The evolution of zonally asymmetric austral ozone in a chemistry–climate model

Dennison, Fraser; McDonald, Adrian; Morgenstern, Olaf

doi:10.5194/acp-17-14075-2017

Cited by 9 publications

(8 citation statements)

References 36 publications

(66 reference statements)

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“…due to orographic forcing. For example, there is a significant trend in the orientation of the Antarctic polar vortex during the satellite era, which some models fail to reproduce (Dennison et al, 2017). Given the inability to attribute such misbehaviour to individual anthropogenic forcings as discussed above, it appears difficult though to consistently account for this in a correction.…”

Section: Linearity Of the Ozone Response To Greenhouse Gas Forcingmentioning

confidence: 95%

Ozone sensitivity to varying greenhouse gases and ozone-depleting substances in CCMI-1 simulations

et al. 2018

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Abstract. Ozone fields simulated for the first phase of the Chemistry-Climate Model Initiative (CCMI-1) will be used as forcing data in the 6th Coupled Model Intercomparison Project. Here we assess, using reference and sensitivity simulations produced for CCMI-1, the suitability of CCMI-1 model results for this process, investigating the degree of consistency amongst models regarding their responses to variations in individual forcings. We consider the influences of methane, nitrous oxide, a combination of chlorinated or brominated ozone-depleting substances, and a combination of carbon dioxide and other greenhouse gases. We find varying degrees of consistency in the models' responses in ozone to these individual forcings, including some considerable disagreement. In particular, the response of total-column ozone to these forcings is less consistent across the multi-model ensemble than profile comparisons. We analyse how stratospheric age of air, a commonly used diagnostic of stratospheric transport, responds to the forcings. For this diagnostic we find some salient differences in model behaviour, which may explain some of the findings for ozone. The findings imply that the ozone fields derived from CCMI-1 are subject to considerable uncertainties regarding the impacts of these anthropogenic forcings. We offer some thoughts on how to best approach the problem of generating a consensus ozone database from a multi-model ensemble such as CCMI-1.

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Section: Linearity Of the Ozone Response To Greenhouse Gas Forcingmentioning

confidence: 95%

Ozone sensitivity to varying greenhouse gases and ozone-depleting substances in CCMI-1 simulations

et al. 2018

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“…The dynamical behavior in the Southern Hemisphere is more similar across simulations than the Northern Hemisphere in Figure 3. This is because the dynamical asymmetry of the Antarctic stratosphere is generally smaller than that of the Arctic, but it may also be influenced by our choice of the UKCA model for our interactive simulation, which has been shown to underrepresent the degree of zonal asymmetry seen in observational analyses (Dennison et al, 2017). PV = potential vorticity.…”

Section: 1029/2018ms001478mentioning

confidence: 99%

Prescribing Zonally Asymmetric Ozone Climatologies in Climate Models: Performance Compared to a Chemistry‐Climate Model

Rae

Keeble

Hitchcock

et al. 2019

J Adv Model Earth Syst

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Three different methods of specifying ozone in an atmosphere‐only version of the HadGEM3‐A global circulation model are compared to the coupled chemistry configuration of this model. These methods include a specified zonal‐mean ozone climatology, a specified 3‐D ozone climatology, and a calculated‐asymmetry scheme in which a specified zonal‐mean ozone field is adapted online to be consistent with dynamically produced zonal asymmetries. These simulations all use identical boundary conditions and, by construction, have the same climatological zonal‐mean ozone, that of the coupled chemistry configuration of the model. Prescribing ozone, regardless of scheme, results in a simulation which is 3–4 times faster than the coupled chemistry‐climate model (CCM). Prescribing climatological zonal asymmetries leads to a vortex which is the correct intensity but which is systematically displaced over regions with lower prescribed ozone. When zonal asymmetries in ozone are free to evolve interactively with model dynamics, the modeled wintertime stratospheric vortex shape and mean sea level pressure patterns closely resemble that produced by the full CCM in both hemispheres, in terms of statistically significant differences. Further, we separate out the two distinct pathways by which zonal ozone asymmetries influence modeled dynamics. We present this interactive‐ozone zonal‐asymmetry scheme as an inexpensive tool for accurately modeling the impacts of dynamically consistent ozone fields as seen in a CCM which ultimately influence mean sea level pressure and tropospheric circulation (particularly during wintertime in the Northern Hemisphere, when ozone asymmetries are generally largest), without the computational burden of simulating interactive chemistry.

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“…Based on the previous sections, we calculate, assuming linear scaling and ignoring nonlinear coupling (Portmann et al, 2012;Dhomse et al, 2016), the ozone fields that would result from GHG scenarios other than the RCP 6.0 forcing used in REF-C2. For the moderate-emissions scenarios RCP 2.6 and 4.5, this can be seen as a consistency test.…”

Section: Linearity Of the Ozone Response To Greenhouse Gas Forcingmentioning

confidence: 99%

“…One limitation of this approach is that it does not account for nonlinear interactions between the forcings (e.g. stratospheric cooling caused by CO 2 slows down gas-phase ozone depletion; Portmann et al, 2012;Dhomse et al, 2016). We will address this further in Sect.…”

Section: Introductionmentioning

confidence: 99%

Response to reviewer 2

Morgenstern¹

2017

Preprint

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Ozone fields simulated for the first phase of the Chemistry-Climate Model Initiative (CCMI-1) will be used as forcing data in the 6th Coupled Model Intercomparison Project. Here we assess, using reference and sensitivity simulations produced for CCMI-1, the suitability of CCMI-1 model results for this process, investigating the degree of consistency amongst models regarding their responses to variations in individual forcings. We consider the influences of methane, nitrous oxide, a combination of chlorinated or brominated ozone-depleting substances, and a combination of carbon dioxide and other greenhouse gases. We find varying degrees of consistency in the models' responses in ozone to these individual forcings, including some considerable disagreement. In particular, the response of total-column ozone to these forcings is less consistent across the multi-model ensemble than profile comparisons. We analyse how stratospheric age of air, a commonly used diagnostic of stratospheric transport, responds to the forcings. For this diagnostic we find some salient differences in model behaviour, which may explain some of the findings for ozone. The findings imply that the ozone fields derived from CCMI-1 are subject to considerable uncertainties regarding the impacts of these anthropogenic forcings. We offer some thoughts on how to best approach the problem of generating a consensus ozone database from a multi-model ensemble such as CCMI-1.

show abstract

The evolution of zonally asymmetric austral ozone in a chemistry–climate model

Cited by 9 publications

References 36 publications

Ozone sensitivity to varying greenhouse gases and ozone-depleting substances in CCMI-1 simulations

Ozone sensitivity to varying greenhouse gases and ozone-depleting substances in CCMI-1 simulations

Prescribing Zonally Asymmetric Ozone Climatologies in Climate Models: Performance Compared to a Chemistry‐Climate Model

Response to reviewer 2

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