Abstract

Abstract. In the framework of the SI2N (SPARC (Stratosphere-troposphere Processes And their Role in Climate)/IO3C (International Ozone Commission)/IGACO-O3 (Integrated Global Atmospheric Chemistry Observations – Ozone)/NDACC (Network for the Detection of Atmospheric Composition Change)) initiative, several long-term vertically resolved merged ozone data sets produced from satellite measurements have been analysed and compared. This paper presents an overview of the methods, assumptions, and challenges involved in constructing such merged data sets, as well as the first thorough intercomparison of seven new long-term satellite data sets. The analysis focuses on the representation of the annual cycle, interannual variability, and long-term trends for the period 1984–2011, which is common to all data sets. Overall, the best agreement amongst data sets is seen in the mid-latitude lower and middle stratosphere, with larger differences in the equatorial lower stratosphere and the upper stratosphere globally. In most cases, differences in the choice of underlying instrument records that were merged produced larger differences between data sets than the use of different merging techniques. Long-term ozone trends were calculated for the period 1984–2011 using a piecewise linear regression with a change in trend prescribed at the end of 1997. For the 1984–1997 period, trends tend to be most similar between data sets (with largest negative trends ranging from −4 to −8% decade−1 in the mid-latitude upper stratosphere), in large part due to the fact that most data sets are predominantly (or only) based on the SAGE-II record. Trends in the middle and lower stratosphere are much smaller, and, particularly for the lower stratosphere, large uncertainties remain. For the later period (1998–2011), trends vary to a greater extent, ranging from approximately −1 to +5% decade−1 in the upper stratosphere. Again, middle and lower stratospheric trends are smaller and for most data sets not significantly different from zero. Overall, however, there is a clear shift from mostly negative to mostly positive trends between the two periods over much of the profile.

Highlights

  • The phase-out of ozone-depleting substances (ODSs) through the Montreal Protocol and its subsequent amendments and adjustments (World Meteorological Organization (WMO), 2015; 2011) resulted in peak stratospheric ODS concentrations in the late 1990s or early 2000s; the exact timing of the peak depends on which part of the stratosphere is considered

  • This paper presents the first intercomparison of seven new merged satellite ozone profile data sets for the period 1984– 2011, common to all data sets

  • We present an overview of the methods, assumptions, and challenges involved in producing such merged data sets

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Summary

Introduction

The phase-out of ozone-depleting substances (ODSs) through the Montreal Protocol and its subsequent amendments and adjustments (World Meteorological Organization (WMO), 2015; 2011) resulted in peak stratospheric ODS concentrations in the late 1990s or early 2000s; the exact timing of the peak depends on which part of the stratosphere is considered. It has not been possible to a priori eliminate all systematic biases in any vertically resolved ozone data set, and one data set is typically chosen as a reference, with others biascorrected with respect to that reference This requires a sufficiently long overlap between the instrument records to derive a statistically significant estimate of the bias, which can be propagated to regions (in space and time) outside of the overlap. The native vertical coordinate for the solar occultation technique used by the SAGE-II instrument is geometric altitude with ozone being retrieved in units of number density, while the thermal emission measurements of the MLS (Microwave Limb Sounder) instruments provide ozone amounts on pressure levels and in units of mixing ratio To combine two such data sets, one of them needs to be converted to the vertical coordinate of the other, requiring knowledge of the vertical temperature profile, and to a common concentration unit, requiring local temperatures.

Merged data sets used in this study
SAGE-based data sets
Vertical coordinates and a common grid
Multi-data-set mean
Multiple linear regression model
Data set intercomparison
Annual cycle
Interannual variability
Interannual anomalies
Trends
Findings
Conclusions

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