Ozone profile trends over the period 2000 to 2016 from several merged
satellite ozone data sets and from ground-based data measured by four
techniques at stations of the Network for the Detection of Atmospheric
Composition Change indicate significant ozone increases in the upper
stratosphere, between 35 and 48
Depletion of the stratospheric ozone layer by anthropogenic chlorine and
bromine from ozone-depleting substances (ODSs) has been a worldwide concern
since the 1970s
The Montreal Protocol has been very successful. The concentration of ODSs in
the atmosphere has been declining since the mid-1990s in the troposphere, and
since the late 1990s also in the stratosphere
The last WMO/UNEP ozone assessment
Merged satellite data sets used in the present study. The URLs serve as an entry point only, and do not always provide the newest and most complete data set used here. See text for references.
Stations and instruments used in the present study. Lidar, microwave, and FTIR
data are from the Network for the Detection of Atmospheric Composition Change
(NDACC) and are originally available at
Annual mean ozone anomalies near 2
Studies published after
The purpose of the present paper is to follow up on these studies, but with
3 to 4 more years of data, and with improved and additional data sets.
Here we present initial results. A more comprehensive investigation of
instrumental and merging uncertainties, and of uncertainties for different
regression analyses is under way in the Long-term Ozone Trends and
Uncertainties in the Stratosphere initiative (LOTUS), an activity of the
Stratosphere-troposphere Processes And their Role in Climate project (SPARC)
of the World Climate Research Programme (WCRP); see
The determination of ozone trends requires homogeneous data records that
extend over several decades, because not only ozone variations associated
with the quasi-biennial oscillation must be quantified well, but also the
slow variations associated with the 11-
The nadir-viewing Solar Backscatter Ultraviolet (SBUV) instruments on NASA
and NOAA satellites have measured ozone profiles continuously since late
1978, covering the sunlit part of the globe, but with only coarse altitude
resolution of 10 to 15
Ozone profiles with higher vertical resolution (about 2
Using microwave emissions in limb geometry, the Microwave Limb Sounder (MLS)
on the Aura satellite has been measuring many stratospheric trace gases since
2004, including ozone profiles with dense spatial sampling and a vertical
resolution of 2.5 to 3
For the period from August 2002 to April 2012, ozone profiles were also
measured by the SCIAMACHY (SCanning Imaging Absorption spectroMeter for
Atmospheric CHartographY), GOMOS (Global Ozone Monitoring by Occultation
of Stars) and MIPAS (Michelson Interferometer for Passive Atmospheric
Sounding) instruments on board the European ENVISAT satellite. Positive ozone
trends have been reported in the upper stratosphere for each of these
instruments
Comparison between principal data sets, trend periods, and regression method
used in the present study, in
Latitude pressure cross section of 2000 to 2016 ozone trends TR
obtained by 2-step multiple linear regression (see text). Panel
Same as Fig.
While satellites provide near global coverage, the limited lifetimes of most
satellite instruments makes the construction of consistent long-term records
difficult, as indicated above. Long-term consistency, therefore, might be
more easily achieved by ground-based measurements, albeit at the cost of only
local coverage. Ground-based instruments have provided some of the longest
available records for ozone trend analysis
A comprehensive intercomparison of limb-viewing satellite instruments with
ground-based NDACC ozone sondes and lidars by
Table
Figure
All observational data sets show similar fluctuations from year to year,
usually within 1 or 2
Multiple linear regression (MLR) has become a standard method for deriving
ozone trends
MLR attempts to reconstruct the observed anomalies as a linear combination of
prescribed predictors
Here our set of predictors
If realistic uncertainties
Strictly, the uncertainties from the MLR assume that the predictors are
orthogonal, and that the residuals
One problem with the “hockey stick” fit is that the slope of the declining
trend and the time of the turning point have an influence on the slope of the
second part of the hockey stick
Figures
The simulations (in the top right panel of Fig.
Figures
A specific look at zonal mean trends from all satellite and ground-based data
sets is given in Fig.
Proxy time series used for the multiple linear regression in
Eq. (
Approaches taken to obtain the average trend and its uncertainty estimate in
the present study, in
Vertical profiles of 2000 to 2016 ozone trends, obtained by 2-step multiple
linear regression (see text), for different merged satellite and ground-based
station data sets. Results are for the zonal bands 60 to 35
Same as Fig.
It is useful to obtain an average ozone trend profile from all individual
trends. In
One problem with the standard weighted mean is that its uncertainty does not
depend on the spread of the individual trends (because of Gaussian error
propagation). Therefore,
To be compatible with
Figure
The (joint distribution) uncertainty bars in Fig.
Average 2000 to 2016 ozone profile trends, obtained from individual trends
for the GOZCARDS, SWOOSH, SAGE–OSIRIS, SAGE–CCI–OMPS(2D),
SAGE–MIPAS–OMPS(v2), SBUV-NASA, and SBUV-NOAA satellite data
sets. Given are mean trend TR and SD
All values are % per decade.
For comparison, the yellow lines and shading in Fig.
Compared to
The updated trend profiles in Fig.
New and improved satellite data sets and the addition of several years of
data until the end of 2016 improve our confidence that ozone in the upper
stratosphere, between 5 and 1
Overall, the updated ozone profile trends are consistent with previous
studies, e.g., with
There are, however, remaining questions, for example regarding the merging of
different instrumental records, the quality of the records in the lowermost
stratosphere, or on the best methods for trend estimation and their detailed
uncertainties. These issues are being addressed in the Long-term Ozone
Trends and Uncertainties in the Stratosphere (LOTUS) initiative, which runs
under the Stratosphere-troposphere Processes And their Role in Climate
project (SPARC) of the World Climate Research Programme (WCRP); see
The update presented here, however, already gives strong indications that
ozone in the upper stratosphere has been increasing over the last
15
The satellite ozone records used in this study are available
from the sources given in Table 1. The ground-based data are available from
the NDACC data base at
The paper was written by WS, who also did the trend analysis, and is responsible for the NDACC lidar measurements at Hohenpeissenberg. LF, RF, HJW, and JA contributed the GOZCARDS data set, RPD, JMZ, AB, CR, and DD the SAGE–OSIRIS–OMPS data set, SF, RSS, RDMcP, and PKB the SBUV-NASA data set and OMPS data, JW and CL the SBUV-NOAA data set, SD and KR the SWOOSH data set, VS, KW, NR, AR, MW and others the SAGE–ESA CCI–OMPS data set, and AL, TvC, GS and NK the SAGE–MIPAS–OMPS data set. NDACC lidar measurements were provided by SGB, TL, RQ, and DPJS. NDACC microwave measurements were given by IB, KH, NK, EM, LM, and GN. CV, TB, MS, OG, NJ, EM, DS, MK, and JR provided the NDACC FTIR data. IP and EMB processed the Umkehr data set. NRPH, BH, DH, and FT contributed important input and discussions on trends, data sets, and their uncertainties.
This article is part of the special issue “Quadrennial Ozone Symposium 2016 – Status and trends of atmospheric ozone (ACP/AMT inter-journal SI)”. It is a result of the Quadrennial Ozone Symposium 2016, Edinburgh, United Kingdom, 4–9 September 2016.
The authors gratefully acknowledge the extremely important contribution from staff at the stations, who run and fix the ground-based systems, and from the many people involved in the satellite measurements. Funding by national and supranational agencies is also gratefully acknowledged. Some of the data sets were calculated with resources provided by the North-German Supercomputing Alliance (HLRN). The merged SAGE–ESA CCI–OMPS data set has been created in the framework of the ESA Ozone_cci project. OHP NDACC lidar measurements are funded by CNRS and CNES. Work performed at the Jet Propulsion Laboratory, California Institute of Technology, was done under contract with the National Aeronautics and Space Administration. NOAA supports and funds a major part of the Dobson Umkehr measurements, in collaboration with funding and work done by Meteoswiss, Switzerland; NIWA, New Zealand; the Australian Bureau of Meteorology; CNRS, France; and the University of Fairbanks, Alaska. We acknowledge the CCMVal-2 group for providing their model simulations. Fiona Tummon was supported by Swiss National Science Foundation grant number 20FI21_138017. We also thank the two reviewers for their helpful comments. Edited by: Stefan Reis Reviewed by: Johannes Staehelin and one anonymous referee