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Ozone profiles derived from ground-based Umkehr measurements at five stations and from the merged data set of Solar Backscattered Ultra Violet (SBUVv8) satellite observations are used to estimate the seasonal influence of the 11-year solar signal in the vertical distribution of stratospheric ozone. Both data sets show a strong response (2-3% of the...
Contexts in source publication
Context 1
... The SBUV(/2) version 8 Merged Ozone Data Set (here- after SBUVmod) has been used in this study. The data, pro- vided by the TOMS science team, are available as profiles of ozone layer amounts in Dobson Units (DU) for 13 layers shown in Table 1. The record spans over 25 years , and consists of monthly mean ozone values zonally averaged over 5° latitude belts. ...
Context 2
... this region, measurements are known to be influ- enced by the total ozone amount and a priori assumptions in the case of SBUV [Bhartia et al., 1996], or the total ozone amount and interdependence between layers [Bojkov et al., 2002 and references therein]. As the Umkehr layers do not precisely coincide with the SBUVmod layers (Tables 1 and 2), to allow for better comparison all results presented in Figures 1, 2, and 3 are plotted against the approximate altitude of the layers' midpoint. ...
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The ozone data obtained from Total Ozone Mapping Spectrometer (TOMS) and Solar Back scatter Ultra Violet spectrometer (SBUV) on Nimbus 7 satellite have been used to study the variability of the total column amount of ozone and ozone concentration in different atmospheric layers respectively at Rajkot (22.3 0 N, 70.8 0 E) over a period from 1980 20...
Abstract
Monitoring of ultra violet (UV) radiation reaching the earth's surface has gained a lot of interest in view of the documentation that 1% decrease in ozone (O3) brings about 1.2 to 1.5% increase in biologically harmful ultra violet (UV) radiation. No continuous monitoring of UV radiation is performed in the equatorial African region. This...
Citations
... The asymmetry towards the summer hemisphere for both December-February (DJF, the Southern Hemisphere) and June-August (JJA, the Northern Hemisphere) suggests an origin involving a solar modulation of the BDC [39] because the upwelling branch of the BDC is limited to low and subtropical latitudes and is also shifted somewhat toward the summer hemisphere. The magnitude of the interhemispheric asymmetry also varies with season as was noted by Soukharev and Hood [44] and Tourpali et al. [45]. ...
... Outside the tropics, the most notable feature takes place in the lower and middle stratosphere with displacement of the solar cycle signal to the SH extratropics leading to the clear hemispheric asymmetry in L9-L10 (25-31 km, Figure 8b,c). Hemispheric asymmetry in the solar activity-ozone response was noted earlier [33,44,45]. In Figure 8b,c, the maximum solar signal in the high southern latitudes appears in autumn and spring. ...
The 11-year solar activity cycle in the vertical ozone distribution over the Antarctic station Faraday/Vernadsky in the Antarctic Peninsula region (65.25° S, 64.27° W) was analyzed using the Solar Backscatter Ultra Violet (SBUV) radiometer data Version 8.6 Merged Ozone Data Sets (MOD) over the 40-year period 1979-2018. The SBUV MOD ozone profiles are presented as partial column ozone in layers with approximately 3-km altitude increments from the surface to the lower mesosphere (1000-0.1 hPa, or 0-64 km). Periodicities in the ozone time series of the layer data were studied using wavelet transforms. A statistically significant signal with a quasi-11-year period consistent with solar activity forcing was found in the lower-middle stratosphere at 22-31 km in ozone over Faraday/Vernadsky, although signals with similar periods were not significant in the total column measurements made by the Dobson spectrophotometer at the site. For comparison with other latitudinal zones, the relative contribution of the wavelet spectral power of the quasi-11-year periods to the 2-33-year period range on the global scale was estimated. While a significant solar activity signal exists in the tropical lower and upper stratosphere and in the lower mesosphere in SBUV MOD, we did not find evidence of similar signals in the ozone forcing data for the Coupled Model Intercomparison Project Phase 6 (CMIP6). In the extratropical lower-middle stratosphere and lower mesosphere, there is a strong hemispheric asymmetry in solar activity-ozone response, which is dominant in the Southern Hemisphere. In general, the results are consistent with other studies and highlight the sensitivity of ozone in the lower-middle stratosphere over the Antarctic Peninsula region to the 11-year solar cycle.
... This solar-cycle-induced ozone response provides an additional source of stratospheric heating (Haigh, 1994). Solar-cycle-induced changes in stratospheric ozone over its 11-year cycle of between ∼ 1 % and ∼ 5 %-6 % have been reported from the analysis of various satellite (Soukharev and Hood, 2006;Tourpali et al., 2007;Dhomse et al., 2013Dhomse et al., , 2016Maycock et al., 2016) and ground-based records (Tourpali et al., 2007). These, alongside changes in incoming solar UV radiation over the 11-year solar cycle, alter stratospheric temperatures (e.g. ...
... This solar-cycle-induced ozone response provides an additional source of stratospheric heating (Haigh, 1994). Solar-cycle-induced changes in stratospheric ozone over its 11-year cycle of between ∼ 1 % and ∼ 5 %-6 % have been reported from the analysis of various satellite (Soukharev and Hood, 2006;Tourpali et al., 2007;Dhomse et al., 2013Dhomse et al., , 2016Maycock et al., 2016) and ground-based records (Tourpali et al., 2007). These, alongside changes in incoming solar UV radiation over the 11-year solar cycle, alter stratospheric temperatures (e.g. ...
The 11-year solar cycle forcing is recognised as an important atmospheric forcing; however, there remain uncertainties in characterising the effects of solar variability on the atmosphere from observations and models. Here we present the first detailed assessment of the atmospheric response to the 11-year solar cycle in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol model) chemistry–climate model (CCM) using a three-member ensemble over the recent past (1966–2010). Comparison of the model simulations is made with satellite observations and reanalysis datasets. The UM-UKCA model produces a statistically significant response to the 11-year solar cycle in stratospheric temperatures, ozone and zonal winds. However, there are also differences in magnitude, spatial structure and timing of the signals compared to observational and reanalysis estimates. This could be due to deficiencies in the model performance, and so we include a critical discussion of the model limitations, and/or uncertainties in the current observational estimates of the solar cycle signals. Importantly, in contrast to many previous studies of the solar cycle impacts, we pay particular attention to the role of the chosen analysis method in UM-UKCA by comparing the model composite and a multiple linear regression (MLR) results. We show that the stratospheric solar responses diagnosed using both techniques largely agree with each other within the associated uncertainties; however, the results show that apparently different signals can be identified by the methods in the troposphere and in the tropical lower stratosphere. Lastly, we examine how internal atmospheric variability affects the detection of the 11-year solar responses in the model by comparing the results diagnosed from the three individual ensemble members (as opposed to those diagnosed from the full ensemble). We show overall agreement between the responses diagnosed for the ensemble members in the tropical and mid-latitude mid-stratosphere to lower mesosphere but larger apparent differences at Northern Hemisphere (NH) high latitudes during the dynamically active season. Our UM-UKCA results suggest the need for long data sets for confident detection of solar cycle impacts in the atmosphere, as well as for more research on possible interdependence of the solar cycle forcing with other atmospheric forcings and processes (e.g. Quasi-Biennial Oscillation, QBO; El Niño–Southern Oscillation, ENSO).
... Dennison et al.: UKCA stratospheric chemistry icant effect on stratospheric ozone (e.g. Zerefos et al., 1997;Calisesi and Matthes, 2006;Tourpali et al., 2007;Kuroda et al., 2008;Gruzdev, 2014). Specifically, studies such as Dameris et al. (2006), Steinbrecht et al. (2004) and Keeble et al. (2018) make the point that ozone increases in the early 2000s were caused by the Sun going through its solar maximum and did not constitute evidence of ozone recovery due to reductions in stratospheric halogen. ...
... The importance of simulating the solar cycle in chemistryclimate models (CCMs) has been noted by a number of studies (e.g. Egorova et al., 2005;Langematz et al., 2005;Tourpali et al., 2003;Labitzke et al., 2002). Of the 20 CCMs participating in the first phase of the Chemistry-Climate Model Initiative (CCMI-1), only three did not consider solar variability (Morgenstern et al., 2017). ...
Improvements are made to two areas of the United Kingdom Chemistry and
Aerosol (UKCA) module, which forms part of the Met Office Unified Model (UM)
used for weather and climate applications. Firstly, a solar cycle is added to
the photolysis scheme. The effect on total column ozone of this addition was
found to be around 1 %–2 % in midlatitude and equatorial regions, in
phase with the solar cycle. Secondly, reactions occurring on the surfaces of
polar stratospheric clouds and sulfate aerosol are updated and extended by
modification of the uptake coefficients of five existing reactions and the
addition of a further eight reactions involving bromine species. These
modifications are shown to reduce the overabundance of modelled total column
ozone in the Arctic during October to February, southern midlatitudes during
August and the Antarctic during September. Antarctic springtime ozone
depletion is shown to be enhanced by 25 DU on average, which now causes the
ozone hole to be somewhat too deep compared to observations. We show that
this is in part due to a cold bias of the Antarctic polar vortex in the
model.
... Ossó et al., 2011;Chehade et al., 2014), and the 11-year solar cycle (e.g. Zerefos et al., 2001;Tourpali et al., 2007;Brönniman et al., 2013). Moreover, volcanic eruptions may also alter the thickness of the ozone layer (Zerefos et al., 1994;Rieder et al., 2013;WMO, 2014). ...
In this work we present evidence that quasi-cyclical perturbations in total
ozone (quasi-biennial oscillation – QBO, El Niño–Southern Oscillation –
ENSO, and North Atlantic Oscillation – NAO) can be used as independent proxies in
evaluating Global Ozone Monitoring Experiment (GOME) 2 aboard MetOp A
(GOME-2A)
satellite total ozone data, using ground-based (GB) measurements, other satellite
data, and chemical transport model calculations. The analysis is performed in
the frame of the validation strategy on longer time scales within the
European Organisation for the Exploitation of Meteorological Satellites
(EUMETSAT) Satellite Application Facility on Atmospheric Composition
Monitoring (AC SAF) project, covering the period 2007–2016. Comparison of
GOME-2A total ozone with ground observations shows mean differences of about
-0.7±1.4 % in the tropics (0–30∘), about +0.1±2.1 % in the mid-latitudes (30–60∘), and about +2.5±3.2 % and
0.0±4.3 % over the northern and southern high latitudes (60–80∘), respectively. In general, we find that GOME-2A total ozone data depict
the QBO–ENSO–NAO
natural fluctuations in concurrence with the co-located solar
backscatter ultraviolet radiometer (SBUV), GOME-type Total Ozone Essential
Climate Variable (GTO-ECV; composed of total ozone observations from GOME, SCIAMACHY – SCanning Imaging Absorption
SpectroMeter for Atmospheric CHartographY, GOME-2A, and OMI – ozone
monitoring instrument, combined into one homogeneous time series), and
ground-based observations. Total ozone from GOME-2A is well correlated
with the QBO (highest correlation in the tropics of +0.8) in agreement with
SBUV, GTO-ECV, and GB data which also give the highest correlation in the
tropics. The differences between deseazonalized GOME-2A and GB total ozone in
the tropics are within ±1 %. These differences were tested further
as to their correlations with the QBO. The differences had practically no QBO
signal, providing an independent test of the stability of the long-term
variability of the satellite data. Correlations between GOME-2A total ozone
and the Southern Oscillation Index (SOI) were studied over the tropical
Pacific Ocean after removing seasonal, QBO, and solar-cycle-related
variability. Correlations between ozone and the SOI are on the order of +0.5,
consistent with SBUV and GB observations. Differences between GOME-2A and GB
measurements at the station of Samoa (American Samoa; 14.25∘ S,
170.6∘ W) are within ±1.9 %. We also studied the impact of the NAO
on total ozone in the northern mid-latitudes in winter. We find very good
agreement between GOME-2A and GB observations over Canada and Europe as to
their NAO-related variability, with mean differences reaching the ±1 % levels. The agreement and small differences which were found between
the independently produced total ozone datasets as to the influence of the QBO, ENSO, and NAO show the importance of these climatological proxies as
additional tool for monitoring the long-term stability of satellite–ground-truth
biases.
... There are many factors that cause variation in TCO such as solar cycle, quasi-biennial-oscillation (QBO), El Niño-southern oscillation (ENSO), stratospheric wind, mixing of ozone from troposphere to stratosphere, etc (Angell, 1989;Labitzke and Van Loon, 1997;Tourpali et al., 2007;Fadnavis et al., 2007;Beig, 2008, 2010;Randel et al., 2009;Singh et al., 2002;Siingh et al., 2011;Ningombam, 2011;Dhomse et al., 2016;Patil et al., 2018). Apart from these factors local variability, aerosol loading and anthropogenic emissions are also responsible for the variation in TCO. ...
Total column ozone (TCO) distribution and its variation over the Indian region at different stations for the period of about 30 years from 1986 to 2015 are studied. TCO data is taken from the merged ozone data set (MOD) overpass data for 15 different stations over India. The average correlation between TCO and solar proxies such as sunspot number and F10.7 cm solar flux is more than 0.5. We further divided the time series of TCO according to solar cycle as 22 nd solar cycle (and 24 th solar cycle (December 2008 to December 2015) (on going cycle) for a period of 1986-2015. Herein, for the long term trend analysis of TCO, we have removed the seasonal effect by the deseasonalization process, the effects of solar activities, stratospheric waves (quasi-biennial-oscillation-QBO and El Niño-Southern Oscillation -ENSO) by the multifunction linear regression method (MLR). We have compared both the linear trends in TCO which are calculated by the simple linear regression (SLR) and deseasonalised multifunction linear regression (DMLR) analysis. It is found that the direction of the trend in 22 nd and the 23 rd solar cycle is similar while, it is opposite in the 24 th solar cycle. We observed a more negative trend in the 22 nd solar cycle and less negative trend in the 23 rd solar cycle while the trend is positive in the 24 th solar cycle. The results indicate that after the DMLR process, the trend values are decreased by a large factor. Therefore, it is found that the role of natural variability is more than that of the ozone depleting substances (ODS) on long term variability in TCO over India. This statistical analysis provides better analysis of trend variation in TCO series over India. The main objective of this work is to analyze the variations in trend in the TCO with respect to the recent three solar cycles.
... Staehelin et al., 2001, and references therein). In the context of extracting the SOR from ozone time series, there is a long history of similar methods being applied to both satellite observations (e.g., Soukharev and Hood, 2006;Remsberg, 2008;Tourpali et al., 2007;Remsberg and Lingenfelser, 2010;Dhomse et al., 2016;Lee and Smith, 2003;Lean, 2014;Randel and Wu, 2007;Merkel et al., 2011;Maycock et al., 2016) and CCMs (Austin et al., 2008;Sekiyama et al., 2006;Lee and Smith, 2003;Egorova et al., 2014;Dhomse et al., 2011Dhomse et al., , 2016Hood et al., 2015;SPARC CCMVal, 2010). Here we follow the methodology described by Maycock et al. (2016), which is very similar to the methods described in those earlier studies. ...
The impact of changes in incoming solar irradiance on stratospheric ozone abundances should be included in climate
simulations to aid in capturing the atmospheric response to solar cycle variability. This study presents the first
systematic comparison of the representation of the 11-year solar cycle ozone response (SOR) in chemistry–climate models
(CCMs) and in pre-calculated ozone databases specified in climate models that do not include chemistry, with a special
focus on comparing the recommended protocols for the Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5 and CMIP6).
We analyse the SOR in eight CCMs from the Chemistry–Climate Model Initiative (CCMI-1)
and compare these with results from three ozone databases for climate models:
the Bodeker Scientific ozone database, the SPARC/Atmospheric Chemistry and Climate (AC&C) ozone database for CMIP5 and the SPARC/CCMI ozone database for
CMIP6. The peak amplitude of the annual mean SOR in the tropical upper stratosphere (1–5 hPa) decreases by more than
a factor of 2, from around 5 to 2 %, between the CMIP5 and CMIP6 ozone databases. This substantial decrease can be
traced to the CMIP5 ozone database being constructed from a regression model fit to satellite and ozonesonde measurements,
while the CMIP6 database is constructed from CCM simulations. The SOR in the CMIP6 ozone database therefore
implicitly resembles the SOR in the CCMI-1 models. The structure in latitude of the SOR in the CMIP6 ozone database and
CCMI-1 models is considerably smoother than in the CMIP5 database, which shows unrealistic sharp gradients in the SOR
across the middle latitudes owing to the paucity of long-term ozone measurements in polar regions. The SORs in the CMIP6
ozone database and the CCMI-1 models show a seasonal dependence with enhanced meridional gradients at mid- to high
latitudes in the winter hemisphere. The CMIP5 ozone database does not account for seasonal variations in the SOR, which is
unrealistic. Sensitivity experiments with a global atmospheric model without chemistry (ECHAM6.3) are performed to assess
the atmospheric impacts of changes in the representation of the SOR and solar spectral irradiance (SSI) forcing between
CMIP5 and CMIP6. The larger amplitude of the SOR in the CMIP5 ozone database compared to CMIP6 causes a likely
overestimation of the modelled tropical stratospheric temperature response between 11-year solar cycle minimum and
maximum by up to 0.55 K, or around 80 % of the total amplitude. This effect is substantially larger than the change
in temperature response due to differences in SSI forcing between CMIP5 and CMIP6. The results emphasize the importance of
adequately representing the SOR in global models to capture the impact of the 11-year solar cycle on the
atmosphere. Since a number of limitations in the representation of the SOR in the CMIP5 ozone database have been
identified, we recommend that CMIP6 models without chemistry use the CMIP6 ozone database and the CMIP6 SSI dataset to
better capture the climate impacts of solar variability. The SOR coefficients from the CMIP6 ozone database are published with this
paper.
... This solarinduced ozone response provides an additional source of stratospheric heating (Haigh, 1994). Solar-induced variability of stratospheric ozone abundances between ~1% and ~5-6% has been reported from the analysis of various satellite (Soukharev and Hood, 2006;Tourpali et al., 2007;Dhomse et al., 2013;2016;Maycock et al., 2016;2017) and ground-based records (Tourpali et al., 2007). These, alongside changes in incoming solar UV radiation over the 11-year 25 solar cycle, alter stratospheric temperatures (e.g. ...
... This solarinduced ozone response provides an additional source of stratospheric heating (Haigh, 1994). Solar-induced variability of stratospheric ozone abundances between ~1% and ~5-6% has been reported from the analysis of various satellite (Soukharev and Hood, 2006;Tourpali et al., 2007;Dhomse et al., 2013;2016;Maycock et al., 2016;2017) and ground-based records (Tourpali et al., 2007). These, alongside changes in incoming solar UV radiation over the 11-year 25 solar cycle, alter stratospheric temperatures (e.g. ...
The 11-year solar cycle forcing is recognised as a potentially important atmospheric forcing; however, there remain uncertainties in characterising the effects of the solar variability on the atmosphere from observations and models. Here we present the first detailed assessment of the atmospheric response to the 11-year solar cycle in the UM-UKCA chemistry-climate model using an ensemble of integrations over the recent past. Comparison of the model simulations is made with observations and reanalysis. Importantly, in contrast to the majority of previous studies of the solar cycle impacts, we pay particular attention to the role of detection method by comparing the results diagnosed using both a composite and a multiple linear regression method. We show that stratospheric solar responses diagnosed using both techniques largely agree with each other within the associated uncertainties; however, the results show that apparently different signals can be identified by the methods in the troposphere and in the tropical lower stratosphere. Lastly, we focus on the role of internal atmospheric variability on the detection of the 11-year solar responses by comparing the results diagnosed from individual model ensemble members (as opposed to those diagnosed from the full ensemble). We show overall agreement between the ensemble members in the tropical and mid-latitude mid-stratosphere-to-lower-mesosphere, but larger apparent differences at NH high latitudes during the dynamically active season. Our results highlight the need for long data sets for confident detection of solar cycle impacts in the atmosphere, as well as for more research on possible interdependence of the solar cycle forcing with other atmospheric forcings and processes (e.g. QBO, ENSO… etc.).
... It is in this 23-32 km layer for subtropical stations that the solar cycle shows the most important contribution (Fig. 4). This is not what has been reported in Randel and Wu (2007) and Tourpali et al. (2007), where the ozone response to the solar cycle was maximum in the tropical lower and upper stratosphere, and minimum in the middle stratosphere. At Wollongong, the middle stratospheric ozone response is about 6 % between solar minimum and solar maximum (see Fig. 9) while values of 1 % have been reported (Sioris et al., 2014) at about 25 km. ...
Ground-based Fourier transform infrared (FTIR) measurements of solar
absorption spectra can provide ozone total columns with a precision of
2% but also independent partial column amounts in about four
vertical layers, one in the troposphere and three in the stratosphere up to
about 45km, with a precision of 5–6%. We use eight of the
Network for the Detection of Atmospheric Composition Change (NDACC) stations
having a long-term time series of FTIR ozone measurements to study the total
and vertical ozone trends and variability, namely, Ny-Ålesund
(79° N), Thule (77° N), Kiruna (68° N), Harestua
(60° N), Jungfraujoch (47° N), Izaña (28° N),
Wollongong (34° S) and Lauder (45° S). The length of the
FTIR time series varies by station but is typically from about 1995 to
present. We applied to the monthly means of the ozone total and four partial
columns a stepwise multiple regression model including the following proxies:
solar cycle, quasi-biennial oscillation (QBO), El Niño–Southern Oscillation
(ENSO), Arctic and Antarctic Oscillation (AO/AAO), tropopause pressure (TP),
equivalent latitude (EL), Eliassen–Palm flux (EPF), and volume of polar
stratospheric clouds (VPSC).
At the Arctic stations, the trends are found mostly negative in the troposphere and
lower stratosphere, very mixed in the middle stratosphere, positive in the upper stratosphere
due to a large increase in the 1995–2003 period, and non-significant when considering the
total columns. The trends for mid-latitude and subtropical stations are all non-significant,
except at Lauder in the troposphere and upper stratosphere and at Wollongong for the total
columns and the lower and middle stratospheric columns where they are found positive. At
Jungfraujoch, the upper stratospheric trend is close to significance (+0.9 ± 1.0% decade−1).
Therefore, some signs of the onset of ozone mid-latitude recovery are observed only in the
Southern Hemisphere, while a few more years seem to be needed to observe it at the
northern mid-latitude station.
... It is in this 23-32 km layer for subtropical stations that the solar cycle shows the most important contribution (Fig. 4). This is not what has been reported in Randel and Wu (2007) Tourpali et al. (2007), where the ozone response to solar cycle was maximum in the tropical lower and upper stratosphere, and minimum in the middle stratosphere. At Wollongong, the middle stratospheric ozone response is about 6 % between solar minimum and solar maximum (see Fig. 9) while values of 1 % have been reported (Sioris et al., 2014) at about 25 km. ...
Ground-based Fourier transform infrared (FTIR) measurements of solar
absorption spectra can provide ozone total columns with a precision of
2%, but also independent partial column amounts in about four
vertical layers, one in the troposphere and three in the stratosphere up to
about 45 km, with a precision of 5–6%. We use eight of the
Network for the Detection of Atmospheric Compososition Change (NDACC) stations
having a long-term time series of FTIR ozone measurements to study the total
and vertical ozone trends and variability, namely: Ny-Alesund
(79° N), Thule (77° N), Kiruna (68° N), Harestua
(60° N), Jungfraujoch (47° N), Izaña (28° N),
Wollongong (34° S) and Lauder (45° S). The length of the
FTIR time-series varies by station, but is typically from about 1995 to
present. We applied to the monthly means of the ozone total and four partial
columns a stepwise multiple regression model including the following proxies:
solar cycle, Quasi-Biennial Oscillation (QBO), El Niño-Southern Oscillation
(ENSO), Arctic and Antarctic Oscillation (AO/AAO), tropopause pressure (TP),
equivalent latitude (EL), Eliassen-Palm flux (EPF), and volume of polar
stratospheric clouds (VPSC).
At the Arctic stations, the trends are found mostly negative in the troposphere and lower stratosphere, very mixed in the middle stratosphere, positive in the upper stratosphere due to a large increase in the 1995–2003 period, and non-significant when considering the total columns. The trends for mid-latitude and subtropical stations are all non-significant, except at Lauder in the troposphere and upper stratosphere, and at Wollongong for the total columns and the lower and middle stratospheric columns; at Jungfraujoch, the upper stratospheric trend is close to significance (+0.9 ± 1.0 % decade−1). Therefore, some signs of the onset of ozone mid-latitude recovery are observed only in the Southern Hemisphere, while a few more years seems to be needed to observe it at the northern mid-latitude station.
... Since the Pinatubo aerosol layer was present near solar-UV maximum, it is very likely that the effects of the scattering completely canceled the effects of the enhanced solar-UV flux. It is noted that SH did not exclude any SBUV data following the volcanic events of El Chichon and Pinatubo for their analyses, while Tourpali et al. (2007) deleted data for 1982 and 1991. RW were more conservative for their regression studies; they deleted two years of their merged SBUV v8 ozone following both volcanic events. ...
Stratospheric Aerosol and Gas Experiment (SAGE II) version 7 (v7) ozone profiles are analyzed for their decadal-scale responses and linear trends in the middle and upper stratosphere for the two periods of 1984 to 1998 and 1991 to 2005. Multiple linear regression (MLR) analysis is applied to time series of the v7 ozone number density vs. altitude data for a range of latitudes and altitudes. The MLR models that are fit to the data include a periodic 11 yr term, and it is in-phase with that of the 11-yr, solar uv-flux throughout most of the latitude/altitude domain of the middle and upper stratosphere. Max minus min, solar cycle (SC-like) responses for the SAGE II ozone at those altitudes and for the low to middle latitudes are similar for 1984–1998 and for 1991–2005 and of the order of 5 to 2.5% from 35 to 50 km. This finding is important because the associated linear trend terms are clearly different from the MLR models of those two time spans. The SAGE II results for the upper stratosphere are also compared with those of the Halogen Occultation Experiment (HALOE) in terms of mixing ratio vs. pressure. The shapes of their respective, SC-like response profiles agree well for a time series from late 1992–2005, or after excluding the first 14 months of data following the Pinatubo eruption. Max minus min, SC-like responses from the SAGE II and HALOE time series vary from 2 to 4% and from 0 to 2%, respectively, and their differences in the upper stratosphere can be accounted for using the analyzed, SC-like response of the HALOE temperatures. The linear ozone trends of the upper stratosphere for 1992–2005 vary from about 0 to −4% decade−1 from the Southern to the Northern Hemisphere from SAGE II, while they vary from 0 to −2% decade−1 and are more nearly symmetric about the Equator from HALOE.
