scholarly journals Trends in Stratospheric Ozone: Lessons Learned from a 3D Chemical Transport Model

2006 ◽  
Vol 63 (3) ◽  
pp. 1028-1041 ◽  
Author(s):  
Richard S. Stolarski ◽  
Anne R. Douglass ◽  
Stephen Steenrod ◽  
Steven Pawson

Abstract Stratospheric ozone is affected by external factors such as chlorofluorcarbons (CFCs), volcanoes, and the 11-yr solar cycle variation of ultraviolet radiation. Dynamical variability due to the quasi-biennial oscillation and other factors also contribute to stratospheric ozone variability. A research focus during the past two decades has been to quantify the downward trend in ozone due to the increase in industrially produced CFCs. During the coming decades research will focus on detection and attribution of the expected recovery of ozone as the CFCs are slowly removed from the atmosphere. A chemical transport model (CTM) has been used to simulate stratospheric composition for the past 30 yr and the next 20 yr using 50 yr of winds and temperatures from a general circulation model (GCM). The simulation includes the solar cycle in ultraviolet radiation, a representation of aerosol surface areas based on observations including volcanic perturbations from El Chichon in 1982 and Pinatubo in 1991, and time-dependent mixing ratio boundary conditions for CFCs, halons, and other source gases such as N2O and CH4. A second CTM simulation was carried out for identical solar flux and boundary conditions but with constant “background” aerosol conditions. The GCM integration included an online ozonelike tracer with specified production and loss that was used to evaluate the effects of interannual variability in dynamics. Statistical time series analysis was applied to both observed and simulated ozone to examine the capability of the analyses for the determination of trends in ozone due to CFCs and to separate these trends from the solar cycle and volcanic effects in the atmosphere. The results point out several difficulties associated with the interpretation of time series analyses of atmospheric ozone data. In particular, it is shown that lengthening the dataset reduces the uncertainty in derived trend due to interannual dynamic variability. It is further shown that interannual variability can make it difficult to accurately assess the impact of a volcanic eruption, such as Pinatubo, on ozone. Such uncertainties make it difficult to obtain an early proof of ozone recovery in response to decreasing chlorine.

2011 ◽  
Vol 11 (24) ◽  
pp. 12773-12786 ◽  
Author(s):  
S. Dhomse ◽  
M. P. Chipperfield ◽  
W. Feng ◽  
J. D. Haigh

Abstract. We have used an off-line 3-D chemical transport model (CTM) to investigate the 11-yr solar cycle response in tropical stratospheric ozone. The model is forced with European Centre for Medium-Range Weather Forecasts (ECMWF) (re)analysis (ERA-40/operational and ERA-Interim) data for the 1979–2005 time period. We have compared the modelled solar response in ozone to observation-based data sets that are constructed using satellite instruments such as Total Ozone Mapping Spectrometer (TOMS), Solar Backscatter UltraViolet instrument (SBUV), Stratospheric Aerosol and Gas Experiment (SAGE) and Halogen Occultation Experiment (HALOE). A significant difference is seen between simulated and observed ozone during the 1980s, which is probably due to inhomogeneities in the ERA-40 reanalyses. In general, the model with ERA-Interim dynamics shows better agreement with the observations from 1990 onwards than with ERA-40. Overall both standard model simulations are partially able to simulate a "double peak"-structured ozone solar response with a minimum around 30 km, and these are in better agreement with HALOE than SAGE-corrected SBUV (SBUV/SAGE) or SAGE-based data sets. In the tropical lower stratosphere (TLS), the modelled solar response with time-varying aerosols is amplified through aliasing with a volcanic signal, as the model overestimates ozone loss during high aerosol loading years. However, the modelled solar response with fixed dynamics and constant aerosols shows a positive signal which is in better agreement with SBUV/SAGE and SAGE-based data sets in the TLS. Our model simulations suggests that photochemistry contributes to the ozone solar response in this region. The largest model-observation differences occur in the upper stratosphere where SBUV/SAGE and SAGE-based data show a significant (up to 4%) solar response whereas the standard model and HALOE do not. This is partly due to a positive solar response in the ECMWF upper stratospheric temperatures which reduces the modelled ozone signal. The large positive upper stratospheric solar response seen in SBUV/SAGE and SAGE-based data can be reproduced in model runs with fixed dynamical fields (i.e. no inter-annual meteorological changes). As these runs effectively assume no long-term temperature changes (solar-induced or otherwise), it should provide an upper limit of the ozone solar response. Overall, full quantification of the solar response in stratospheric ozone is limited by differences in the observed data sets and by uncertainties in the solar response in stratospheric temperatures.


2012 ◽  
Vol 12 (11) ◽  
pp. 30825-30867
Author(s):  
G. Kirgis ◽  
T. Leblanc ◽  
I. S. McDermid ◽  
T. D. Walsh

Abstract. The Jet Propulsion Laboratory (JPL) lidars, at the Mauna Loa Observatory, Hawaii (MLO, 19.5° N, 155.6° W) and the JPL Table Mountain Facility (TMF, California, 34.5° N, 117.7° W), have been measuring vertical profiles of stratospheric ozone routinely since the early 1990's and late-1980s respectively. Interannual variability of ozone above these two sites was investigated using a multi-linear regression analysis on the deseasonalized monthly mean lidar and satellite time-series at 1 km intervals between 20 and 45 km from January 1995 to April 2011, a period of low volcanic aerosol loading. Explanatory variables representing the 11-yr solar cycle, the El Niño Southern Oscillation, the Quasi-Biennial Oscillation, the Eliassen–Palm flux, and horizontal and vertical transport were used. A new proxy, the mid-latitude ozone depleting gas index, which shows a decrease with time as an outcome of the Montreal Protocol, was introduced and compared to the more commonly used linear trend method. The analysis also compares the lidar time-series and a merged time-series obtained from the space-borne stratospheric aerosol and gas experiment II, halogen occultation experiment, and Aura-microwave limb sounder instruments. The results from both lidar and satellite measurements are consistent with recent model simulations which propose changes in tropical upwelling. Additionally, at TMF the ozone depleting gas index explains as much variance as the Quasi-Biennial Oscillation in the upper stratosphere. Over the past 17 yr a diminishing downward trend in ozone was observed before 2000 and a net increase, and sign of ozone recovery, is observed after 2005. Our results which include dynamical proxies suggest possible coupling between horizontal transport and the 11-yr solar cycle response, although a dataset spanning a period longer than one solar cycle is needed to confirm this result.


2012 ◽  
Vol 5 (6) ◽  
pp. 1531-1542 ◽  
Author(s):  
L. K. Emmons ◽  
P. G. Hess ◽  
J.-F. Lamarque ◽  
G. G. Pfister

Abstract. A procedure for tagging ozone produced from NO sources through updates to an existing chemical mechanism is described, and results from its implementation in the Model for Ozone and Related chemical Tracers (MOZART-4), a global chemical transport model, are presented. Artificial tracers are added to the mechanism, thus, not affecting the standard chemistry. The results are linear in the troposphere, i.e., the sum of ozone from individual tagged sources equals the ozone from all sources to within 3% in zonal mean monthly averages. In addition, the tagged ozone is shown to equal the standard ozone, when all tropospheric sources are tagged and stratospheric input is turned off. The stratospheric ozone contribution to the troposphere determined from the difference between total ozone and ozone from all tagged sources is significantly less than estimates using a traditional stratospheric ozone tracer (8 vs. 20 ppbv at the surface). The commonly used technique of perturbing NO emissions by 20% in a region to determine its ozone contribution is compared to the tagging technique, showing that the tagged ozone is 2–4 times the ozone contribution that was deduced from perturbing emissions. The ozone tagging described here is useful for identifying source contributions based on NO emissions in a given state of the atmosphere, such as for quantifying the ozone budget.


2013 ◽  
Vol 13 (8) ◽  
pp. 21455-21505
Author(s):  
E. Emili ◽  
B. Barret ◽  
S. Massart ◽  
E. Le Flochmoen ◽  
A. Piacentini ◽  
...  

Abstract. Accurate and temporally resolved fields of free-troposphere ozone are of major importance to quantify the intercontinental transport of pollution and the ozone radiative forcing. In this study we examine the impact of assimilating ozone observations from the Microwave Limb Sounder (MLS) and the Infrared Atmospheric Sounding Interferometer (IASI) in a global chemical transport model (MOdèle de Chimie Atmosphérique à Grande Échelle, MOCAGE). The assimilation of the two instruments is performed by means of a variational algorithm (4-D-VAR) and allows to constrain stratospheric and tropospheric ozone simultaneously. The analysis is first computed for the months of August and November 2008 and validated against ozone-sondes measurements to verify the presence of observations and model biases. It is found that the IASI Tropospheric Ozone Column (TOC, 1000–225 hPa) should be bias-corrected prior to assimilation and MLS lowermost level (215 hPa) excluded from the analysis. Furthermore, a longer analysis of 6 months (July–August 2008) showed that the combined assimilation of MLS and IASI is able to globally reduce the uncertainty (Root Mean Square Error, RMSE) of the modeled ozone columns from 30% to 15% in the Upper-Troposphere/Lower-Stratosphere (UTLS, 70–225 hPa) and from 25% to 20% in the free troposphere. The positive effect of assimilating IASI tropospheric observations is very significant at low latitudes (30° S–30° N), whereas it is not demonstrated at higher latitudes. Results are confirmed by a comparison with additional ozone datasets like the Measurements of OZone and wAter vapour by aIrbus in-service airCraft (MOZAIC) data, the Ozone Monitoring Instrument (OMI) total ozone columns and several high-altitude surface measurements. Finally, the analysis is found to be little sensitive to the assimilation parameters and the model chemical scheme, due to the high frequency of satellite observations compared to the average life-time of free-troposphere/low-stratosphere ozone.


2021 ◽  
Vol 13 (12) ◽  
pp. 5711-5729
Author(s):  
Sandip S. Dhomse ◽  
Carlo Arosio ◽  
Wuhu Feng ◽  
Alexei Rozanov ◽  
Mark Weber ◽  
...  

Abstract. High-quality stratospheric ozone profile data sets are a key requirement for accurate quantification and attribution of long-term ozone changes. Satellite instruments provide stratospheric ozone profile measurements over typical mission durations of 5–15 years. Various methodologies have then been applied to merge and homogenise the different satellite data in order to create long-term observation-based ozone profile data sets with minimal data gaps. However, individual satellite instruments use different measurement methods, sampling patterns and retrieval algorithms which complicate the merging of these different data sets. In contrast, atmospheric chemical models can produce chemically consistent long-term ozone simulations based on specified changes in external forcings, but they are subject to the deficiencies associated with incomplete understanding of complex atmospheric processes and uncertain photochemical parameters. Here, we use chemically self-consistent output from the TOMCAT 3-D chemical transport model (CTM) and a random-forest (RF) ensemble learning method to create a merged 42-year (1979–2020) stratospheric ozone profile data set (ML-TOMCAT V1.0). The underlying CTM simulation was forced by meteorological reanalyses, specified trends in long-lived source gases, solar flux and aerosol variations. The RF is trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set over the time periods of the Microwave Limb Sounder (MLS) from the Upper Atmosphere Research Satellite (UARS) (1991–1998) and Aura (2005–2016) missions. We find that ML-TOMCAT shows excellent agreement with available independent satellite-based data sets which use pressure as a vertical coordinate (e.g. GOZCARDS, SWOOSH for non-MLS periods) but weaker agreement with the data sets which are altitude-based (e.g. SAGE-CCI-OMPS, SCIAMACHY-OMPS). We find that at almost all stratospheric levels ML-TOMCAT ozone concentrations are well within uncertainties of the observational data sets. The ML-TOMCAT (V1.0) data set is ideally suited for the evaluation of chemical model ozone profiles from the tropopause to 0.1 hPa and is freely available via https://doi.org/10.5281/zenodo.5651194 (Dhomse et al., 2021).


2005 ◽  
Vol 5 (3) ◽  
pp. 597-609 ◽  
Author(s):  
C. S. Singleton ◽  
C. E. Randall ◽  
M. P. Chipperfield ◽  
S. Davies ◽  
W. Feng ◽  
...  

Abstract. The SLIMCAT three-dimensional chemical transport model (CTM) is used to infer chemical ozone loss from Polar Ozone and Aerosol Measurement (POAM) III observations of stratospheric ozone during the Arctic winter of 2002-2003. Inferring chemical ozone loss from satellite data requires quantifying ozone variations due to dynamical processes. To accomplish this, the SLIMCAT model was run in a "passive" mode from early December until the middle of March. In these runs, ozone is treated as an inert, dynamical tracer. Chemical ozone loss is inferred by subtracting the model passive ozone, evaluated at the time and location of the POAM observations, from the POAM measurements themselves. This "CTM Passive Subtraction" technique relies on accurate initialization of the CTM and a realistic description of vertical/horizontal transport, both of which are explored in this work. The analysis suggests that chemical ozone loss during the 2002-2003 winter began in late December. This loss followed a prolonged period in which many polar stratospheric clouds were detected, and during which vortex air had been transported to sunlit latitudes. A series of stratospheric warming events starting in January hindered chemical ozone loss later in the winter of 2003. Nevertheless, by 15 March, the final date of the analysis, ozone loss maximized at 425K at a value of about 1.2ppmv, a moderate amount of loss compared to loss during the unusually cold winters in the late-1990s. SLIMCAT was also run with a detailed stratospheric chemistry scheme to obtain the model-predicted loss. The SLIMCAT model simulation also shows a maximum ozone loss of 1.2ppmv at 425K, and the morphology of the loss calculated by SLIMCAT was similar to that inferred from the POAM data. These results from the recently updated version of SLIMCAT therefore give a much better quantitative description of polar chemical ozone loss than older versions of the same model. Both the inferred and modeled loss calculations show the early destruction in late December and the region of maximum loss descending in altitude through the remainder of the winter and early spring.


2014 ◽  
Vol 14 (1) ◽  
pp. 177-198 ◽  
Author(s):  
E. Emili ◽  
B. Barret ◽  
S. Massart ◽  
E. Le Flochmoen ◽  
A. Piacentini ◽  
...  

Abstract. Accurate and temporally resolved fields of free-troposphere ozone are of major importance to quantify the intercontinental transport of pollution and the ozone radiative forcing. We consider a global chemical transport model (MOdèle de Chimie Atmosphérique à Grande Échelle, MOCAGE) in combination with a linear ozone chemistry scheme to examine the impact of assimilating observations from the Microwave Limb Sounder (MLS) and the Infrared Atmospheric Sounding Interferometer (IASI). The assimilation of the two instruments is performed by means of a variational algorithm (4D-VAR) and allows to constrain stratospheric and tropospheric ozone simultaneously. The analysis is first computed for the months of August and November 2008 and validated against ozonesonde measurements to verify the presence of observations and model biases. Furthermore, a longer analysis of 6 months (July–December 2008) showed that the combined assimilation of MLS and IASI is able to globally reduce the uncertainty (root mean square error, RMSE) of the modeled ozone columns from 30 to 15% in the upper troposphere/lower stratosphere (UTLS, 70–225 hPa). The assimilation of IASI tropospheric ozone observations (1000–225 hPa columns, TOC – tropospheric O3 column) decreases the RMSE of the model from 40 to 20% in the tropics (30° S–30° N), whereas it is not effective at higher latitudes. Results are confirmed by a comparison with additional ozone data sets like the Measurements of OZone and wAter vapour by aIrbus in-service airCraft (MOZAIC) data, the Ozone Monitoring Instrument (OMI) total ozone columns and several high-altitude surface measurements. Finally, the analysis is found to be insensitive to the assimilation parameters. We conclude that the combination of a simplified ozone chemistry scheme with frequent satellite observations is a valuable tool for the long-term analysis of stratospheric and free-tropospheric ozone.


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