Recent Trends in Stratospheric Chlorine From Very Short‐Lived Substances

Hossaini, Ryan; Atlas, Elliot L.; Dhomse, Sandip; Chipperfield, Martyn P.; Bernath, Peter F.; Fernando, Anton; Mühle, Jens; Leeson, Amber; Montzka, S. A.; Feng, Wuhu; Harrison, Jeremy J.; Krummel, P. B.; Vollmer, Martin K.; Reimann, Stefan; O’Doherty, Simon; Young, Dickon; Maione, Michela; Arduini, Jgor; Lunder, Chris Rene

doi:10.1029/2018jd029400

Cited by 49 publications

(70 citation statements)

References 75 publications

(120 reference statements)

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“…S3). Past validation references for MLS O 3 include Jiang et al (2007), Froidevaux et al (2008a), and Livesey et al (2008), as well as the more recent work covering many satellite instruments by Hubert et al (2016). The original MLS data validation work for H 2 O is from Read et al (2007) and , who also described N 2 O validation; MLS HNO 3 validation was provided by Santee et al (2007).…”

Section: Average Abundancesmentioning

confidence: 99%

“…These results are broadly consistent with O 3 trends obtained by Steinbrecht et al (2017), who L. Froidevaux et al: Evaluation of CESM1 (WACCM) simulations use MLS as part of the longer-term merged data records, although they studied a longer time period (2000-2016). All things being equal, the errors in these trends should diminish as more years of data are added to the MLS O 3 record, which, for the middle and upper stratosphere, has been characterized as "very stable", namely within 0.1 to 0.2 % yr −1 versus sonde and lidar network ozone data (Hubert et al, 2016); it seems difficult to quantify "absolute stability" to much better than this, especially in the lower stratosphere. In the lower stratosphere, trend results are closer to zero, with larger variability and error bars (in % yr −1 ), and unambiguous detection of post-1997 ozone trends in this region remains elusive (WMO, 2014;Harris et al, 2015).…”

Section: Trendsmentioning

confidence: 99%

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Evaluation of CESM1 (WACCM) free-running and specified dynamics atmospheric composition simulations using global multispecies satellite data records

et al. 2019

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Abstract. We have analyzed near-global stratospheric data (and mesospheric data as well for H2O) in terms of absolute abundances, variability, and trends for O3, H2O, HCl, N2O, and HNO3, based on Aura Microwave Limb Sounder (MLS) data, as well as longer-term series from the Global OZone Chemistry And Related trace gas Data records for the Stratosphere (GOZCARDS). While we emphasize the evaluation of stratospheric models via data comparisons through 2014 to free-running (FR-WACCM) and specified dynamics (SD-WACCM) versions of the Community Earth System Model version 1 (CESM1) Whole Atmosphere Community Climate Model (WACCM), we also highlight observed stratospheric changes, using the most recent data from MLS. Regarding highlights from the satellite data, we have used multiple linear regression to derive trends based on zonal mean time series from Aura MLS data alone, between 60∘ S and 60∘ N. In the upper stratosphere, MLS O3 shows increases over 2005–2018 at ∼0.1–0.3 % yr−1 (depending on altitude and latitude) with 2σ errors of ∼0.2 % yr−1. For the lower stratosphere (LS), GOZCARDS O3 data for 1998–2014 point to small decreases between 60∘ S and 60∘ N, but the trends are more positive if the starting year is 2005. Southern midlatitudes (30–60∘ S) exhibit near-zero or slightly positive LS trends for 1998–2018. The LS O3 trends based on 2005–2018 MLS data are most positive (0.1–0.2 % yr−1) at these southern midlatitudes, although marginally statistically significant, in contrast to slightly negative or near-zero trends for 2005–2014. Given the high variability in LS O3, and the high sensitivity of trends to the choice of years used, especially for short periods, further studies are required for a robust longer-term LS trend result. For H2O, upper-stratospheric and mesospheric trends from GOZCARDS 1992–2010 data are near zero (within ∼0.2 % yr−1) and significantly smaller than trends (within ∼0.4–0.7 % yr−1) from MLS for 2005–2014 or 2005–2018. The latter short-term positive H2O trends are larger than expected from changes resulting from long-term increases in methane. We note that the very shallow solar flux maximum of solar cycle 24 has contributed to fairly large short-term mesospheric and upper-stratospheric H2O trends since 2005. However, given known drifts in the MLS H2O time series, MLS H2O trend results, especially after 2010, should be viewed as upper limits. The MLS data also show regions and periods of small HCl increases in the lower stratosphere, within the context of the longer-term stratospheric decrease in HCl, as well as interhemispheric–latitudinal differences in short-term HCl tendencies. We observe similarities in such short-term tendencies, and interhemispheric asymmetries therein, for lower-stratospheric HCl and HNO3, while N2O trend profiles exhibit anti-correlated patterns. In terms of the model evaluation, climatological averages for 2005–2014 from both FR-WACCM and SD-WACCM for O3, H2O, HCl, N2O, and HNO3 compare favorably with Aura MLS data averages over this period. However, the models at mid- to high latitudes overestimate mean MLS LS O3 values and seasonal amplitudes by as much as 50 %–60 %; such differences appear to implicate, in part, a transport-related model issue. At lower-stratospheric high southern latitudes, variations in polar winter and spring composition observed by MLS are well matched by SD-WACCM, with the main exception being for the early winter rate of decrease in HCl, which is too slow in the model. In general, we find that the latitude–pressure distributions of annual and semiannual oscillation amplitudes derived from MLS data are properly captured by the model amplitudes. In terms of closeness of fit diagnostics for model–data anomaly series, not surprisingly, SD-WACCM (driven by realistic dynamics) generally matches the observations better than FR-WACCM does. We also use root mean square variability as a more valuable metric to evaluate model–data differences. We find, most notably, that FR-WACCM underestimates observed interannual variability for H2O; this has implications for the time period needed to detect small trends, based on model predictions. The WACCM O3 trends generally agree (within 2σ uncertainties) with the MLS data trends, although LS trends are typically not statistically different from zero. The MLS O3 trend dependence on latitude and pressure is matched quite well by the SD-WACCM results. For H2O, MLS and SD-WACCM positive trends agree fairly well, but FR-WACCM shows significantly smaller increases; this discrepancy for FR-WACCM is even more pronounced for longer-term GOZCARDS H2O records. The larger discrepancies for FR-WACCM likely arise from its poorer correlations with cold point temperatures and with quasi-biennial oscillation (QBO) variability. For HCl, while some expected decreases in the global LS are seen in the observations, there are interhemispheric differences in the trends, and increasing tendencies are suggested in tropical MLS data at 68 hPa, where there is only a slight positive trend in SD-WACCM. Although the vertical gradients in MLS HCl trends are well duplicated by SD-WACCM, the model trends are always somewhat more negative; this deserves further investigation. The original MLS N2O product time series yield small positive LS tropical trends (2005–2012), consistent with models and with rates of increase in tropospheric N2O. However, longer-term series from the more current MLS N2O standard product are affected by instrument-related drifts that have also impacted MLS H2O. The LS short-term trend profiles from MLS N2O and HNO3 at midlatitudes in the two hemispheres have different signs; these patterns are well matched by SD-WACCM trends for these species. These model–data comparisons provide a reminder that the QBO and other dynamical factors affect decadal variability in a major way, notably in the lower stratosphere, and can thus significantly hinder the goals of robustly extracting (and explaining) small underlying long-term trends. The data sets and tools discussed here for model evaluation could be expanded to comparisons of species or regions not included here, as well as to comparisons between a variety of chemistry–climate models.

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Section: Average Abundancesmentioning

confidence: 99%

Section: Trendsmentioning

confidence: 99%

Evaluation of CESM1 (WACCM) free-running and specified dynamics atmospheric composition simulations using global multispecies satellite data records

et al. 2019

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“…Yields for the different VSLS reaction pathways producing stratospheric phosgene are listed in Table . Phosgene production from CH 2 Cl 2 was parameterized using an expression adapted from the full degradation mechanism (Hossaini et al, ):

normalξ = \frac{0.7 k_{3} ([], normalH O_{2}) + 0.4 k_{4} ([], normalC H_{3} O_{2})}{k_{1} ([], NO) + k_{2} ([], normalN O_{3}) + k_{3} ([], normalH O_{2}) + k_{4} ([], normalC H_{3} O_{2})},

…”

Section: Model Simulations Of Phosgenementioning

confidence: 99%

Phosgene in the Upper Troposphere and Lower Stratosphere: A Marker for Product Gas Injection Due to Chlorine‐Containing Very Short Lived Substances

Harrison

Chipperfield

Hossaini

et al. 2019

Geophysical Research Letters

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Phosgene in the atmosphere is produced via the degradation of carbon tetrachloride, methyl chloroform, and a number of chlorine‐containing very short lived substances (VSLS). These VSLS are not regulated by the Montreal Protocol even though they contribute to stratospheric ozone depletion. While observations of VSLS can quantify direct stratospheric source gas injection, observations of phosgene in the upper troposphere/lower stratosphere can be used as a marker of product gas injection of chlorine‐containing VSLS. In this work we report upper troposphere/lower stratosphere measurements of phosgene made by the ACE‐FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) instrument and compare with results from the TOMCAT/SLIMCAT three‐dimensional chemical transport model to constrain phosgene trends over the 2004–2016 period. The 13‐year ACE‐FTS time series provides the first observational evidence for an increase in chlorine product gas injection. In 2016, VSLS accounted for 27% of modeled stratospheric phosgene, up from 20% in the mid‐2000s.

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“…A quantitative measure of Antarctic O 3 increase attributable to the known ODS decline is essential in order to demonstrate that the Montreal Protocol and its amendments are having the intended impact. If Antarctic O 3 in the coming decades does not respond as we predict, then we must assess whether this indicates a change in stratospheric chemical or dynamical processes controlling O 3 or whether it points to unexpected emissions of regulated or unregulated ODSs (e.g., Hossaini et al, ; Montzka et al, ).…”

Section: Introductionmentioning

confidence: 99%

Why Do Antarctic Ozone Recovery Trends Vary?

2019

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We use satellite ozone records and Global Modeling Initiative chemistry transport model simulations integrated with Modern Era Retrospective for Research and Analysis 2 meteorology to identify a metric that accurately captures the trend in Antarctic ozone attributable to the decline in ozone depleting substances (ODSs). The GMI CTM Baseline simulation with realistically varying ODS levels closely matches observed interannual to decadal scale variations in Antarctic September ozone over the past four decades. The expected increase or recovery trend is obtained from the differences between the Baseline simulation and one with identical meteorology and fixed 1995 ODS levels. The differences show that vortex-averaged column O 3 has the greatest sensitivity to ODS change from 1 to 20 September. The observed vortex-averaged column O 3 during this period produces a trend consistent with the expected recovery attributable to ODS decline. Trends from dates after 20 September have smaller sensitivity to ODS decline and are more uncertain due to transport variability. Simulations show that the greatest decrease in O 3 loss (i.e., recovery) occurs inside the vortex near the edge. The polar cap metrics have vortex size-dependent bias and do not consistently sample this region. Because the 60-90°S 220 Dobson unit O 3 mass deficit metric does not sample the edge region, its trend is lower than the expected trend; this is improved by area weighting. The 250-Dobson unit O 3 mass deficit metric samples more of the edge region, which increases its trend. Approximately 25% of the September Antarctic O 3 increase is due to higher O 3 levels in June prior to winter depletion.Plain Language Summary Atmospheric levels of ozone depleting substances (ODSs) are decreasing due to the Montreal Protocol and its amendments. The Ozone Hole is beginning to shrink, but trends derived from Antarctic O 3 observations differ widely. We compared model simulations with different ODS levels to reveal where, when, and how much Antarctic O 3 increases in response to ODS decline. We found that trend studies used O 3 measurements from different dates and regions, which usually did not line up with regions where the greatest O 3 recovery occurs or with the time period when O 3 changes are most sensitive to declining ODSs. This explains why reported trends and their uncertainties vary so much. Our simulations found the strongest, clearest signal of increasing O 3 due to ODS change between 1 and 20 September inside the Antarctic polar vortex. The observed vortex O 3 trend from 1 to 20 September is 1.2-1.6 Dobson unit/year and is consistent with the simulations' results, indicating that O 3 is increasing at the rate expected due to ODS decrease. The greatest recovery occurs inside the vortex but just outside the O 3 220 Dobson unit contour, the traditionally defined boundary of the Ozone Hole. Simulations and observations agree that the September Ozone Hole is shrinking at 0.24-0.36 × 10 6 km 2 /year.

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Recent Trends in Stratospheric Chlorine From Very Short‐Lived Substances

Cited by 49 publications

References 75 publications

Evaluation of CESM1 (WACCM) free-running and specified dynamics atmospheric composition simulations using global multispecies satellite data records

Evaluation of CESM1 (WACCM) free-running and specified dynamics atmospheric composition simulations using global multispecies satellite data records

Phosgene in the Upper Troposphere and Lower Stratosphere: A Marker for Product Gas Injection Due to Chlorine‐Containing Very Short Lived Substances

Why Do Antarctic Ozone Recovery Trends Vary?

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