2. Assess the state of the ozone layer and its future
evolution
Evaluate recent Antarctic ozone hole and Arctic ozone depletion
behavior
Evaluate trends of ozone-depleting substances in the atmosphere
Assess the impacts of climate change on ozone layer
Analyze atmospheric concentrations of bromine and implications
for the ozone-layer
Describe surface ultraviolet radiation observations and future
expectations
Assess interaction between tropospheric and stratospheric ozone
Assess approaches to evaluating very short-lived substances
The Montreal Protocol Parties’ Request
(Decision XIX/20)
3. Chapter 1: Ozone-Depleting Substances (ODSs) and Related Chemicals
Steve Montzka (NOAA, USA)
Stefan Reimann (EMPA, Switzerland)
Chapter 2: Stratospheric Ozone and Surface Ultraviolet Radiation
Anne Douglass (NASA, USA)
Vitali Fioletov (Environment Canada, Canada)
Chapter 3: The Future of the Ozone Layer and Its Impact on Surface UV:
The Influence of ODSs, Climate, and Other Factors
Slimane Bekki (CNRS, France)
Greg Bodeker (NIWA, New Zealand)
Chapter 4: Impact of Stratospheric Changes on Climate
Piers Forster (University of Leeds, UK)
Dave Thompson (Colorado State University, USA)
Chapter 5: Information and Options for Policymakers
John Daniel (NOAA, USA)
Guus Velders (Netherlands Environmental Assessment Agency, Netherlands)
WMO/UNER Ozone Assessment 2010
Chapters and Coordinating Lead Authors
4. 4
Global total ozone deviations from the pre-1980 level
Annual mean area weighted global total ozone deviations. While global ozone
was fairly constant during 1996-2008, the average values are about 4% lower
during that time than those of the late 1970s.
5. Vertical profile of ozone trends over northern and southern midlatitudes estimated
from ozonesondes, Umkehr, SAGE I+II, and SBUV(/2) for the period 1979-2004
The trends were estimated using regression to an EESC curve and converted to
%/decade using the variation of EESC with time in the 1980s. The 2σ error bars
are shown (from WMO Ozone Assessment 2006)
35 N - 60 N 35 S - 60 S
-12 -8 -4 0 4
Trend (% per decade)
10
20
30
40
50
Height
(km)
SAGE I+II
Umkehr
SBUV(/2)
Sondes
-12 -8 -4 0 4
Trend (% per decade)
SAGE I+II
SBUV(/2)
6. Steinbrecht et al., IJRS, 2009,
Upper stratospheric ozone anomalies from
the satellite-borne sensors agree within 5%
or better with ground-based data at five
stations of the Network for the Detection of
Atmospheric Composition Change (NDACC),
from 45S to 48N. From 1979 until the late
1990s all data show a clear decline of ozone
near 40 km, by 10% to 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.
Ozone in the upper
stratosphere (35-45 km)
7. Ozone variations from satellite data at 37 km
SBUV(/2) data SBUV(/2) data merged with SAGE
8. Ozone variations from satellite data at 37 km
SBUV(/2) data SBUV(/2) data merged with SAGE +…
9. Satellite measurements of ozone profiles
– Backscatter UV measurements
(SBUV(/2), GOME, SCIAMACHY)
• Global coverage
• Biases in individual instruments that are time
and altitude-dependent
• Low vertical resolution (>5 km)
– Limb measurements (OSIRIS,
SCIAMACHY)
• Vertical resolution ~3 km
• Poor spatial resolution
• Good coverage, but with gaps
– Occultation measurements (SAGE, ACE)
• Absolute measurements, low uncertainties
• Poor spatial resolution
• High vertical resolution ~ 1 km
• Limited spatial coverage
X
Tangent
Point
Earth
Atmosphere
Solar
Spectra
Sun
Vertical
Profiles
ACE
10. Monthly mean ozone time series comparison of 6 instruments in nine altitude/latitude
bins; SAGE I+II (blue), SBUV/2 (orange), HALOE (red), SMR (magenta), OSIRIS
(black), SCIAMACHY (cyan). The bins range from 60 S to 60 N in an altitude range
from 20–45 km (Jones et al., 2009).
11. Quasi-biennial signals in (a) SAGE II data and (b) merged SBUV data.
Plotted are monthly, zonal-mean ozone anomalies in the tropics (5S-
5N). Anomalies were calculated as percent deviations from the 1978-
1990 means.
Quasi-biennial signals in SAGE and SBUV data
12. The left column of plots displays ozone
trends from published data: (a) SAGEI+II
(reproduction of Randel and Wu, (2007)
calculations), (b) the NASA merged SBUV
data set, (c) SAGE-corrected SBUV
(McLinden et al., 2009). For paned (c)
SAGE I+II converted onto a pressure using
a temperature trend from Randel et al.(2009)
and then vertically smoothed to match the
SBUV vertical resolution. Shading indicates
the trends are significant at the 2 − σ level.
Panel (a) is plotted in altitude, the remaining
panels in pressure-altitude. Pressure-altitude
is defined as z∗ = −16 log10(p/1000), where
p is in hPa and z∗ is km. Trend contours are
every 2%/decade
SAGE
SBUV
SAGE-corrected SBUV
Stratospheric ozone trends in %/decade
13. Reconstruction of time series based on March O3
original SBUV(/2) time series
March values of original SBUV(/2) time series
reconstructed time series
The reconstructed time series captures well all
the features of the original time series (r=0.88).
S. Tegtmeier et al., 2009
14. Questions
• How to combine ozone profile records
from different satellite instruments ?
• How to deal with uncertainties related to
composites of satellite records?
• How do the records depend on the
available meteorological data used?
15. Possible procedure and planning
• IGACO-O3/UV lead with help from WMO
SAG-Ozone, SPARC and IOC
• Support from
– the space agencies (ESA, NASA,…),
– meteorological agencies involved in satellite
and ground-based measurements
– leading scientists in the field
• Workshop in late 2010 or early 2011 to
develop a work plan
Neil Harris and Johannes Staehelin, March 2010
16.
17. Solar Cycle
%
deviation
%
deviation
%
deviation
Deseasonalized, deternded
and adjusted for biases
SBUV(/2) data from Nimbus-
7 and NOAA-9, 11, 16, and
17 satellites in different layers
for 25S-25N. The seasonal
cycle was estimated from
Nimbus-7 data and then
subtracted from the other
data sets. The black line
represents the solar cycle
estimated from the 27-day
cycle.
30 km 33 km
37 km 40 km
43 km 46 km
18. Persistence of HALOE NOx anomalies
Number of years too small to calculate
meaningful correlation coefficients
NOx anomalies clearly persist from
winter until the following autumn
Persistence of NO2 and NOx
anomalies points to mechanism that
transport-induced NOy anomalies and
their seasonal persistence cause the
observed persistence of ozone
anomalies
