The ozone profile records of a large number of limb and occultation satellite instruments are widely used to address several key questions in ozone research. Further progress in some domains depends on a more detailed understanding of these data sets, especially of their long-term stability and their mutual consistency. To this end, we made a systematic assessment of 14 limb and occultation sounders that, together, provide more than three decades of global ozone profile measurements. In particular, we considered the latest operational Level-2 records by SAGE II, SAGE III, HALOE, UARS MLS, Aura MLS, POAM II, POAM III, OSIRIS, SMR, GOMOS, MIPAS, SCIAMACHY, ACE-FTS and MAESTRO. Central to our work is a consistent and robust analysis of the comparisons against the ground-based ozonesonde and stratospheric ozone lidar networks. It allowed us to investigate, from the troposphere up to the stratopause, the following main aspects of satellite data quality: long-term stability, overall bias and short-term variability , together with their dependence on geophysical parameters and profile representation. In addition, it permitted us to quantify the overall consistency between the ozone profilers. Generally, we found that between 20 and 40 km the satellite ozone measurement biases are smaller than ±5 %, the short-term variabilities are less than 5-12 % and the drifts are at most ±5 % decade −1 (or even ±3 % decade −1 for a few records). The agreement with ground-based data degrades somewhat towards the stratopause and especially towards the tropopause where natural variability and low ozone abundances impede a more precise analysis. In part of the stratosphere a few records deviate from the preceding general conclusions ; we identified biases of 10 % and more (POAM II and SCIAMACHY), markedly higher single-profile variability (SMR and SCIAMACHY) and significant long-term drifts (SCIAMACHY, OSIRIS, HALOE and possibly GO-MOS and SMR as well). Furthermore, we reflected on the repercussions of our findings for the construction, analysis and interpretation of merged data records. Most notably, the discrepancies between several recent ozone profile trend assessments can be mostly explained by instrumental drift. This clearly demonstrates the need for systematic comprehensive multi-instrument comparison analyses.

International audienceUpper stratospheric ozone anomalies from the satellite-borne Solar Backscatter Ultra-Violet (SBUV), Stratospheric Aerosol and Gas Experiment II (SAGE II), Halogen Occultation Experiment (HALOE), Global Ozone Monitoring by Occultation of Stars (GOMOS), and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instruments agree within 5% or better with ground-based data from lidars and microwave radiometers at five stations of the Network for the Detection of Atmospheric Composition Change (NDACC), from 45°S to 48°N. From 1979 until the late 1990s, all available data show a clear decline of ozone near 40 km, by 10%–15%. This decline has not continued in the last 10 years. At some sites, ozone at 40 km appears to have increased since 2000, consistent with the beginning decline of stratospheric chlorine. The phaseout of chlorofluorocarbons after the International Montreal Protocol in 1987 has been successful, and is now showing positive effects on ozone in the upper stratosphere. Temperature anomalies near 40 km altitude from European Centre for Medium Range Weather Forecast reanalyses (ERA-40), from National Centers for Environmental Prediction (NCEP) operational analyses, and from HALOE and lidar measurements show good consistency at the five stations, within about 3 K. Since about 1985, upper stratospheric temperatures have been fluctuating around a constant level at all five NDACC stations. This non-decline of upper stratospheric temperatures is a significant change from the more or less linear cooling of the upper stratosphere up until the mid-1990s, reported in previous trend assessments. It is also at odds with the almost linear 1 K per decade cooling simulated over the entire 1979–2010 period by chemistry–climate models (CCMs). The same CCM simulations, however, track the historical ozone anomalies quite well, including the change of ozone tendency in the late 1990s

Abstract.A standardized approach for the definition and reporting of vertical resolution of the ozone and temperature lidar profiles contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed. Two standardized definitions homogeneously and unequivocally describing the impact of vertical filtering are recommended.The first proposed definition is based on the width of the response to a finite-impulse-type perturbation. The response is computed by convolving the filter coefficients with an impulse function, namely, a Kronecker delta function for smoothing filters, and a Heaviside step function for derivative filters. Once the response has been computed, the proposed standardized definition of vertical resolution is given by z = δz × H FWHM , where δz is the lidar's sampling resolution and H FWHM is the full width at half maximum (FWHM) of the response, measured in sampling intervals.The second proposed definition relates to digital filtering theory. After applying a Laplace transform to a set of filter coefficients, the filter's gain characterizing the effect of the filter on the signal in the frequency domain is computed, from which the cut-off frequency f C , defined as the frequency at which the gain equals 0.5, is computed. Vertical resolution is then defined by z = δz/(2f C ). Unlike common practice in the field of spectral analysis, a factor 2f C instead of f C is used here to yield vertical resolution values nearly equal to the values obtained with the impulse response definition using the same filter coefficients. When using either of the proposed definitions, unsmoothed signals yield the best possible vertical resolution z = δz (one sampling bin).Numerical tools were developed to support the implementation of these definitions across all NDACC lidar groups. The tools consist of ready-to-use "plug-in" routines written in several programming languages that can be inserted into any lidar data processing software and called each time a filtering operation occurs in the data processing chain.When data processing implies multiple smoothing operations, the filtering information is analytically propagated through the multiple calls to the routines in order for the standardized values of vertical resolution to remain theoretically and numerically exact at the very end of data processing.

The long-term evolution of stratospheric ozone at different stations in the low and mid-latitudes is investigated. The analysis is performed by comparing the collocated profiles of ozone lidars, at the northern mid-latitudes (Meteorological Observatory Hohenpeißenberg, Haute-Provence Observatory, Tsukuba and Table Mountain Facility), tropics (Mauna Loa Observatory) and southern mid-latitudes (Lauder), with ozonesondes and space-borne sensors (SBUV(/2), SAGE II, HALOE, UARS MLS and Aura MLS), extracted around the stations. Relative differences are calculated to find biases and temporal drifts in the measurements. All measurement techniques show their best agreement with respect to the lidar at 20–40 km, where the differences and drifts are generally within ±5% and ±0.5% yr⁻¹, respectively, at most stations. In addition, the stability of the long-term ozone observations (lidar, SBUV(/2), SAGE II and HALOE) is evaluated by the cross-comparison of each data set. In general, all lidars and SBUV(/2) exhibit near-zero drifts and the comparison between SAGE II and HALOE shows larger, but insignificant drifts. The RMS of the drifts of lidar and SBUV(/2) is 0.22 and 0.27% yr⁻¹, respectively at 20–40 km. The average drifts of the long-term data sets, derived from various comparisons, are less than ±0.3% yr⁻¹ in the 20–40 km altitude at all stations. A combined time series of the relative differences between SAGE II, HALOE and Aura MLS with respect to lidar data at six sites is constructed, to obtain long-term data sets lasting up to 27 years. The relative drifts derived from these combined data are very small, within ±0.2% yr⁻¹

Abstract.A standardized approach for the definition, propagation, and reporting of uncertainty in the ozone differential absorption lidar data products contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed. One essential aspect of the proposed approach is the propagation in parallel of all independent uncertainty components through the data processing chain before they are combined together to form the ozone combined standard uncertainty.The independent uncertainty components contributing to the overall budget include random noise associated with signal detection, uncertainty due to saturation correction, background noise extraction, the absorption cross sections of O 3 , NO 2 , SO 2 , and O 2 , the molecular extinction cross sections, and the number densities of the air, NO 2 , and SO 2 . The expression of the individual uncertainty components and their step-by-step propagation through the ozone differential absorption lidar (DIAL) processing chain are thoroughly estimated. All sources of uncertainty except detection noise imply correlated terms in the vertical dimension, which requires knowledge of the covariance matrix when the lidar signal is vertically filtered. In addition, the covariance terms must be taken into account if the same detection hardware is shared by the lidar receiver channels at the absorbed and non-absorbed wavelengths.The ozone uncertainty budget is presented as much as possible in a generic form (i.e., as a function of instrument performance and wavelength) so that all NDACC ozone DIAL investigators across the network can estimate, for their own instrument and in a straightforward manner, the expected impact of each reviewed uncertainty component. In addition, two actual examples of full uncertainty budget are provided, using nighttime measurements from the tropospheric ozone DIAL located at the Jet Propulsion Laboratory (JPL) Table Mountain Facility, California, and nighttime measurements from the JPL stratospheric ozone DIAL located at Mauna Loa Observatory, Hawai'i.