An updated version of a gap-free monthly mean zonal mean ozone
database

Haßler, Birgit; Kremser, Stefanie; Bodeker, G. E.; Lewis, Jared; Nesbit, Kage; Davis, Sean; Chipperfield, Martyn P.; Dhomse, Sandip; Dameris, Martin

doi:10.5194/essd-2018-56

Cited by 5 publications

(7 citation statements)

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“…The methodology of filling data gaps to construct a globally filled database is an updated version of the method described in Bodeker et al (2013), where a pre-filling processing step was added. A more detailed description of BSVertOzone can be found in Hassler et al (2018).…”

Section: Models Scenarios and Simulationsmentioning

confidence: 99%

“…6) stratosphere separately. The figures include partial column observations derived from the composite BSVertOzone dataset (Bodeker et al, 2013;Hassler et al, 2018). This composite dataset has the advantage, compared to observations from any single instrument, of being fully height-resolved and available continuously over 1979-2016.…”

Section: Ozone Profile Variationsmentioning

confidence: 99%

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Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations

et al. 2018

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Abstract. >We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed meteorology) there is a large spread (±20 DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new CCMI simulations project that global total column ozone will return to 1980 values in 2049 (with a 1σ uncertainty of 2043–2055). At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2045 (2039–2050), and at Northern Hemisphere mid-latitudes in 2032 (2020–2044). In the polar regions, the return dates are 2060 (2055–2066) in the Antarctic in October and 2034 (2025–2043) in the Arctic in March. The earlier return dates in the Northern Hemisphere reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5–17 years, depending on the region, with the previous best estimates often falling outside of our uncertainty range. In the tropics only around half the models predict a return of ozone to 1980 values, around 2040, while the other half do not reach the 1980 value. All models show a negative trend in tropical total column ozone towards the end of the 21st century. The CCMI models generally agree in their simulation of the time evolution of stratospheric chlorine and bromine, which are the main drivers of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse gas-induced cooling speeds up the return by about 10–20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates of ozone and chlorine, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, clear conclusions can only be drawn for stratospheric ozone columns rather than the total column. As noted by previous studies, the timing of ozone recovery is affected by the evolution of N2O and CH4. However, quantifying the effect in the simulations analysed here is limited by the few realisations available for these experiments compared to internal model variability. The large increase in N2O given in RCP 6.0 extends the ozone return globally by ∼ 15 years relative to N2O fixed at 1960 abundances, mainly because it allows tropical column ozone to be depleted. The effect in extratropical latitudes is much smaller. The large increase in CH4 given in the RCP 8.5 scenario compared to RCP 6.0 also lengthens ozone return by ∼ 15 years, again mainly through its impact in the tropics. Overall, our estimates of ozone return dates are uncertain due to both uncertainties in future scenarios, in particular those of greenhouse gases, and uncertainties in models. The scenario uncertainty is small in the short term but increases with time, and becomes large by the end of the century. There are still some model–model differences related to well-known processes which affect ozone recovery. Efforts need to continue to ensure that models used for assessment purposes accurately represent stratospheric chemistry and the prescribed scenarios of ozone-depleting substances, and only those models are used to calculate return dates. For future assessments of single forcing or combined effects of CO2, CH4, and N2O on the stratospheric column ozone return dates, this work suggests that it is more important to have multi-member (at least three) ensembles for each scenario from every established participating model, rather than a large number of individual models.

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Section: Models Scenarios and Simulationsmentioning

confidence: 99%

Section: Ozone Profile Variationsmentioning

confidence: 99%

Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations

et al. 2018

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“…CESM1-WACCM and CESM1-CAM4 data were downloaded from http: //www.earthsystemgrid.org. For instructions for access to both archives see http://blogs.reading.ac.uk/ccmi/badc-data-access or Hegglin et al (2015).…”

Section: Discussionmentioning

confidence: 99%

Response to Reviewers#2’s comments

Dhomse¹

2018

Preprint

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We thank the reviewer#2 very much for his/her insightful comments. These are repeated below in italics, followed by our responses after the '»'. This paper details ozone return dates from the CCMI model intercomparison. As such, the new estimates of the return dates are the primary new finding of the paper and most of the other results discussed are previously known results. The paper is clearly written and outlining the latest results on ozone return dates is an important task for the upcoming ozone assessment. I have a number of comments but most are relatively minor and thus I recommend publishing the paper after the comments are adequately addressed. C1 ACPD Interactive commentPrinter-friendly version Discussion paper

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“…For the data presented here the following improvements over the latest version of the BDBP were made: (1) ozone measurements from different data sources that are used as input for the monthly mean zonal mean calculation were updated (different satellite measurements and ozone soundings); (2) additional data sources were added (Microwave Limb Sounder, MLS, ozone 45 profiles and recent years of ozone soundings); (3) drifts and biases between measurements from different data sources are adjusted (using a chemical transport model as transfer standard); (4) uncertainties are propagated from individual measurements through all preparation and calculation procedure steps to the final product; and (5) construct a globally filled database, is identical to the method described in Bodeker et al (2013). A more detailed description of BSVertOzone can be found in Hassler et al (2018). Figures S1-S5).…”

Section: ) Methodologymentioning

confidence: 99%

Estimates of Ozone Return Dates from Chemistry-Climate Model Initiative Simulations

Dhomse¹,

Kinnison²,

Chipperfield³

et al. 2018

Preprint

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Abstract. We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed 5 meteorology) there is a large spread (±20 DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new 10 CCMI simulations project that global total column ozone will return to 1980 values in 2047 (with a 1-σ uncertainty of [2042][2043][2044][2045][2046][2047][2048][2049][2050][2051][2052]. At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2046 (2042-2050), and at Northern Hemisphere midlatitudes in 2034 (2024-2044). In the polar regions, the return dates are 2062 (2055)(2056)(2057)(2058)(2059)(2060)(2061)(2062)(2063)(2064)(2065)(2066) in the Antarctic in October and 2035October and (2025October and -2040 in the Arctic in March. The earlier return dates in the 15 NH reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5-15 years, depending on the region. In the tropics only around half the models predict a return to 1980 values, at around 2040, while the other half do not reach this value. All models show a negative trend in tropical total column ozone towards the end of the 21 st century. The CCMI models generally agree in 20 their simulation of the time evolution of stratospheric chlorine, which is the main driver of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse 25 gas-induced cooling speeds up the return by about 10-20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, 30 clear conclusions can only be drawn for stratospheric ozone columns rather than the total ...

show abstract

An updated version of a gap-free monthly mean zonal mean ozone database

Cited by 5 publications

References 12 publications

Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations

Estimates of ozone return dates from Chemistry-Climate Model Initiative simulations

Response to Reviewers#2’s comments

Estimates of Ozone Return Dates from Chemistry-Climate Model Initiative Simulations

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