scholarly journals Solar response in tropical stratospheric ozone: a 3-D chemical transport model study using ERA reanalyses

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.

2011 ◽  
Vol 11 (5) ◽  
pp. 13975-14001 ◽  
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-year 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 1978–2005 time period. We have compared the modelled solar response in ozone to observational data from three satellite instruments, 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 ERA-40. Overall both standard model simulations are partially able to simulate a "double peak"-structured ozone solar response profile with a minimum around 30 km, and these are in better agreement with HALOE than SBUV or SAGE. The largest model-observation differences occur in the upper stratosphere where SBUV and SAGE 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 stratosphere analysed temperatures which reduces the modelled ozone signal. The large positive upper stratosphere response seen in SAGE/SBUV can be reproduced in a model run with fixed dynamical fields (i.e. no inter-annual meteorological changes). As this run effectively assumes 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 upper stratosphere ozone solar response is limited by differences in the observed dataset and by uncertainties in the solar response in the stratospheric temperatures. In the lower stratosphere we find that transport by analysed winds, which contain information about the Quasi-Biennial Oscillation (QBO), can lead to a large ozone solar response. However, the run with fixed dynamical fields also produces a positive solar response (up to 2 %) in line with the SAGE and SBUV observations.


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).


2015 ◽  
Vol 15 (2) ◽  
pp. 829-843 ◽  
Author(s):  
T. Sakazaki ◽  
M. Shiotani ◽  
M. Suzuki ◽  
D. Kinnison ◽  
J. M. Zawodny ◽  
...  

Abstract. This paper contains a comprehensive investigation of the sunset–sunrise difference (SSD, i.e., the sunset-minus-sunrise value) of the ozone mixing ratio in the latitude range of 10° S–10° N. SSD values were determined from solar occultation measurements based on data obtained from the Stratospheric Aerosol and Gas Experiment (SAGE) II, the Halogen Occultation Experiment (HALOE), and the Atmospheric Chemistry Experiment–Fourier transform spectrometer (ACE–FTS). The SSD was negative at altitudes of 20–30 km (−0.1 ppmv at 25 km) and positive at 30–50 km (+0.2 ppmv at 40–45 km) for HALOE and ACE–FTS data. SAGE II data also showed a qualitatively similar result, although the SSD in the upper stratosphere was 2 times larger than those derived from the other data sets. On the basis of an analysis of data from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and a nudged chemical transport model (the specified dynamics version of the Whole Atmosphere Community Climate Model: SD–WACCM), we conclude that the SSD can be explained by diurnal variations in the ozone concentration, particularly those caused by vertical transport by the atmospheric tidal winds. All data sets showed significant seasonal variations in the SSD; the SSD in the upper stratosphere is greatest from December through February, while that in the lower stratosphere reaches a maximum twice: during the periods March–April and September–October. Based on an analysis of SD–WACCM results, we found that these seasonal variations follow those associated with the tidal vertical winds.


2012 ◽  
Vol 12 (15) ◽  
pp. 7073-7085 ◽  
Author(s):  
J. Kuttippurath ◽  
S. Godin-Beekmann ◽  
F. Lefèvre ◽  
G. Nikulin ◽  
M. L. Santee ◽  
...  

Abstract. We present a detailed discussion of the chemical and dynamical processes in the Arctic winters 1996/1997 and 2010/2011 with high resolution chemical transport model (CTM) simulations and space-based observations. In the Arctic winter 2010/2011, the lower stratospheric minimum temperatures were below 195 K for a record period of time, from December to mid-April, and a strong and stable vortex was present during that period. Simulations with the Mimosa-Chim CTM show that the chemical ozone loss started in early January and progressed slowly to 1 ppmv (parts per million by volume) by late February. The loss intensified by early March and reached a record maximum of ~2.4 ppmv in the late March–early April period over a broad altitude range of 450–550 K. This coincides with elevated ozone loss rates of 2–4 ppbv sh−1 (parts per billion by volume/sunlit hour) and a contribution of about 30–55% and 30–35% from the ClO-ClO and ClO-BrO cycles, respectively, in late February and March. In addition, a contribution of 30–50% from the HOx cycle is also estimated in April. We also estimate a loss of about 0.7–1.2 ppmv contributed (75%) by the NOx cycle at 550–700 K. The ozone loss estimated in the partial column range of 350–550 K exhibits a record value of ~148 DU (Dobson Unit). This is the largest ozone loss ever estimated in the Arctic and is consistent with the remarkable chlorine activation and strong denitrification (40–50%) during the winter, as the modeled ClO shows ~1.8 ppbv in early January and ~1 ppbv in March at 450–550 K. These model results are in excellent agreement with those found from the Aura Microwave Limb Sounder observations. Our analyses also show that the ozone loss in 2010/2011 is close to that found in some Antarctic winters, for the first time in the observed history. Though the winter 1996/1997 was also very cold in March–April, the temperatures were higher in December–February, and, therefore, chlorine activation was moderate and ozone loss was average with about 1.2 ppmv at 475–550 K or 42 DU at 350–550 K, as diagnosed from the model simulations and measurements.


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.


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 (19) ◽  
pp. 10113-10123 ◽  
Author(s):  
S. S. Dhomse ◽  
M. P. Chipperfield ◽  
W. Feng ◽  
W. T. Ball ◽  
Y. C. Unruh ◽  
...  

Abstract. Solar spectral fluxes (or irradiance) measured by the SOlar Radiation and Climate Experiment (SORCE) show different variability at ultraviolet (UV) wavelengths compared to other irradiance measurements and models (e.g. NRL-SSI, SATIRE-S). Some modelling studies have suggested that stratospheric/lower mesospheric O3 changes during solar cycle 23 (1996–2008) can only be reproduced if SORCE solar fluxes are used. We have used a 3-D chemical transport model (CTM), forced by meteorology from the European Centre for Medium-Range Weather Forecasts (ECMWF), to simulate middle atmospheric O3 using three different solar flux data sets (SORCE, NRL-SSI and SATIRE-S). Simulated O3 changes are compared with Microwave Limb Sounder (MLS) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) satellite data. Modelled O3 anomalies from all solar flux data sets show good agreement with the observations, despite the different flux variations. The off-line CTM reproduces these changes through dynamical information contained in the analyses. A notable feature during this period is a robust positive solar signal in the tropical middle stratosphere, which is due to realistic dynamical changes in our simulations. Ozone changes in the lower mesosphere cannot be used to discriminate between solar flux data sets due to large uncertainties and the short time span of the observations. Overall this study suggests that, in a CTM, the UV variations detected by SORCE are not necessary to reproduce observed stratospheric O3 changes during 2001–2010.


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.


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