Introduction
Monitoring the global distributions of chlorofluorocarbons (CFCs) is
important for various reasons. The chlorine released by photolytic
decomposition of CFCs plays a key role in ozone depletion both in the
upper stratosphere and in the polar regions
. Furthermore, CFCs and most of their
replacements are strong infrared absorbers that contribute
significantly to the anthropogenic greenhouse effect
. Tracer–tracer relations of long-lived
trace gases, such as CFCs, are frequently examined to study dynamical
processes in the stratosphere, in particular the mixing of air masses
near the subtropical and polar vortex transport barriers
. The data are
also used to determine the age of air .
Continuous, global measurements of CFCs are useful assets to validate
the representation of transport, mixing, and photochemistry in
atmospheric models . Here we focus on
CFCl3 (CFC-11) and CF2Cl2 (CFC-12), which are the CFCs with
the largest atmospheric abundances.
CFCs originate from anthropogenic emissions in the troposphere, where
they are well mixed and chemically stable. In the stratosphere they
are removed mainly by means of photolytic decomposition and reaction with
atomic oxygen. Their trends are controlled by the balance of the
tropospheric sources and the stratospheric sinks. The lifetime τ
(in years) is one particular measure of the global loss rate of a
long-lived trace gas. It is defined as the ratio
τ=BS
of the
atmospheric burden B and the sink S.
The burden B is defined as the total mass of the gas (in Tg) integrated
over the atmospheric reservoir. The sink S represents the
total loss of mass (in Tg yr-1). For the CFCs we usually refer to the
lifetimes as “stratospheric lifetimes”, because the sinks are mostly located
in the stratosphere.
For CFC-11 it was recently recognized that there is a minor sink in the
tropical upper troposphere , which is, however, neglected in our analysis.
The stratospheric lifetimes of CFCs are
crucial in determining their global warming potentials and ozone
depletion potentials; see and for a more
detailed discussion.
Based on various lifetime estimates derived from observations,
laboratory data, and a range of modeling approaches, the World
Meteorological Organization (WMO) recommended lifetimes of 45 years for
CFC-11 and 100 years for CFC-12 in the 1998 Scientific Assessment of
Ozone Depletion . These recommendations were retained
unaltered during the following three assessments. However, later
studies and the WMO assessment in 2010
indicated problems with the lifetime estimates of some
halogen-containing species. As a consequence, the lifetimes of many
long-lived compounds, including CFC-11 and CFC-12, have been recently
reassessed within a Stratosphere-troposphere Processes And their Role
in Climate (SPARC) project . The aims of the SPARC
project were to provide new estimates of the lifetimes and associated
errors of many long-lived trace gases, to assess the influence of
different lifetime definitions, and to assess the effect of a changing
climate on lifetimes. The project results will be used to update the
lifetime recommendations of the next WMO assessment. The lifetime
recommendations from the SPARC project are 52(43–67) years for CFC-11
and 102(88–122) years for CFC-12. The errors given here for the SPARC
data indicate “most likely” ranges and denote 2σ uncertainties.
In this study we aimed at providing new estimates of the ratio of the
stratospheric lifetimes of CFC-11 and CFC-12 based on satellite
observations and model output, which can be helpful input for future
reassessments.
Various methods have been developed to determine the lifetimes of
long-lived species from measurements or model output. In this study we
apply the tracer–tracer correlation approach
to estimate the ratio of the
stratospheric lifetimes of CFC-11 and CFC-12. Following a common
convention, we use the lifetime ratio to also estimate the absolute
lifetime of CFC-12, based on a given reference lifetime for CFC-11.
We here make use of the new SPARC recommendation of 52 years for CFC-11.
Note that all CFC-12 lifetime estimates presented in this paper will
change if the reference lifetime for CFC-11 changes. We directly
apply the tracer–tracer analysis to multi-annual zonal mean
climatologies of CFC-11 and CFC-12 that are derived from satellite
measurements or atmospheric model output. This is a simple and
efficient approach, as it separates the task of lifetime estimation
from the task of preparing a climatology, which typically requires the
processing of large satellite or model data sets. An important
difference compared to previous studies using satellite data is that
we used in situ surface measurements rather than satellite data to
estimate the global burdens of CFC-11 and CFC-12. This yields more
accurate results because the in situ measurements are much less
affected by systematic errors or data gaps, which are typical for limb
and occultation satellite measurements in the troposphere. The high
degree of consistency of the results for the different and, except for
use of the same lists of spectral lines, independent data sets
analyzed here provides confidence in the validity of our approach.
In Sect. we introduce the tracer–tracer correlation
method used to estimate the CFC-11 / CFC-12 lifetime ratio from zonal
mean climatologies. We also describe the different satellite
observations and the model data set. In Sect. we
present estimates of the CFC-11 / CFC-12 lifetime ratio and the CFC-12
lifetime for the different data sets. Section
shows a comparison with lifetime estimates from other studies and
provides a discussion of the results. Appendix A illustrates the
influence of systematic measurement errors on lifetime analyses, based
on tests with idealized CFC profiles. Appendix B describes the
electronic supplement of this paper.
Methods and data
Lifetime estimates from tracer–tracer correlations <?xmltex \hack{\newline}?>
The tracer–tracer approach to estimate stratospheric lifetimes of
long-lived species is based on the theoretical work of
, , and . In these
studies it is shown that any two species whose local lifetimes are
longer than quasi-horizontal transport timescales are in
climatological slope equilibrium. This means that they share surfaces
of constant volume mixing ratios so that a scatter plot of their
volume mixing ratios shows a compact curve. If this surface is chosen
to lie below all sinks, the slope of the correlation curve can be
related to the ratio of the tracer lifetimes,
τ1τ2=B1B2dσ2dσ1,
where τ1 and τ2 denote the lifetimes, B1 and B2 are
the global burdens, and dχ2 / dχ1 is the correlation slope
under steady-state conditions. For stratospheric tracers such as CFCs,
Eq. (2) holds at the tropopause.
Before we discuss the estimation of the stratospheric lifetimes of
CFCs in more detail, we first summarize the arguments leading to the
conclusion that data from the lower stratosphere at midlatitudes are
best suited for that purpose. In general, the correlations of
long-lived tracers are affected by the rates and locations of their
sources and sinks as well as the typical characteristics of advective
and diffusive fluid dynamical transport. Compact correlations are
found if the chemical sources and sinks are weak and if mixing on
isentropic surfaces is much faster than diabatic advection through
those surfaces . While the sources of the CFCs are
located at the Earth's surface, the decomposition takes place mostly
at low and midlatitudes in the middle and upper stratosphere
. The tropical stratosphere is
dominated by large-scale upwelling and is relatively isolated from
midlatitudes . Thus tropical correlation curves
are influenced by local tropical sinks rather than reflecting only
global sinks and are therefore generally not suited to derive global
stratospheric lifetimes. At high latitudes the polar vortex causes
stratospheric air to subside in isolation from midlatitudes and
correlation curves within the vortex develop separately from those at
midlatitudes over the course of the winter
. Finally, in the
free troposphere, complex advection and mixing processes can cause the
breakdown of the compact, stratospheric correlations. In particular,
fast vertical transport by convection violates the assumption that
diabatic advection is slow compared with isentropic mixing
.
Equation () strictly applies only for steady-state
conditions for which sources and sinks are balanced and for which the
burdens do not change over time. In reality, depending on the
age of air, the surface trends affect the stratospheric volume mixing
ratios in different regions at different times. As a consequence, the
observed transient correlation slopes dχ2 / dχ1, with
transient volume mixing ratios χi, typically do not match with
steady-state slopes dσ2 / dσ1, with steady-state volume
mixing ratios σi. introduced correction factors
Ci for each tracer, which depend on the correlations between the
age of air and the tracer volume mixing ratio, to correct for the
transience effect. Thereby the equation for the lifetime ratio becomes
τ1τ2=B1B2dχ2dχ1C2C1.
Equation () is used here to estimate the lifetime
ratio of CFC-11 and CFC-12 and to estimate the lifetime of CFC-12,
based on a given lifetime for CFC-11. In the following we will
discuss the three factors in Eq. () that determine
the lifetime ratio in more detail.
The first factor in Eq. () is the ratio of the
burdens B1/B2. This factor could, in principle, be determined
directly from satellite or model climatologies. However, infrared limb
or occultation satellite measurements in the troposphere are often
affected by systematic errors, including, e.g., uncertainties in
radiometric and spectral calibration or pointing knowledge. Forward
model parameters errors such as uncertainties of spectroscopic data
are another important error source in the CFC retrievals.
Furthermore, the total number of observations in the troposphere is
often limited due to the interference of clouds. As a consequence,
zonal mean climatologies from satellite instruments typically have
limited data quality in the troposphere. At their lowermost altitudes
the climatologies often do not converge to surface values, which are
very accurately known from in situ measurements. Therefore we
estimated the ratio of burdens based on global mean volume mixing
ratios at the surface, σs,1 and σs,2,
B1B2=ασs,1σs,2.
This approach is motivated by the fact that more than 90 % of the mass
of CFC-11 and CFC-12 is located in the troposphere. In the
troposphere CFCs are well mixed and their concentrations are
well known from in situ measurements. Differences between the ratio
of the burdens and the ratio of the surface volume mixing ratios arise
from the different stratospheric distributions of the CFCs. To take
into account the stratospheric distributions, we apply a scaling
factor α=0.97±0.01 to convert the ratio of surface values to
the ratio of total atmospheric burdens. This value of α
specifically applies to the ratio of CFC-11 and CFC-12. It was
estimated from data reported by Table 3 and
Table A4. We also confirmed it independently with
the model data set described in Sect. by comparing
pressure- and cosine latitude-weighted averages of the zonal mean
cross sections with the surface data of the model. Although the
surface volume mixing ratios and burdens show significant trends,
α was found to be rather stable in time. The small uncertainty
of α reported here covers the differences between the various
references and data sources. Model results in the troposphere are
likely not affected by systematic errors as much as satellite
measurements. However, we decided to apply the same approach of
transferred surface data also to the model output for consistency.
Annual global mean surface data of CFC-11 and CFC-12 were obtained
from the National Oceanic and Atmospheric Administration/Earth
System Research Laboratory (NOAA/ESRL) halocarbons program
. Annual means are
derived from weighted and smoothed averages of monthly mean data,
which again are combined, interpolated, and smoothed for each sampling
location of the NOAA/ESRL measurement network. Hemispheric and global
means are estimated by means of cosine weighting by latitude. The accuracy of
the data is better than 2 % . A time series of the data
is shown in Fig. . The ratio of the CFC-11 and CFC-12
surface volume mixing ratios slightly decreased from 0.48±0.02 in
2002 to 0.45±0.02 in 2009, which is the time period of interest
for this study.
Annual global means of CFC-11 and CFC-12 volume mixing
ratios at the surface calculated from monthly data of the
NOAA/ESRL halocarbons program. Error bars indicate the mean
standard deviations of the monthly data.
![]()
The second factor in Eq. () is the transient
tracer–tracer slope dχ2 / dχ1. To estimate this factor we
followed the approach of , which we applied directly to
the multi-annual satellite and model zonal mean climatologies of
CFC-11 and CFC-12. These climatologies usually consist of sets of
volume mixing ratio profiles χ1,i for CFC-11 and χ2,i
for CFC-12 at common altitudes zi, pressure levels pi, or model
levels ζi (see Sect. ) for different latitude
bands. As the actual vertical coordinates are not important for the
tracer–tracer analysis, we simply present all data sets on
approximated altitudes below. For the satellite climatologies we
converted pressure levels pi to log-pressure altitudes,
zi=Hln(p0/pi), with a fixed scale height H=7 km and surface
pressure p0=1013.25 hPa. For the model we used geopotential
heights. We will show vertical profiles and tracer–tracer
correlations for all latitudes for reference below, but it should be
noted that the lifetime analyses are based only on midlatitude data
(typically from 30 to 60∘ N/S).
To estimate the tracer–tracer slope, we first sorted all correlation
data points (χ1,i,χ2,i) into different analysis windows,
covering specific ranges of CFC-11 volume mixing ratios. Our analysis
windows had a width of 100 ppt and a nominal center shifting from 50
to 250 ppt in steps of 5 ppt. For each window we determined the
tracer–tracer slope by means of a linear fit to the data points. As
the data points are unevenly distributed within the windows, we also
calculated the mean CFC-11 volume mixing ratio, to which the
corresponding slope from the linear fit was assigned. By shifting the
analysis window from lower to higher CFC-11 volume mixing ratios, the
change in the slopes from the lower stratosphere towards the
tropopause can be assessed. The tracer–tracer slope at the tropopause,
which is located at the CFC-11 surface volume mixing ratio, was
obtained by extrapolating a linear fit through the individual slopes
of the different analysis windows. This fit through the slopes was
restricted to mean CFC-11 volume mixing ratios larger than
100 ppt. Smaller CFC-11 volume mixing ratios are related to data
points in the middle and upper stratosphere that cannot be used to
estimate lifetimes. Our error analysis takes the statistical errors of
the linear fits into account. However, the leading error of the
correlation slopes is due to systematic errors of the CFC data that we
assumed to be 10 % for each species (see Sect. for a
discussion of measurement errors).
Our method to estimate the tracer–tracer slope differs in some aspects
from the approach developed by : (i) our analysis is
directly based on zonal mean climatologies, while
binned data from individual soundings in the specific analysis
windows. The latter allows for more careful filtering of data points
that are below the tropopause or outside the midlatitudes. Our method
assumes that the degrading effects of these outliers can be neglected
because a large number of soundings is statistically combined. The
method of was originally developed to analyze a limited
number of in situ measurements from aircraft campaigns, while our
study focuses on multiyear satellite records that comprise on the
order of 104 to 106 vertical soundings each. (ii)
used slightly smaller analysis windows, i.e., 70 ppt
rather than 100 ppt. We performed a sensitivity test with window
widths between 50 and 150 ppt and found the most stable and
consistent results for 100 ppt. Differences to 70 ppt were
minor. (iii) used a quadratic fit rather than a linear
fit to extrapolate the slope at the tropopause. However, we found
that a linear fit helps to avoid problems with increasing systematic
errors of the slopes towards the tropopause (see Appendix A). The
linear fit is more tightly constrained by measurements at upper
altitudes. Visual inspection of the slopes for the different
analysis windows helps to judge that the linear fit provides an
acceptable representation.
The third factor in Eq. () is the ratio of
correction factors C=C2/C1 for tracer transience. We determined
C based on data of . Data for different years from
that study are presented in Fig. . The results of
a linear fit applied to the data are also presented. We use the fit
to determine C for any given reference year. In the time period from
2002 to 2009 the combined transience corrections for CFC-11 and CFC-12
range from 0.92 to 1.05. When estimating the error of the lifetime
ratio we assumed that the correction factor C has an uncertainty of
5 %. This uncertainty is much larger than the statistical uncertainty
of the linear fit, but takes into account the systematic errors of the
input data. found that the seasonal variability of
the correction factors is less than 3 % each year.
Combined transience correction factors C=C2/C1 for
CFC-12 vs. CFC-11, which we calculated from data of
. The red line shows a linear fit to the data; see
plot labels for fit parameters and statistical errors.
![]()
Satellite observations of CFC-11 and CFC-12
In this study we make use of CFC-11 and CFC-12 data from three
infrared limb and occultation satellite instruments: the Atmospheric
Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS)
, the HIgh Resolution Dynamics Limb Sounder
(HIRDLS) , and the Michelson
Interferometer for Passive Atmospheric Sounding (MIPAS)
. There are other data sets available for CFC-11 and
CFC-12 from different satellites or from the same instruments, but
analyzed with different retrieval schemes
.
However, these data sets have not been analyzed here. We focus on
data sets covering reasonably long time periods, i. e., at least a
year or longer, to capture a significant part of atmospheric
variability. We also focus on data sets measured after CFC-11 and
CFC-12 reached their peak burdens in the years 1994 and 2002,
respectively. After the peak burdens have been reached, the trends of
CFC-11 and CFC-12 are slower such that the correction for transience
is smaller and thus introduces less uncertainty in this type of
analysis. The ACE-FTS and MIPAS data were already used in other
studies to estimate the stratospheric lifetimes of CFC-11 and CFC-12
. The HIRDLS data are used here for the
first time for that purpose.
ACE-FTS is the main instrument on the Canadian satellite SCISAT-1.
The satellite was launched into a high-inclination, circular low-Earth
orbit (74∘ inclination, 650 km altitude, 97.7 min period) in
August 2003. ACE-FTS measures infrared spectra from 2.2 to
13.3 µm in solar occultation mode. We make use of a
quality-controlled, validated climatology of ACE-FTS data provided by
the ACE Science Operations Centre at the University of Waterloo,
Canada . The
climatology covers the 14 baseline species for ACE-FTS, including
CFC-11 and CFC-12. It is based on retrieval products obtained with
processing software version 2.2, including updates for O3 and
N2O5. The retrievals cover an altitude range of 5 to 22 km for
CFC-11 and 6 to 28 km for CFC-12. The vertical resolution is
typically 3 to 4 km. The validation of the CFC data sets is
described by . It was found that ACE-FTS CFC-11 and
CFC-12 data are systematically lower than balloon-borne
measurements. For CFC-11 the difference is 10 % above 12 km and 20 %
below 12 km. For CFC-12 the maximum bias is 10 % between 12 and
28 km. The precision of individual profiles is not relevant here
because of the large number of profiles we analyzed. The ACE-FTS
climatology of covers the time period from January
2004 to February 2009. During that time about 19 000 occultation
measurements were performed. The original climatological data are
provided on a 3-monthly basis at 5∘ latitude spacing and on
28 pressure levels. We averaged the 3-monthly data, giving them
equal weight, to obtain a multiyear annual mean climatology. The
ACE-FTS data of CFC-11 and CFC-12 are presented in
Fig. , along with the other data sets used in this
study.
Zonal mean climatologies of CFC-11 (left) and CFC-12
(right) volume mixing ratios from the satellite experiments
ACE-FTS, HIRDLS, and MIPAS, as well as the EMAC/CLaMS model. See
plot titles for time periods covered by the different
climatologies. Note that altitudes are log-pressure altitudes for
the satellite climatologies and geopotential heights for the
EMAC/CLaMS model.
![]()
HIRDLS is an infrared limb-sounding radiometer aboard the National
Aeronautics and Space Administration's Aura satellite. Aura was
launched into a near-polar, Sun-synchronous orbit (98.2∘
inclination, 705 km altitude, 98.5 min period) in July 2004. Being
in operation until March 2008, HIRDLS measured thermal emissions from
the atmospheric limb at various spectral intervals in the range from 6
to 17 µm, chosen to correspond to specific trace gases such as
CFC-11 and CFC-12. We analyzed retrieval products obtained with the
processing software version 7 . The
retrievals cover an altitude range of 8 to 26 km for CFC-11 and 8 to
32 km for CFC-12. The vertical resolution is about 1 km. A
comparison of HIRDLS and ACE-FTS for August and September 2006 showed
good agreement for both CFC-11 and CFC-12 . The bias
between both instruments is mostly below 10 %. To derive zonal mean
climatologies from HIRDLS, we first averaged the data on the given
pressure levels in 10∘ latitude bins on a monthly basis. We
filtered individual measurements that are affected by significant
contributions of a priori data or for which the limb view is blocked
by clouds. We also removed outliers that we identified based on volume
mixing ratios exceeding the global mean surface values in 2006 by more
than 10 %. The actual thresholds used for filtering are 275 ppt for
CFC-11 and 595 ppt for CFC-12. The monthly means from January 2005
to March 2008 were averaged, giving them equal weight, to obtain a
multiyear annual mean climatology of CFC-11 and CFC-12. The
climatology is based on more than 6 million individual limb soundings.
The data are presented in Fig. .
MIPAS is one of ten instruments aboard the European Space Agency's
Envisat satellite. Envisat was launched in a nearly polar, Sun-synchronous orbit (98.6∘ inclination, 790 km altitude,
100.2 min period) in March 2002. After losing contact with the
satellite, the end of Envisat's mission was announced in May 2012.
MIPAS measured infrared spectra from 4.1 to 15.4 µm in the limb-viewing geometry. We focus on observations made in between September
2002 and March 2004. During that time period the MIPAS nominal limb
scans covered 6 to 68 km altitude with 3 km vertical sampling from
the troposphere to the middle stratosphere. The retrieval,
validation, and preparation of climatologies of the CFC-11 and CFC-12
MIPAS data used here are described by
. Based on comparisons with
other satellite data sets and in situ measurements, it is shown that
the accuracy of the MIPAS data is about 10 %. The MIPAS climatologies
of CFC-11 and CFC-12 are based on more than 400 000 vertical
soundings. The data are given on a 10∘ latitude and 1 km
log-pressure altitude grid. The zonal mean cross sections are shown
in Fig. . For additional consistency tests we
prepared a second MIPAS climatology (not shown here) based on the new
European Space Agency (ESA) MIPAS level-2 processor version 6 data
. We found that the new ESA data agree well with
the data set of . The
differences of the midlatitude climatological profiles were below
±5% at 12 to 20 km altitude. This indicates that the two
different forward models and retrieval schemes have only a minor impact
on the results.
All three satellite instruments, ACE-FTS, HIRDLS, and MIPAS, show
reasonable zonal mean cross sections. We found the expected spatial
distributions due to upwelling of CFC-rich air in the tropics,
decomposition of CFCs at low and midlatitudes in the middle and upper
stratosphere, and downwelling of CFC-poor air in the polar
regions. Having more C–F bonds, CFC-12 is photochemically more stable
and propagates higher up in the tropical stratosphere. Although the
satellite data sets are obtained during different time periods, there
is mostly good consistency of the zonal mean climatologies. The only
significant difference found, based on visual inspection of the
cross sections, is a high bias of HIRDLS CFC-12 measurements at
southern midlatitudes around 20 to 30 km altitude. This anomaly is
present in many, but not all, of the individual profiles and has
already been identified by the HIRDLS team (B. Nardi, personal
communication, 2013). However, at the moment no further explanation
can be provided. We decided to restrict the analysis of the HIRDLS
data to the Northern Hemisphere.
Coupled chemistry climate model
In this study we use the satellite observations to validate first
simulation results obtained from a new coupled model system
. The model integrates a Lagrangian chemistry
transport model into a climate model. It was mainly developed to
assess the differences between Eulerian and Lagrangian transport
modeling with respect to climate predictions. However, we expect that
the new model will also help to improve long-term simulations of
long-lived trace gases such as CFCs in the stratosphere, due to the
very low numerical diffusion of the Lagrangian transport scheme. Here
we demonstrate, based on a comparison of the lifetime diagnostics, that
the new model system provides realistic global distributions of CFC-11
and CFC-12 with respect to transport, mixing, and photochemistry.
One component of the coupled model is the Chemical Lagrangian Model of
the Stratosphere (CLaMS)
. CLaMS comprises
three main modules for chemistry, advection, and mixing, as well as
several submodules for the simulation of various other physical and
chemical processes in the atmosphere. Due to its transport scheme,
which allows for a precise control of mixing intensity, CLaMS is
especially well suited for simulating transport barriers in the
atmosphere, e.g., at the subtropical and polar jets. The
trajectory module of CLaMS calculates Lagrangian non-diffusive
transport of air parcels based on numerical integration with a
fourth-order Runge–Kutta scheme. Trajectory calculations
are based on the hybrid vertical coordinate ζ
. The original CLaMS version contains a
detailed stratospheric chemistry scheme that involves around 150
chemical species . Here, we employed a
simplified chemistry scheme that is efficient for long-term
simulations . The simplified scheme uses daily-mean
photolysis rates and describes the first-order loss of long-lived
tracers, such as CFC-11 and CFC-12. The photolysis rates were
calculated as diurnal averages using the CLaMS photolysis code
. The simplified chemistry scheme does not simulate
chemical loss due to the reaction with excited-state atomic oxygen,
O(1D). However, the contribution to global CFC loss due to the reaction
with O(1D) is below 10 % .
The second component of the coupled model system is the ECHAM/MESSy
Atmospheric Chemistry (EMAC) model. EMAC is a chemistry climate model
that includes the climate model ECHAM5 and the
interface structure Modular Earth Submodel System (MESSy)
. MESSy provides a coupling interface structure to
develop Earth system models with the flexibility to vary between many
processes that are included as submodels. MESSy includes a special
submodel for dealing with atmospheric tracers (submodel TRACER;
). In the standard EMAC setup, tracers are
transported using the flux-form semi-Lagrangian transport scheme of
. The CLaMS modules for trajectory transport, mixing,
simplified chemistry, and boundary conditions have been integrated
into the MESSy interface structure as submodels. In the coupled
EMAC/CLaMS model, ECHAM5 provides meteorological input for the CLaMS
chemistry transport model.
For this study we performed a 10-year perpetual run with 2005
boundary conditions with the coupled EMAC/CLaMS model. The free-running simulation was not nudged to observations. Sea surface
temperatures and sea ice concentrations were taken from the
Atmospheric Model Intercomparison Project (AMIP II) climatology
. The EMAC spectral resolution was T42, which
corresponds to a quadratic Gaussian grid of approximately
2.8∘×2.8∘ in latitude and longitude, with 90 vertical
levels. For the CLaMS transport core, about 1 million air parcels
were distributed from the surface up to 2500 K potential temperature
(about 60 km altitude). Initial values as well as boundary conditions
for chemical species were taken from a climatological run with the
stand-alone CLaMS model . As CFC-12 is not included
in the CLaMS climatological run, its initial values for the EMAC/CLaMS
simulation were obtained using three correlation functions of CFC-12
with N2O for the tropics (15∘ N to 15∘ S) and the
northern or southern extratropics. To prepare a zonal mean
climatology, data from the years 6 to 10 of the 10-year perpetual run
with EMAC/CLaMS were averaged. Years 1 to 5 were not taken into
account to minimize the influence of initialization. The EMAC/CLaMS
data were binned and averaged on a 10∘ latitude grid for a set
of 33 ζ levels. The vertical spacing of these levels varies
between 0.5 and 1.3 km in the upper troposphere and lower
stratosphere. The EMAC/CLaMS zonal mean climatologies of CFC-11 and
CFC-12 are presented in Fig. . Good agreement is
found in comparison with the satellite measurements. Further
validation of the EMAC/CLaMS simulation results is provided by
.
Results
In this section we present our estimates of the stratospheric lifetime
ratio of CFC-11 and CFC-12 and the absolute lifetime of CFC-12 for the
three satellite missions and the model. All climatologies cover
several years of data, i.e., about 5 years for ACE-FTS, 3
years for HIRDLS, 1.5 years for MIPAS, and 5 years for
EMAC/CLaMS. The different time periods covered by the data sets make
it slightly more difficult to compare the results, but averaging over
long time periods helps to reduce the influence of atmospheric
variability and to constrain the results. We assigned a reference year
to each data set that is used to determine the ratios of the burdens
and the transience correction factors. As shown in
Sect. , these parameters vary only slowly over
time. By selecting the reference year in the middle of the time period
of each data set we made sure that the errors due to a constant
approximation are minor. The uncertainties of all results are given
as standard deviations (1σ values) and calculated based on
conventional error propagation principles. Note that the CFC-12
lifetimes have asymmetric error bars because error propagation was
calculated for their inverse. Following other studies, we here did
not take the uncertainty of the CFC-11 reference lifetime into account
when we estimated the error of the CFC-12 lifetime. The input data
for the lifetime calculations according to Eq. ()
and the CFC-11 / CFC-12 lifetime ratios for the four data sets used here
are summarized in Table .
Summary of input data for the calculation of CFC-11 / CFC-12 lifetime ratios.
Data set
B1/B2
χ2/χ1
C2/C1
τ1/τ2
ACE-FTS (2004–2009)
0.448±0.020
1.05±0.15
0.991±0.050
0.466±0.075
HIRDLS (2005–2008)
0.448±0.020
1.04±0.15
0.991±0.050
0.462±0.073
MIPAS (2002–2004)
0.458±0.020
1.07±0.16
0.934±0.047
0.458±0.076
EMAC/CLaMS (2005)
0.451±0.020
1.05±0.15
1.000±0.000
0.475±0.071
The data used for the ACE-FTS lifetime analysis are presented in
Fig. . The analysis is based on 5∘
latitude bands at 60 to 35∘ S and 40 to 60∘ N. For the
lifetime calculations we selected the year 2006 as the reference year.
The surface volume mixing ratios for the reference year are (249±8) ppt for CFC-11 and (540±16) ppt for CFC-12. We calculated
a ratio of burdens of 0.448±0.020 for CFC-11 vs. CFC-12. The
linear fits yielded a correlation slope of 1.05±0.15 for CFC-12
vs. CFC-11 at the tropopause. The ratio C of transience
correction factors was estimated as 0.99±0.05. These data lead
to a ratio of the steady-state lifetimes of CFC-11 and CFC-12 of 0.47±0.08 and, assuming a lifetime of 52 years for CFC-11, an estimated
lifetime of 112(96–133) years for CFC-12. A separate analysis for the
Northern Hemisphere only provided a lifetime of 113(97–135) years. For
the Southern Hemisphere we found 110(95–131) years.
Volume mixing ratio (vmr) profiles of CFC-11 (top, left)
and CFC-12 (top, right), tracer–tracer correlations (bottom,
left), and tracer–tracer slopes (bottom, right) used to estimate
lifetimes from ACE-FTS data. Black color indicates midlatitude
data. Grey color indicates data from other latitudes. The red
line shows a linear fit used to extrapolate the tracer–tracer
slope at the tropopause (red dot).
![]()
Figure shows the data set used for the
HIRDLS lifetime analysis. The analysis is based on 10∘ latitude
bands at 30 to 60∘ N. Data from the Southern Hemisphere were not
used due to data quality issues (Sect. ). For the
lifetime calculations we selected the year 2006 as the reference year,
resulting in the same surface volume mixing ratios and ratio of
burdens as for ACE-FTS. The linear fits yielded a correlation slope of
1.04±0.15 for CFC-12 vs. CFC-11 at the tropopause. With application of
the same combined transience correction factor C as for ACE-FTS,
this leads to a ratio of the steady-state lifetimes of CFC-11 and
CFC-12 of 0.46±0.07 and a lifetime of 112(97–134) years for
CFC-12.
Same as Fig. , but for HIRDLS data.
![]()
The data used for the MIPAS lifetime analysis are presented in Fig. . The analysis is based on 10∘
latitude bands at 60 to 30∘ S and 30 to 60∘ N. For the
lifetime calculations we selected the year 2003 as the reference year.
The surface volume mixing ratios for the reference year are (256±8) ppt for CFC-11 and (543±16) ppt for CFC-12. We calculated
a ratio of burdens of 0.458±0.020 for CFC-11 vs. CFC-12.
Compared to ACE-FTS and HIRDLS, the ratio of burdens differs only by
2 %. The linear fits yielded a correlation slope of 1.07±0.16 for
CFC-12 vs. CFC-11. The ratio C of transience correction factors
was estimated as 0.934±0.047, i.e., a larger correction than
the one used for ACE-FTS and HIRDLS. These data lead to a ratio of
the steady-state lifetimes of CFC-11 and CFC-12 of 0.46±0.08 and
a lifetime of 114(98–136) years for CFC-12. A separate analysis
provided a lifetime of 111(95–134) years for the Northern Hemisphere
and 120(103–144) years for the Southern Hemisphere. For the ESA data
the analysis gave a lifetime of 113(95–137) years globally,
114(95–140) years for the Northern Hemisphere, and 113(97–135) years
for the Southern Hemisphere. While hemispheric data differ to some
extent, the global results for the ESA data agree well with the
results for the data of .
Same as Fig. , but for MIPAS data.
![]()
Finally, the data set used for the EMAC/CLaMS lifetime analysis is
presented in Fig. . The analysis is based on
10∘ latitude bands at 60 to 30∘ S and 30 to
60∘ N. For the lifetime calculations we selected the year 2005
as the reference year. The surface volume mixing ratios for the
reference year are (252±8) ppt for CFC-11 and (542±16) ppt for CFC-12. We calculated a ratio of burdens of 0.451±0.020 for CFC-11 vs. CFC-12. The linear fits yielded a correlation
slope of 1.05 ± 0.15. We did not apply a transience correction,
because we assume that the model approached steady-state conditions
during the last 5 years of the 10-year perpetual run. The EMAC/CLaMS
model results lead to a ratio of the steady-state lifetimes of CFC-11
and CFC-12 of 0.48±0.07 and a CFC-12 lifetime of
110(95–129) years. We found a lifetime of 108(94–127) years for the
Northern Hemisphere and 111(97–131) years for the Southern Hemisphere.
Same as Fig. , but for EMAC/CLaMS
data.
![]()
Discussion and conclusions
We applied the tracer–tracer approach of ,
, and to estimate the stratospheric
lifetime ratio of CFC-11 and CFC-12 from ACE-FTS, HIRDLS, and MIPAS
satellite observations as well as EMAC/CLaMS model output. We also
estimated the absolute lifetime of CFC-12, based on a reference
lifetime of 52 years for CFC-11. As discussed in Sect.
, our approach is similar to, but differs in some
aspects from, the method of . An important difference
compared to other studies using satellite data is that we estimated
the ratio of burdens of CFC-11 and CFC-12 based on NOAA/ESRL in situ
surface measurements rather than using the satellite data for that
purpose. This avoids problems related to degraded data quality of limb
and occultation satellite measurements in the troposphere due to
systematic measurement errors and data gaps. Another difference
between our study and the method of is that our
analysis is based on multi-annual zonal mean climatologies that are
prepared beforehand and independently from the estimation of
lifetimes.
The lifetime estimates from our analysis are summarized and compared
to other recent studies in Table . Our estimates
for the three satellite data sets show a very high degree of
consistency and are in good agreement with the current WMO
recommendation, the new SPARC reassessment, and other work. In
particular, the estimated lifetime ratios are in excellent agreement
with the study of , which is based on data from the
Advanced Global Atmospheric Gases Experiment (AGAGE) and the NOAA/ESRL
ground-based networks, which are analyzed with a chemical transport
model and a statistical inversion method. Compared to the study of
, who applied the method of on ACE-FTS
data, we found a 17 % larger CFC-11 / CFC-12 lifetime ratio for
measurements from the same instrument. Part of the difference is due
to the fact that we applied a linear fit to extrapolate the
tracer–tracer slope at the tropopause, whereas
applied a quadratic fit. If we replace the linear fit with a quadratic
fit in our analysis, the differences to the results of
are reduced to 10 %. However, we also found that the
quadratic fit significantly increases the error of the extrapolated
tracer–tracer slope and thus decided to keep the linear fit in our
analysis. The ratio of burdens from our analysis is in good agreement
(≤ 0.7 %) with the data reported by . The data for
the transience correction are directly obtained from
and therefore cannot explain any significant differences. We think
that the remaining differences may be due to different data sets used
for the lifetime analysis. The study of covers
ACE-FTS data version 3.0 for the years 2005 to 2010, whereas in our
study the climatology based on version 2.2 was used,
covering the years 2004 to 2009. In addition, the median average
deviation filtering for each data set was applied using different
altitude, spatial and temporal bins. Our CFC-11 / CFC-12 lifetime ratio
for MIPAS is 39 % larger than the corresponding estimate of
. Both analyses are based on the same
climatology. However, very different analysis techniques were
used. applied a photochemical model with
additional input parameters to determine the CFC global loss rates.
These are used to estimate absolute lifetimes rather than a lifetime
ratio. The results of mostly depend on CFC data
in the middle and upper stratosphere at equatorial latitudes, whereas
our results depend on data from the midlatitude lower stratosphere.
Comparison of stratospheric lifetime estimates of CFC-11 and CFC-12 from different
studies. The table lists the data sources of the studies and if absolute (abs) or relative (rel)
lifetime estimates are provided. All relative lifetime estimates are normalized to a CFC-11
lifetime of 52 years. A sub- and superscript notation is used to report errors. Note that
error definitions vary between the studies (see individual references). In particular,
for the errors represent 2σ uncertainties.
Reference
Data source
Method
τ(CFC-11)
τ(CFC-12)
Ratio
[years]
[years]
This study
ACE-FTS
rel
52
11296133
0.470.390.54
HIRDLS
rel
52
11397134
0.460.390.54
MIPAS
rel
52
11498136
0.460.380.53
EMAC/CLaMS
rel
52
11095129
0.480.400.55
various
both
524367
10288122
0.510.350.76
ACE-FTS
rel
52
131110161
0.400.320.47
model results
abs
55
95
0.58
aircraft data
rel
52
877797
0.600.540.67
model results
abs
58
–
–
ACE-FTS
abs
463665
10584139
0.440.260.77
CLAES
abs
–
10888140
–
CRISTA-1
abs
534175
–
–
CRISTA-2
abs
614786
–
–
MIPAS
abs
362850
10883151
0.330.190.60
combined
abs
453658
10790130
0.420.280.64
AGAGE
abs
544861
11195132
0.490.360.64
NOAA/ESRL
abs
524561
11295136
0.460.330.64
various
both
45
100
0.45
model results
abs
605664
106101110
0.570.510.63
aircraft data
abs
412953
7751103
0.530.30.76
rel
52
9987112
0.520.450.59
In our study the results for the three satellite missions show
excellent agreement among each other. The CFC-11 / CFC-12 lifetime
ratios vary only by 1.7 % and the CFC-12 lifetime estimates vary only
by 2 years. Consequently, we combined the ACE-FTS, HIRDLS, and MIPAS
results to obtain error-weighted optimal estimates. This led to a
CFC-11 / CFC-12 lifetime ratio of 0.46±0.04 and a CFC-12 lifetime of
113(103–124) years. The combined results are in very good agreement
with the current WMO recommendation (≤ 3 %) and in good agreement
with the new SPARC reassessment (≤ 10 %). The WMO assessment in
2010 showed a 60 % difference between 2005 and 2008 “bottom-up” and
“top-down” emission estimates for CFC-11, while good agreement was
found for CFC-12 . As “top-down” estimates critically
depend on the lifetimes, whereas “bottom-up” estimates do not, it was
further demonstrated that a longer CFC-11 lifetime
(64 years rather than 45 years) and thus a larger CFC-11 / CFC-12 lifetime
ratio could resolve this discrepancy. Our study indicates that the
CFC-11 / CFC-12 lifetime ratio is about 3 % larger than the current WMO
recommendation. This explains only some of the discrepancy identified
in the last WMO assessment. However, a larger ratio was found in the new SPARC
assessment. An important benefit of our study is that the
errors of the combined data are up to a factor of 2 smaller than the
error estimates of other recent studies. We conclude that our results
can contribute to further constraining the reference values for the
CFC-11 and CFC-12 lifetimes in future assessments and scientific
studies.
The stratospheric lifetimes of long-lived tracers such as CFC-11 and
CFC-12 are important diagnostic quantities to evaluate the
representation of transport and mixing in atmospheric models.
point out that models with faster circulation
produce younger age-of-air distributions and that increasing
circulation speed leads to shorter CFC lifetimes. A comparison of CFC
lifetimes from a model and from observations therefore allows for a
judgement to be made regarding whether the model appropriately represents important
features of the stratospheric circulation. We used the satellite
results to validate the new EMAC/CLaMS coupled model system. As we
applied exactly the same method to estimate the lifetimes for the
satellite observations and the model, the results are indeed
indicative of differences in the underlying data and are not affected
by differences that could occur if different methods for lifetime
estimation were to be used. We found that the EMAC/CLaMS results are in excellent agreement (≤ 3 %) with the
satellite observations after a spin-up phase of 5 years. However, the CFC-11 / CFC-12 lifetime ratio
found here is about 17 % smaller than the result of the recent
multi-model study of . On the one hand, it
should be noted that our simulations are based on a simplified
chemistry scheme that neglects CFC loss due to reaction with excited-state atomic oxygen (Sect. ). However, this is only a
minor loss mechanism. On the other hand, we put forward that the
Lagrangian transport scheme of EMAC/CLaMS provides an improved
representation of advection and mixing in the stratosphere
. The Lagrangian transport scheme used by EMAC/CLaMS
is fundamentally different from the other schemes used by the models
discussed by . We conclude that the new
EMAC/CLaMS model will likely become a useful tool to assess the impact
of advective transport, mixing, and photochemistry as well as
climatological variability on the stratospheric lifetimes of
long-lived tracers.
Another topic of interest is the spatial and temporal variability of
lifetime estimates. Rossby wave breaking and mixing in the
stratosphere are typically much stronger in the winter hemisphere than
in the summer hemisphere . Furthermore,
because of the larger continental land masses in the Northern
Hemisphere, the northern stratosphere has more frequent and intense
planetary wave activity than the southern stratosphere
. Stronger wave activity in Northern
Hemisphere winter leads to a faster Brewer–Dobson circulation in the
stratosphere. Model calculations show that faster stratospheric
circulations produce younger distributions for the age of air, have
larger loss rates of long-lived stratospheric tracers, and therefore
yield shorter CFC lifetimes . The quasi-biennial
oscillation (QBO) also has a significant impact on the stratospheric
distributions of CFC-11 and CFC-12, in particular in the tropics
. These issues are of practical relevance for the
analysis of temporally and spatially limited data sets from aircraft
campaigns, for instance. One example is the recent study of
, which closely followed the approach of
to estimate the CFC-11 / CFC-12 lifetime ratio from measurements of two
aircraft campaigns in late 2009 and early 2010 in northern Europe.
found a CFC-11 / CFC-12 lifetime ratio which is 30 %
larger than our combined result from the satellite data and 18 %
larger than the new SPARC recommendation. This larger lifetime ratio
corresponds to model results , but
further study would be helpful to assess possible impacts of the
limited sampling characteristics of aircraft measurements. Long-term
satellite data sets and model simulations bear the potential to study
variability of lifetimes in detail. studied the
hemispheric and seasonal differences based on ACE-FTS data from 2005
to 2010 and found substantial variations of the CFC-12 lifetime
estimates (from 94 to 173 years), but no clear correlations with either
hemisphere or season. We also analyzed the hemispheric differences of
the CFC-11 / CFC-12 lifetime ratio, but found no significant
differences, when taking the error estimates of the results into
account. Differences in CFC-12 lifetime estimates are 9 years for MIPAS
(only 1 year for the ESA data), 4 years for ACE-FTS, and 3 years for
EMAC/CLaMS.
In this study we estimated the ratio of the stratospheric lifetimes of
CFC-11 and CFC-12 based on the tracer–tracer method directly from
zonal mean climatologies from satellite observations and atmospheric
model output. We took advantage of the fact that these climatologies
provide multiyear coverage, which allowed us to neglect the
statistical errors of individual measurements and take significant
parts of atmospheric variability into account. In contrast to other
studies using satellite measurements, we found highly consistent
lifetime estimates for CFC-11 and CFC-12 for the ACE-FTS, HIRDLS, and
MIPAS as well as the EMAC/CLaMS model. We also found excellent
agreement with the current SPARC recommendations. Nevertheless, new
infrared limb or occultation satellite measurements with high vertical
resolution would help to further improve CFC-11 and CFC-12 lifetime
recommendations and their error estimates in future studies.