We evaluate polar ozone depletion chemistry using the specified dynamics version of the Whole Atmosphere Community Climate Model for the year 2011. We find that total ozone depletion in both hemispheres is dependent on cold temperatures (below 192 K) and associated heterogeneous chemistry on polar stratospheric cloud particles. Reactions limited to warmer temperatures above 192 K, or on binary liquid aerosols, yield little modeled polar ozone depletion in either hemisphere. An imposed factor of three enhancement in stratospheric sulfate increases ozone loss by up to 20 Dobson unit (DU) in the Antarctic and 15 DU in the Arctic in this model. Such enhanced sulfate loads are similar to those observed following recent relatively small volcanic eruptions since 2005 and imply impacts on the search for polar ozone recovery. Ozone losses are strongly sensitive to temperature, with a test case cooler by 2 K producing as much as 30 DU additional ozone loss in the Antarctic and 40 DU in the Arctic. A new finding of this paper is the use of the temporal behavior and variability of ClONO 2 and HCl as indicators of the efficacy of heterogeneous chemistry. Transport of ClONO 2 from the southern subpolar regions near 55-65°S to higher latitudes near 65-75°S provides a flux of NO x from more sunlit latitudes to the edge of the vortex and is important for ozone loss in this model. Comparisons between modeled and observed total column and profile ozone perturbations, ClONO 2 abundances, and the rate of change of HCl bolster confidence in these conclusions.

Over the past three decades, Antarctic surface climate has undergone pronounced changes. Many of these changes have been linked to stratospheric ozone depletion. Here linkages between Antarctic ozone loss, the accompanying circulation changes, and summertime Southern Hemisphere (SH) midlatitude surface temperatures are explored. Long-term surface climate changes associated with ozone-driven changes in the southern annular mode (SAM) at SH midlatitudes in summer are not annular in appearance owing to differences in regional circulation and precipitation impacts. Both station and reanalysis data indicate a trend toward cooler summer temperatures over southeast and south-central Australia and inland areas of the southern tip of Africa. It is also found that since the onset of the ozone hole, there have been significant shifts in the distributions of both the seasonal mean and daily maximum summertime temperatures in the SH midlatitude regions between high and low ozone years. Unusually hot summer extremes are associated with anomalously high ozone in the previous November, including the recent very hot austral summer of 2012/13. If the relationship found in the past three decades continues to hold, the level of late springtime ozone over Antarctica has the potential to be part of a useful predictor set for the following summer's conditions. The results herein suggest that skillful predictions may be feasible for both the mean seasonal temperature and the frequency of extreme hot events in some SH midlatitude regions of Australia, Africa, and South America.

Observed and modeled patterns of lower stratospheric seasonal trends in Antarctic ozone and temperature in the late 20th (1979–2000) and the early 21st (2000–2014) centuries are compared. Patterns of pre‐2000 observed Antarctic ozone decreases and stratospheric cooling as a function of month and pressure are followed by opposite‐signed (i.e., “mirrored”) patterns of ozone increases and warming post‐2000. An interactive chemistry‐climate model forced by changes in anthropogenic ozone depleting substances produces broadly similar mirrored features. Statistical analysis of unforced model simulations (from long‐term model control simulations of a few centuries up to 1000 years) suggests that internal and solar natural variability alone is unable to account for the pattern of observed ozone trend mirroring, implying that forcing is the dominant driver of this behavior. Radiative calculations indicate that ozone increases have contributed to Antarctic warming of the lower stratosphere over 2000–2014, but dynamical changes that are likely due to internal variability over this relatively short period also appear to be important. Overall, the results support the recent finding that the healing of the Antarctic ozone hole is underway and that coupling between dynamics, chemistry, and radiation is important for a full understanding of the causes of observed stratospheric temperature and ozone changes.

Model simulations presented in this paper suggest that transport processes associated with the summer monsoons bring increased abundances of hydrochloric acid into contact with liquid sulfate aerosols in the cold tropical lowermost stratosphere, leading to heterogeneous chemical activation of chlorine species. The calculations indicate that the spatial and seasonal distributions of chlorine monoxide and chlorine nitrate near the monsoon regions of the northern hemisphere tropical and subtropical lowermost stratosphere could provide indicators of heterogeneous chlorine processing. In the model, these processes impact the local ozone budget and decrease ozone abundances, implying a chemical contribution to longer‐term northern tropical ozone profile changes at 16–19 km.

The conventional method of calculating atmospheric temperature profiles using Rayleigh-scattering lidar measurements has limitations that necessitate abandoning temperatures retrieved at the greatest heights, due to the assumption of a pressure value required to initialize the integration at the highest altitude. An inversion approach is used to develop an alternative way of retrieving nightly atmospheric temperature profiles from the lidar measurements. Measurements obtained by the Purple Crow lidar facility located near The University of Western Ontario are used to develop and test this new technique. Our results show temperatures can be reliably retrieved at all heights where measurements with adequate signal-to-noise ratio exist. A Monte Carlo technique was developed to provide accurate estimates of both the systematic and random uncertainties for the retrieved nightly average temperature profile. An advantage of this new method is the ability to seed the temperature integration from the lowest rather than the greatest height, where the variability of the pressure is smaller than in the mesosphere or lower thermosphere and may in practice be routinely measured by a radiosonde, rather than requiring a rocket or satellite-borne measurement. Thus, this new technique extends the altitude range of existing Rayleigh-scatter lidars 10-15 km, producing the equivalent of four times the power-aperture product.

The Optical Spectrograph and InfraRed Imaging System (OSIRIS) on the Odin satellite is currently in its 12th year of observing the Earth's limb. For the first time, continuous temperature profiles extending from the stratopause to the upper mesosphere have been derived from OSIRIS measurements of Rayleigh-scattered sunlight. Through most of the mesosphere, OSIRIS temperatures are in good agreement with coincident temperature profiles derived from other satellite and ground-based measurements. In the altitude region of 55-80 km, OSIRIS temperatures are typically within 4-5 K of those from the SABER, ACE-FTS, and SOFIE instruments on the TIMED, SciSat-I, and AIM satellites, respectively. The mean differences between individual OSIRIS profiles and those of the other satellite instruments are typically within the combined uncertainties and previously reported biases. OSIRIS temperatures are typically within 2 K of those from the University of Western Ontario's Purple Crow Lidar in the altitude region of 52-79 km, where the mean differences are within combined uncertainties. Near 84 km, OSIRIS temperatures exhibit a cold bias of 10-15 K, which is due to a cold bias in OSIRIS O 2 A-band temperatures at 85 km, the upper boundary of the Rayleigh-scatter derived temperatures; and near 48 km OSIRIS temperatures exhibit a cold bias of 5-15 K, which is likely due to multiple-scatter effects that are not taken into account in the retrieval.

Abstract. We perform a formal attribution study of upperand lower-stratospheric ozone changes using observations together with simulations from the Whole Atmosphere Community Climate Model. Historical model simulations were used to estimate the zonal-mean response patterns ("fingerprints") to combined forcing by ozone-depleting substances (ODSs) and well-mixed greenhouse gases (GHGs), as well as to the individual forcing by each factor. Trends in the similarity between the searched-for fingerprints and homogenized observations of stratospheric ozone were compared to trends in pattern similarity between the fingerprints and the internally and naturally generated variability inferred from long control runs. This yields estimated signal-to-noise (S/N) ratios for each of the three fingerprints (ODS, GHG, and ODS + GHG). In both the upper stratosphere (defined in this paper as 1 to 10 hPa) and lower stratosphere (40 to 100 hPa), the spatial fingerprints of the ODS + GHG and ODS-only patterns were consistently detectable not only during the era of maximum ozone depletion but also throughout the observational record . We also develop a fingerprint attribution method to account for forcings whose time evolutions are markedly nonlinear over the observational record. When the nonlinearity of the time evolution of the ODS and ODS + GHG signals is accounted for, we find that the S/N ratios obtained with the stratospheric ODS and ODS + GHG fingerprints are enhanced relative to standard linear trend analysis. Use of the nonlinear signal detection method also reduces the detection time -the estimate of the date at which ODS and GHG impacts on ozone can be formally identified. Furthermore, by explicitly considering nonlinear signal evolution, the complete observational record can be used in the S/N analysis, without applying piecewise linear regression and introducing arbitrary break points. The GHG-driven fingerprint of ozone changes was not statistically identifiable in either the upper-or lower-stratospheric SWOOSH data, irrespective of the signal detection method used. In the WACCM simulations of future climate change, the GHG signal is statistically identifiable between 2020 and 2030. Our findings demonstrate the importance of continued stratospheric ozone monitoring to improve estimates of the contributions of ODS and GHG forcing to global changes in stratospheric ozone.

<p><strong>Abstract.</strong> We perform a formal attribution study of upper and lower stratospheric ozone changes using observations together with simulations from the Whole Atmosphere Community Climate Model. Historical model simulations were used to estimate the zonal-mean response patterns (<q>fingerprints</q>) to combined forcing by ozone depleting substances (ODS) and well-mixed greenhouse gases (GHG), as well as to the individual forcing by each factor. Trends in the similarity between the searched-for fingerprints and homogenized observations of stratospheric ozone were compared to trends in pattern similarity between the fingerprints and the internally and naturally generated variability inferred from long control runs. This yields estimated signal-to-noise (S/N) ratios for each of the three fingerprints (ODS, GHG, and ODS+GHG). In both the upper stratosphere (defined in this paper as 1 to 10 hPa) and lower stratosphere (40 to 100 hPa), the spatial fingerprints of the ODS+GHG and ODS only patterns were consistently detectable not only during the era of maximum ozone depletion, but also throughout the observational record (1984–2016). Furthermore, we develop a fingerprint attribution method to account for forcings whose time evolutions are markedly nonlinear over the observational record. When the nonlinearity of the time evolution of the ODS and ODS+GHG signals are used in the trend regression, we find that the S/N ratios obtained with the stratospheric ODS and ODS+GHG fingerprints are enhanced relative to standard linear trend analysis. With this method, the complete observational record can be used in the S/N analysis, without applying piece-wise linear regression and introducing arbitrary break points. The GHG-driven fingerprint of ozone changes was not statistically identifiable in the either the upper or lower stratospheric SWOOSH data, irrespective of the method used. Use of the nonlinear signal method, instead of directly operating on ozone trends, also reduces the detection time – the estimate of the date at which ODS and GHG impacts on ozone can be formally identified. In the WACCM future simulations, the GHG signal is statistically identifiable between 2020–2030. Our findings demonstrate the importance of continued stratospheric ozone monitoring to improve estimates of the contributions of ODS and GHG forcing to global changes in stratospheric ozone.</p>