 2 and 4 are not mentioned in the text. Are they necessary or helpful for understanding the results?
- (l. 18-19) It is not clear what “phase shift” refers to nor why E3SM cannot predict it.
- (l. 33-34) “assigning the pattern of ozone perturbations over the QBO cycle to specific processes is not easy”: This gets at the gist of the issue raised by my first major concern. One reason that it is not easy is that no simple either/or assignment can capture the complexity.
- (l. 125-126) “The parameters for the convective GW momentum transport were tuned especially for this version”: Can you provide more details, such as a link where the tuning choices and parameters can be found? Some other users of this model might be interested.
- (l. 407-408) “this demonstrates the overall effectiveness of the nudging strategy” I would say “overall effectiveness” is too strong since the extratropical response is not well simulated.
- (l. 419-420) “The results shown here are important for diagnosing model-model and model-observation differences” Can you provide an example?
- (l. 447-448) “using interactive ozone or not in the simulation does not significantly alter the results for QBO simulations” This has not been shown. Also, I suggest you take care with the term “significantly”, which is best reserved for quantitative measures of statistical significance.
Citation: https://doi.org/10.5194/egusphere-2024-1927-RC1 -
RC2: 'Comment on egusphere-2024-1927', Anonymous Referee #2, 07 Aug 2024
General comments
The paper explores the chemistry and transport impact of the QBO on stratospheric ozone. They make use of climate model simulations as well as an offline ozone calculation to investigate the response of ozone to temperature and overhead ozone changes. They claim that ozone perturbations above 20hPa are predicted by the ozone column response to temperature whilst those below show no temperature response and are presumed to be driven by the circulation changes.
1) The motivation for the choice of methodology is not made clear in the paper. It is not apparent what is being gained by it. Far too many other uncertainties are being introduced by the methodology that lead to questions about the robustness of the results. The work makes use of two different climate models, EAMv2 and CESM2. These two models do not simply differ in one having a QBO, they will have different ozone climatologies. This makes it difficult to compare the experiment as interactive and non-interactive runs as the paper is trying to do. Furthermore, there are inconsistencies as to how ensembles are being used (different numbers for historical and future).
2) The new QBO index is being calculated using a complicated method. It would be good to see more validation of this being performed. How related is this new index to the underlying dynamical variability? On line 173, “asymmetric” presumably refers to two phases rather than in latitude.
3) The Linoz calculation is problematic. The major assumption that NOy is omitted from the chemical families whilst it has been shown by Chipperfield et al. (1994) and subsequent work such as by Tian et al. (2006) that NOy variations are the primary driver of ozone QBO changes above 20hPa. This major assumption will affect the conclusion of ozone behaviour above 20 hPa.
4) The authors speculate that the changes below 20 hPa are driven by dynamics. Using their tools, it would be possible to quantify this.
Specific comments
1) Line 271 and Figure 3a. I am having difficulty seeing a monopole to tripole pattern. It looks like a tripole in each phase?
2) Much more care needs to be taken with the figures. The colorbars especially do not have sensible divisions. Some figures are too small to be easily readable.
References:
Chipperfield, M. P., L. J. Gray, J. S. Kinnersley, and J. Zawodny (1994), A two-dimensional model study of QBO signal in SAGE II NO2 and O3, Geophys. Res. Lett., 21, 589 – 592.
Tian, W., M. P. Chipperfield, L. J. Gray, and J. M. Zawodny (2006), Quasi-biennial oscillation and tracer distributions in a coupled chemistry-climate model, J. Geophys. Res., 111, D20301, doi:10.1029/2005JD006871.
Citation: https://doi.org/10.5194/egusphere-2024-1927-RC2
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