Significance of the drifts in terms of the chosen standard deviation .

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PSCs and heterogeneous chemistry

Normally, the stratosphere is very dry and cloudless even though a thin layer of aerosol (liquid-phase binary H2SO4/H2O droplets) is present in the lower stratosphere. But during polar night, when temperatures reach below 195K in 15–25km the background aerosols take up HNO3 and H2O and evolve into ternary HNO3/H2SO4/H2O droplets, referred to as PSCs (Carslaw et al., 1994). Figure 1.7 shows a photograph of the PSCs in the Antarctic stratosphere. PSCs are classified into three types, Type Ia, Type Ib and Type II, according to their physical state or optical properties and chemical composition. This classification is based on air-borne lidar measurements (lidar backscatter and depolarisation ratios for  PSCs) as the instrument is sensitive to the state of polarisation of the backscattered light (Browell et al., 1990; Felton et al., 2007). Type Ia PSCs are made up of crystals of ni- tric acid trihydrate [NAT – (HNO3. 3H2O)] and Type Ib consists of supercooled ternary  solutions (STS) of HNO3/H2SO4/H2O. Type II PSCs are frozen water ice non-spherical crystalline particles. During austral winter heterogeneous reactions occur on the surface of PSC particles and convert the reservoir species such as ClONO2 and BrONO2 into more active species. The principal heterogeneous reactions are given below. HCl(s) + ClONO2(g) → HNO3(s) + Cl2.

Equivalent Effective Stratospheric Chlorine

As seen in Sect. 1.3, Cly and Bry originated from the CFCs and halons are the main cause for the stratospheric ozone depletion. The quantification of the combined impact of Cly and Bry to destroy ozone is defined as the Equivalent Effective Stratospheric Chlorine (EESC). EESC = Cly + ®Bry (1.43).
where ® is the weighting factor that accounts for the greater effectiveness of Br in destructing ozone compared to that of Cl on a per-atom basis. It varies with latitude, altitude and time. As described in Sect. 1.3, even though the amount of Bry compounds is less than that of Cly, the Br catalytic cycle is more efficient in destroying ozone eventhough PSC surface is not required for the activation of Br catalytic cycle. In order to account for this, Bry contribution is scaled by a factor ® (WMO, 2007). The value of column ® varies in a range from 50 to 130 from the equator to the poles depending on season. The global annual mean value of ® is about 66. In the mid-latitudes, ® is estimated to be about 60 in the lower stratosphere and 5 in the upper stratosphere (Sinnhuber et al., 2009).
Stratospheric EESC at different regions is calculated from the surface measurements of tropospheric ODS abundances and taking into account for the transit times (or ages) and conversion of Cly and Bry. The extent of degradation of ODSs in the stratosphere is described by considering the mean stratospheric age of an air parcel (Newman et al., 2007). The mean age of air in the lower stratosphere is »3 years in the mid-latitudes and »5.5 years in the polar latitudes (Waugh and Hall, 2002; Newman et al., 2006). Therefore, EESC values are directly linked with the ODS emissions in the atmosphere. The discovery of the cause of polar ozone depletion led to the implementation of the Montreal Protocol in 1987 for controlling the vast emission of human-produced CFCs. Studies by Rinsland et al. (2003) and Lary et al. (2007) reported that levels of Cl and Br radicals are decreasing from the past decade onwards, which is clear from the EESC values too.

Ozone recovery : different stages of ozone evolution

The satellite and ground-based observations showed a clear decrease in ozone before the mid-1990s, a stabilisation and an increase afterwards. Figure 1.14 presents the temporal evolution of ozone showing the past, present and future ozone levels between 60±S and 60±N in 1960–2100. Because of the successful implementation of the Montreal Protocol and its amendments, the observations showed a slowing of stratospheric ozone decline and is considered as the first stage of ozone evolution. This first stage of ozone evolution is already revealed in several studies, referred in Sect. 1.5. The second stage of ozone evolution is considered as the onset of increase in ozone due to the reduction in ODSs. Since the mid- 1990s, the decline of ozone has completely stopped in the considered latitude regimes and the ozone levels start to stabilise. More recently, the ozone levels show a slight increase reflecting the second stage of ozone evolution. Now the main issue is to identify whether this increase in ozone is related to the ODS decrease or not.

The ozone lidar system at OHP

The ozone lidar system at OHP (43.93± N, 5.71± E) uses DIAL technique for measuring stratospheric ozone since 1986. Since then, various improvements have been made in the experimental set-up among which the most important one is the implementation of a new optical and electronic detector in 1993. The schematic picture of OHP ozone lidar system is shown in Fig. 2.1 and a detailed description of the new experimental set-up is discussed in the following sections.

Transmitter

The lidar system includes a Lambda Physik EMG 200 excimer laser for the ozone absorbed laser radiation at 308nm and the third harmonic of a continuum Nd:YAG laser for the reference wavelength at 355 nm. Excimer laser operates at 100 Hz and the output energy is 200 mJ/pulse. The Nd:YAG laser operates at 50 Hz and its output energy is adapted to provide a return signal equivalent to the on-line signal at 40km altitude, which results in an emitted pulse energy of »60 mJ. Additionally, two beam expanders are used to reduce the divergence of both lasers to 0.2 and 0.1 mrad at 308 and 355nm respectively.

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Ozone retrieval algorithm

The retrieval algorithm is generally based on the differential lidar equation formalism. First, to increase the signal-to-noise ratio, the lidar signals are time averaged during the measure- ment period (3–4 h in general), taken as the temporal resolution of the measurement. Then, a certain number of corrections such as background correction and dead time correction are applied to the averaged signals. The former term is related to the estimation of background light using linear or polynomial regression in the 80–150km altitude range, where the lidar signal is negligible. The latter term is linked with the saturation of photon counting used for the signal acquisition in the lower ranges. In addition to the differentiation, a low pass filter is used in the DIAL technique to account for the rapid decrease of signal-to-noise ratio in the higher altitudes (above 40 km). Generally, the ozone number density is computed from the difference in the derivative of the logarithm of each lidar signal fitted to a straight line, or to a second order polynomial or to higher order polynomials. At OHP, the second order polynomial fit is used to derive the ozone number density (Godin et al., 1999).
The Rayleigh high and low energy and Raman signals optimise the accuracy of the ozone profile in the upper, middle-low and lower stratosphere respectively. In background aerosol loading conditions, the low energy Rayleigh signals provide more vertically resolved profiles than the Raman signals in the lower stratosphere, but the use of these signals in the lowermost stratosphere is prevented by the saturation of the photon counters. Hence, a correction called pulse pile-up correction is applied to correct for this saturation. The equation used to compute the true photon count rate from the observed count rate is Pc = 1 + [(1 − x)Pr − 1] exp(−xPr).

Table of contents :

Acknowledgements
Acronym
Publications
Abstract
Résumé
Preface
List of Figures
List of Tables
1 Introduction 
1.1 Vertical structure of the atmosphere
1.2 Stratospheric ozone
1.2.1 Stratospheric chemistry
1.2.2 Dynamical processes
1.3 Ozone depletion issue
1.3.1 Antarctic ozone loss
1.3.2 Arctic ozone loss
1.3.3 Mid-latitude ozone loss
1.4 Equivalent Effective Stratospheric Chlorine
1.5 Present state of the ozone layer
1.5.1 Ozone total column measurements
1.5.2 Ozone vertical profile
1.6 Ozone recovery : different stages of ozone evolution
1.7 Ozone and climate
1.8 Conclusions
2 Ozone lidar measurements 
2.1 LIDAR
2.2 Ozone DIAL system
2.2.1 Retrieval
2.2.2 Precision
2.2.3 Error analysis
2.3 The ozone lidar system at OHP
2.3.1 Transmitter
2.3.2 Optical receiver
2.3.3 Detection and acquisition
2.3.4 Ozone retrieval algorithm
2.3.5 Features of OHP lidar measurements
2.4 Features of other NDACC lidar measurements
2.5 Sensitivity tests
2.5.1 Ozone absorption cross-section
2.5.2 Temperature and wavelength dependence of cross-section
2.5.3 Comparison between BP and BDM cross-sections
2.5.4 Comparison between BP and BDM ozone number densities
2.5.5 Temperature dependence of ozone retrieval
2.6 OHP lidar ozone retrieval using NCEP data
2.7 Summary
3 Stability of ozone measurements at OHP 
3.1 Ozone Measurements
3.1.1 Umkehr
3.1.2 Ozonesondes
3.1.3 SBUV(/2)
3.1.4 SAGE II
3.1.5 HALOE
3.1.6 GOMOS
3.1.7 MLS
3.2 Methodology
3.2.1 Data screening
3.2.2 Coincidence criteria
3.2.3 Data conversion
3.2.4 Data analysis
3.3 Vertical distribution of mean bias
3.3.1 Long-term data sets
3.3.2 Short-term data sets
3.4 Temporal evolution
3.4.1 Comparison of Umkehr with lidar
3.4.2 Comparison of ozonesondes with lidar
3.4.3 Comparison of SAGE II and HALOE with lidar
3.4.4 Comparison of SBUV(/2) with lidar
3.4.5 Comparison of MLS and GOMOS with lidar
3.5 Drift in ozone differences
3.5.1 Sensitivity of standard deviations
3.5.2 Significance of the drifts in terms of the chosen standard deviation .
3.6 Summary
4 Stability of ozone observations over NDACC lidar stations 
4.1 Ozonesonde measurements
4.2 Data analysis
4.2.1 Relative difference and mean bias
4.2.2 Data conversion
4.3 Average biases: comparison with lidar measurements
4.3.1 Correction factor
4.4 Relative drifts
4.4.1 Comparison with ozone lidar as reference
4.4.2 Comparison of lidar with SBUV(/2), SAGE II and HALOE as references
4.4.3 Comparison of SBUV(/2), SAGE II and HALOE
4.4.4 Average of the drifts of long-term measurements
4.5 Combined data: SAGE II, HALOE and Aura MLS
4.5.1 Time series
4.5.2 Relative drifts of the combined time series
4.6 Summary
5 Stratospheric ozone evolution in the northern mid-latitudes 
5.1 Explanatory variables
5.1.1 Quasi Biennial Oscillation
5.1.2 Solar flux
5.1.3 Aerosols
5.1.4 Eddy heat flux
5.1.5 North Atlantic Oscillation
5.1.6 PWLT and EESC : Ozone trend estimation methods
5.2 Multiple regression model and method
5.3 Ozone total column measurements
5.3.1 Evolution of ozone total column
5.3.2 Ozone anomaly
5.3.3 Comparison between Dobson and SAOZ at OHP: bias and drift
5.4 Multiple regression analysis of ozone total column at OHP
5.4.1 Contribution of proxies to ozone variability
5.4.2 Trends in ozone total column
5.5 Multiple regression analysis of ozone total column at MOHp
5.5.1 Contribution of proxies to ozone variability
5.5.2 Trends in ozone total column
5.6 Vertically resolved ozone observations at OHP
5.6.1 Stratospheric ozone evolution
5.6.2 Stratospheric ozone anomaly
5.6.3 Application of multiple regression
5.6.4 Contribution of proxies to the variability of ozone profiles
5.6.5 Trends in stratospheric ozone vertical profiles
5.7 Connection between ozone profile and column measurements
5.8 Summary
6 Summary, conclusions and perspectives 
6.1 Summary and conclusions
6.2 Perspectives
Bibliography 

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