Stratospheric Processes And their Role in Climate
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Overview of planned coupled chemistry-climate simulations to support upcoming ozone and climate assesments
Veronika Eyring, DLR-Institut für Physik der Atmosphäre, Germany (Veronika.Eyring@dlr.de)
Douglas E. Kinnison, Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder,
USA (dkin@ucar.edu)
Theodore G. Shepherd, University of Toronto, Canada (tgs@atmosp.physics.utoronto.ca)
On behalf of the CCM Validation Activity for SPARC (CCMVal)
Introduction
SPARC has established a new validation
activity, CCMVal, for coupled chemistry climate
models (CCMs). The activity is
based on the framework developed at the
SPARC workshop on process-oriented
CCM validation held in Grainau, Germany
in November 2003 (Eyring et al., 2004,
2005) and draws upon the experiences
within the SPARC GCM-Reality
Intercomparison Project (GRIPS) (See the
Report on GRIPS in this issue). As more
climate models include chemical components,
the time has arrived for formal comparisons
of these coupled chemistry-climate
models. Within SPARC, this new
activity will be one of the supporting “pillars”
of the integrated themes.
The goal of the new activity is to improve
understanding of CCMs and their underlying
GCMs (General Circulation Models) through
process-oriented validation. One outcome of
this effort is expected to be improvements in
how well CCMs represent physical, chemical,
and dynamical processes. In addition, this effort
will focus on understanding the ability of
CCMs to reproduce past trends and variability
and providing predictions from ensembles of
long model runs. Achieving these goals will
involve comparing CCM constituent distributions
with (robust) relationships between constituent
variables as found in observations.
This effort is both a model-model and modeldata
comparison exercise.At the Grainau workshop,
a set of key diagnostics was defined
for evaluating CCM performance with
respect to radiation, dynamics, transport,
and stratospheric chemistry and microphysics (http://www.pa.op.dlr.de/CCMVal/). This
approach allows modellers to decide (based on
their own priorities and resources) which
diagnostics to examine in any particular area.
The CCMVal activity will help coordinate and
organize CCM model efforts around the world. In this way,the CCM community can provide the
maximum amount of useful scientific information
for WMO/UNEP and IPCC assessments.
As a first step, the CCM community has
defined two reference simulations and a set
of model forcings to support the upcoming
WMO/UNEP Scientific Assessment of
Ozone Depletion. The forcings are defined
by natural and anthropogenic emissions
based on existing scenarios, on atmospheric
observations, and on the Kyoto and
Montreal Protocols and Amendments. In
the following sections, we describe current
models and proposed model simulations,
and discuss several special issues related to
the use of CCMs.
Participating models
During the last few years, a number of new CCMs have been developed, which significantly deepens the pool of available models. In comparison with the models used in support of the last WMO/UNEP ozone assessment (Austin et al., 2003; WMO, 2003), current CCMs generally have improved representations of physical processes, and modelling groups have greater computational resources. Table 1 gives an overview of current coupled-chemistry climate models around the world.
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Table 1: Main features of current coupled chemistry-climate models (CCMs). CCMs are listed alphabetically. The horizontal resolution is given in either degrees latitude x longitude (grid point models), or as T21, T30, etc., which are the resolution in spectral models corresponding to triangular truncation of the spectral domain with 21, 30, etc., wavenumbers, respectively. All CCMs have a comprehensive range of chemical reactions except the UMUCAM model, which has parameterized ozone chemistry. The coupling between chemistry and dynamics is represented in all models, but to different degrees. All models include orographic gravity wave drag schemes (O-GWD); most models additionally include non-orographic gravity wave drag schemes (NonO-GWD). |
Multi-model simulations to support the upcoming WMO/UNEP assessment
CCMs represent both natural dynamical
variability and the dynamical response to
forcings such as sea surface temperatures
(SSTs).As a result, a meaningful comparison
of different CCM results requires a proper
analysis of statistical significance and a careful
representation of natural and anthropogenic
forcings. To address these issues, a
set of questions has been set up for the community
to decide on possible model simulations
and forcings. The draft was opened for
discussion within the CCM community (see
Table 1) and with several other experts.
The proposed scenarios were developed to address the following key questions outlined by the WMO/UNEP Steering Committee to be of significance to the upcoming assessment: (1) How well do we understand the observed changes in stratospheric ozone (polar and extra-polar) over the past few decades during which stratospheric climate and constituents (including halogens, nitrogen oxides, water, and methane) were changing? (2) What does our best understanding of the climate and halogens, as well as the changing stratospheric composition, portend for the future? (3) Given this understanding, what options do we have for influencing the future state of the stratospheric ozone layer?
In order to address questions (1) and (2), two reference simulations (REF) have been proposed.
Reproduce the past: Reference simulation 1 (REF1), Core time period 1980 to 2004
REF 1 is designed to reproduce the wellobserved
period of the last 25 years during
which ozone depletion is well recorded, and
allows a more detailed investigation of the
role of natural variability and other atmospheric changes important for ozone balance and trends. This transient simulation
includes all anthropogenic and natural forcings
based on changes in trace gases, solar
variability, volcanic eruptions, quasi-biennial
oscillation (QBO), and sea surface temperatures
(SSTs). SSTs in this run are based on
observations. Depending on computer
resources some model groups might be able
to start earlier.We highly recommend reporting
results for REF1 between 1960 and 2004
to examine model variability. Forcings for the
simulation and a detailed description can be
downloaded from the CCMVal website
(http://www.pa.op.dlr.de/CCMVal/Forcings/
CCMVal_Forcings.html). They are defined
for the time period 1950 to 2004.
SSTs in REF1 are prescribed as monthly means following the global sea ice and sea surface temperature (HadISST1) data set provided by the UK Met Office Hadley Centre (Rayner et al., 2003). This data set is based on blended satellite and in situ observations.
Both chemical and direct radiative effects of
enhanced stratospheric aerosol abundance
from large volcanic eruptions are considered
in REF1. The three major volcanic
eruptions (Agung, 1963; El Chichon, 1982;
Pinatubo, 1991) are taken into account, i.e.,
additional heating rates and sulfate aerosol
densities are prescribed on the basis of
model estimates and measurements,
respectively.A climatology of sulfate surface
area density (SAD) based on monthly zonal
means derived from various satellite data
sets between 1979 and 1999 has been provided
by David Considine (NASA Langley
Research Center, USA). Details on how to
represent the sulfate SAD before 1979 are
described on the CCMVal web site.
The QBO is generally described by zonal
wind profiles measured at the equator.While
the QBO is an internal mode of atmospheric
variability and not a “forcing” in the usual
sense, at the present time most models do
not exhibit a QBO. This leads to an underestimation
of ozone variability, and compromises
the comparison with observations.
While some of the models internally generate
a QBO, for the others it has been agreed
to assimilate observed tropical winds.
Assimilation of the zonal wind in the QBO
domain can add the QBO to the system, thus
providing, for example, its effects on transport
and chemistry. Radiosonde data from
Canton Island (1953-1967), Gan/Maledives
(1967-1975) and Singapore (1976-2000)
have been used to develop a time series of
measured monthly mean winds at the equator
(Naujokat, 1986; Labitzke et al., 2002).
This data set covers the lower stratosphere
up to 10 hPa. Based on rocket wind measurements
near 8 degree latitude, the QBO
data set has been vertically extended to 3
hPa. The software package to assimilate the
QBO by a linear relaxation method (also
known as “nudging”) as well as the wind
data sets have been provided by Marco
Giorgetta (MPI Hamburg, Germany).
The influence of the 11-year solar cycle on photolysis rates is parameterized according to the intensity of the 10.7 cm radiation of the sun (which is a proxy to the phase of the given solar cycle). The spectral distribution of changes in the observed extraterrestrial flux is based on investigations presented by Lean et al. (1997) (see http://www.drao.nrc.ca/icarus/www/sol_h ome.shtml for details).
Making predictions:
Reference simulation 2 (REF2),
Core time period 1980 to 2025
REF 2 is an internally consistent simulation
from the past into the future. The proposed
transient simulation uses the IPCC SRES scenario A1B(medium) (IPCC, 2000). REF 2
only includes anthropogenic forcings; natural
forcings such as solar variability are not
considered, and the QBO is not externally
forced (neither in the past, nor in the future).
Sulfate surface area density is consistent with
REF1 through 1999. Sulfate surface area
densities beyond 1999 will be fixed at 1999
conditions (volcanically clean conditions).
Changes in halogens will be prescribed following
the Ab scenario (WMO, 2003; Table
4B-2). SSTs in this run are based on coupled
atmosphere-ocean model-derived SSTs.
Depending on computer resources some
model groups might be able to run longer
and/or start earlier. We recommend reporting
results for REF2 until 2050. The forcings
on the website are defined through 2100.
Fully coupled atmosphere-ocean CCMs that extend to the middle atmosphere and include coupled chemistry, will use their internally calculated SSTs. CCMs driven by SSTs and sea ice distributions from the underlying IPCC coupled-ocean model simulation could use the model consistent SSTs. One constraint is to make the SST dataset consistent with the SRES greenhouse gas (GHG) scenario A1B (medium). All other CCM groups will run with the same SSTs, provided by a single IPCC coupled-ocean model simulation. These simulations have good spatial resolution, so the data-sets should be suitable for all the CCMs participating in the WMO/UNEP assessment.
Sensitivity simulations
Scenarios for sensitivity experiments to address question (3) will be defined later. Possible sensitivity experiments could be:
SCN 1 (REF 1 with enhanced Bry): An additional
simulation is being developed to represent
the known lower stratospheric deficit
in modelled inorganic bromine abundance.
This simulation will be identical to REF 1,
with the exception of including source gas
abundances that will increase the stratospheric
burden of Bry.Details of this simulation
will be made available shortly.
SCN 2 (REF 2 with natural forcings): A sensitivity simulation has been defined similar to REF1, with the inclusion of solar variability, volcanic activity, and the QBO in the past. Future forcings include a repeating solar cycle and QBO under volcanically clean aerosol conditions. SSTs are based on REF2. Greenhouse gases and halogens will be the same as in REF2.
A summary of the proposed CCMVal reference and sensitivity simulations is given in Table 2.
A web site containing descriptions of the
model simulations, as well as relevant forcings
(past and present), can be found at http://www.pa.op.dlr.de/CCMVal/Forcings
/CCMVal_Forcings.html. The forcings for
the specified simulations may be downloaded
from this website.
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Table 2: Summary of proposed CCMVal simulations. |
Discussion
In the effort to select the simulations in Table 2, several issues arose that required a special action or decision. A brief perspective on these issues is presented in this section.
Greenhouse Gases and Halogens
Historical and Future Trends: It has been agreed that the simulations to represent the past (REF1) should not stop in the year 2000, but should be extended until 2004. Between the years 2000 and 2004 new measurements of trace gases from the SCIAMACHY, MIPAS, AURA, ACE and ODIN satellite instruments became available. In addition, new data from existing satellite instruments, such as TOMS, GOME, and HALOE, are also available for CCM intercomparisons. In response, Stephen Montzka (NOAA Climate Monitoring and Diagnostics Laboratory, USA) has offered to update the datasets of halogen and other greenhouse gas observations to 2004. Datasets of sea surface temperatures up to 2004 are available on the Hadley Centre web site (see http://www.hadobs.org/).
For the prediction simulation (REF 2) the
community agreed to run with the GHG
scenario SRES A1B(medium) with the
halogen scenario Ab from WMO (2003).
However, Paul Fraser (CSIRO, Australia)
mentioned that the SRES reference scenario
A1B is very unlikely to be realistic for
CH4 over the next 20 years. A1B requires
CH4 to increase from 1760 ppb in 2000 to
2026 ppb in 2020, i.e., with a growth rate of
13-14 ppb per year. This growth rate has
not been observed since the late 1970s. In
contrast, the growth rate in the Southern
and Northern Hemispheres for the past
five years has been less than 1 ppb per year,
with the current globally averaged concentration
at 1750 ppb (2004).
In the proposed simulation REF2, the CCMs
are driven by SSTs and sea ice distributions
from coupled ocean-atmosphere model
simulations using IPCC SRES GHG scenarios.
To be consistent with the IPCC simulations,
the GHG scenarios must be the same
as in the coupled ocean-atmosphere model
simulations. Therefore, it has been decided
that CH4 emissions during this phase of the
assessment process will not be changed from
the IPCC SRES GHG scenarios for REF2.
Inorganic Bromine Deficit: Model representations
of inorganic bromine radicals in
the lower stratosphere and comparisons
with observations have recently been documented
(see WMO, 2003, Chapters 1 and 2;
Salawitch et al., 2005 and references within).
Results from these comparisons strongly
suggest that models greatly underestimate
the total inorganic bromine (Bry) in
this region (up to 6 pptv). Furthermore, it is
clear that using time-dependent boundary
conditions as prescribed in the Ab scenario
(WMO 2003) will not correct the modelled
Bry distribution. It is believed that this discrepancy
occurs because very short-lived
(VSL) bromine-containing source gases are
not included in the models. Incorporating
these species into CCMs will require understanding
of the magnitude and geographic
distribution of the sources of these VSL
gases and their loss processes in the atmosphere.
Based on input from Ross
Salawitch (Jet Propulsion Laboratory,
USA), Martyn Chipperfield (University of
Leeds, UK), and Stephen Montzka, and
considering the time constraints of including
VSL species and related processes into
CCMs, it was decided that no attempt
should be made to address the Bry deficit in
the reference simulations (REF1 and
REF2). This means that the reference CCM
experiments will necessarily underestimate
stratospheric Bry by about 25%. This will
impact their ability to reproduce, for example,
polar ozone loss quantitatively, and
predict the future ozone changes; this
caveat needs to be remembered when analyzing
the results. However, a sensitivity
simulation is being developed to examine
this issue (SCN1). Quantification of the
effect of enhanced Bry on ozone trends for
the WMO/UNEP 2006 ozone assessment
will most likely be done with 2D and 3D
chemical-transport models.
QBO and Solar Variability
Solar activity, as well as the QBO, has a
strong influence on ozone variability. Some
CCMs with high horizontal and vertical resolutions
are able to internally generate a
QBO. However, the majority of CCMs do
not generate a QBO. Consequently these
models simulate permanent tropical easterlies
instead of a QBO. As the QBO is important
for wave propagation and interaction
with high latitudes, the latter CCMs therefore
have a known deficit which would
affect both the means and variabilities of
trace gas distributions. Therefore, part of
the community felt that QBO and solar
variability should also be included in future
years in the reference simulations to the year
2025 and, therefore, suggested using SCN2
as the reference simulation instead of REF2.
However, others have reservations about including a QBO and solar cycle in the future, since these are not anthropogenic forcings and, hence, cannot be predicted. In the case of the QBO, which is an internal mode of atmospheric variability and not a “forcing” at all, the amplitude and phase of the QBO will have no connection to the prognostic model variables or the SSTs and, of course, will not respond to climate changes.
The obvious way to address the opposing
views is to encourage groups to run both
simulations, REF2 and SCN2. However, due
to limited time and computer resources it is
not very likely that all, or even most, groups
can afford to run both the REF2 and SCN2
simulations. Therefore, a decision was
made to make REF1 and REF2 the highest
priority and encourage groups to run SCN2
in addition if resources allow.
Sea Surface Temperatures
One of the most critical issues in the discussion was the design of the future simulation REF2. The problem is how to extend SST observations into the future without introducing a discontinuity at the presentto- future transition.
One possibility would be to add timeevolving anomalies to the observed SSTs that are specified for REF1. However, the community sees at least two problems with this approach. First, the patterns and temporal variability are changed, depending on the shortcomings of the coupled system. Second, the ice distribution in the SST observational dataset is not the same as in the model. This is especially problematic in regions where the ice cover disagrees significantly between model and observations.
We can avoid these problems if the onesimulation-for-all design is abandoned in
favour of a design including two separate
simulations. The first would be for the
observed period (REF1), for which we can
assess the degree to which observed stratospheric
dynamics and chemistry are reproduced.
The second would be an internally
consistent simulation from the past to the
future (REF2). With this approach, fully
coupled atmosphere-ocean CCMs with the
atmosphere extending to the middle atmosphere
and with coupled chemistry, will
use their internally calculated SSTs in
REF2, whereas all other CCMs will use
modelled SSTs from a coupled atmosphere-ocean simulation for the full time
period (1980 to 2025 or longer). One constraint
is to make the external SST dataset
consistent with the GHG scenario A1B.
There has also been a debate on whether or
not the model simulations should use the
same set of SSTs for future years in REF2.
Obviously, if different SSTs are used, the
forced low frequency variability could be
quite different between the simulations. One
of the biggest uncertainties is the predictability
of the decadal timescale and the separation
of internal from externally-forced variability
in the models. However, the focus of
the future simulation is not a model-model
intercomparison. Rather we would like to
provide the best available prediction of the
future. REF2 is a simulation that focuses on
consistency and that follows the IPCC simulations.
Essentially we are asking that modelling
groups make their best prediction.
Therefore, it is not necessary to have consistent
SSTs. In fact, by applying different SSTs,
the change in climate and its variability are
effectively included in the simulation. (To
use a common set of SSTs would certainly
underestimate the uncertainty in future climate
predictions, and any error in those SST
predictions would lead to a bias in the model
predictions.)
Finally, an agreement was reached that at least a subset of groups will run with the same SST forcings, whereas others will use internally calculated SSTs or model-consistent SSTs. This will allow us to address both views.
Summary and Outlook
CCM Modelling groups are encouraged to
run the proposed reference simulations with
the same forcings. In order to facilitate the
set-up of the reference simulations,CCMVal
has established a website where the forcings
for the simulations can be downloaded
(http://www.pa.op.dlr.de/CCMVal/Forcings
/CCMVal_Forcings.html). This web site was
developed to serve the needs of the CCM
community, and encourage consistency of
anthropogenic and natural forcings in future
model-model and model-observation intercomparisons.
Any updates as well as detailed
explanation and further discussion will be
placed on this website.
We encourage the groups to run both simulations, REF1 and REF2. If a model only provides REF2 it will be more difficult to assess the model’s ability to simulate realistic trends and variability. Changes on the decadal timescale are not necessarily part of the secular trend. It is quite probable that some of the changes are due to low frequency variability that is likely to be unpredictable if the source is internal. It is then possible that some of the differences between the deterministic model predictions will be attributed to unpredictability and not to differences in the fundamental forcings and responses of the models. For these reasons, we encourage groups to run ensembles. Depending on computer resources, a subset of groups might also be able to carry out sensitivity simulations. Especially if the prediction simulation only covers the short-term prediction (e.g. until 2025), it would be very useful to see how the prediction changes if a solar cycle and the QBO are included. If you are interested in this topic, please run the sensitivity simulation SCN2.
In agreement with the experts in this field, it
has been decided that the enhanced stratospheric
bromine scenario should not be
included in the reference simulation (REF1
and REF2). Enhancing the inorganic
bromine reservoir increases BrO, a reaction
partner for anthropogenically derived ClO,
above that found in the standard simulation
in the first few kilometres of the stratosphere.
The sensitivity of ozone to enhanced
bromine in the lowermost stratosphere will
likely depend on details of the model simulation
of ClO just above the tropopause.
Due to the inherent three-dimensional
nature of accurately simulating ClO and
BrO near the tropopause, it is hoped that
one or more of the CCMs will carry out
simulation SCN1. It is also expected that 2D
and 3D chemical transport model (CTM)
simulations will be relied upon to further
assess the sensitivity of ozone trends to
bromine in the lowermost stratosphere for
the next UNEP/WMO ozone assessment.
CCMVal will provide a list of model recommendations that will be placed on the website.We encourage groups to check the CCMVal forcing website for recommendations concerning the model set-up and the variables that should be stored in order to allow for sophisticated intercomparisons of chemistry, transport, dynamics and radiation within the CCM.
A detailed intercomparison of CCM results
and observations has successfully started.
Model results from 10 European model
groups that are participating in the
European Integrated Project SCOUT-O3
and one model group from outside Europe
(CCSR/NIES) have been obtained. The
first phase of the intercomparison will be
based on existing runs.With the exception
of total column ozone, only transient
model simulations for the time period
1980 to 1999 will be compared (no time
slice experiments). We would like to
encourage other model groups to join in
the intercomparison and to send data from
existing runs. As soon as the results of the
CCMVal simulations with equal forcings
become available, the intercomparisons
and analyses will be repeated. It will be
interesting to see how the results and interpretation
change when runs with equal
forcings are compared. CCMVal is still
looking for volunteers from around the
world to assist with the intercomparison. If
you are interested in a certain diagnostic or
scientific topics, please contact us.
A second CCMVal workshop will be held from October 17 to 19, 2005 at the National Center for Atmospheric Research in Boulder, Colorado (http://www.pa.op.dlr.de/workshops/ CCMVal2005/). The 2005 Chemistry- Climate Modelling Workshop will focus on progress in chemistry-climate modelling and process-oriented validation of CCMs.
The aims of the workshop are to identify near-term and long-term goals within the validation architecture and to coordinate activities among the participating modelling groups. In addition we will discuss how CCM results can support the WMO/UNEP Scientific Assessment of Ozone Depletion 2006 and other upcoming assessments. We encourage the participation of global modellers as well as scientists who make atmospheric observations that are relevant for model evaluation.
Acknowledgements
We wish to thank the community for a lively and fruitful discussion and for the excellent cooperation. Special thanks go to Byron Boville, Christoph Brühl, Neal Butchart, Martyn Chipperfield, David Considine, Martin Dameris, David Fahey, Rolando Garcia, Marco Giorgetta, Elisa Manzini, Jerry Meehl, Stephen Montzka, A. Ravishankara and Ross Salawitch who helped us formulate the reference simulations and putting together the CCMVal forcing website.
We would also like to thank H. Akiyoshi, J. Austin, S. Bekki, G. Bodeker, P. Braesicke, N. Harris, D. Hauglustaine, A. Gettelman, I. Isaksen, M. Gauss, U. Langematz, E. Manzini, T. Nagashima, P. Newman, S. Pawson, G. Pitari, D. Rind, E. Rozanov, K. Shibata, D. Shindell, R. Stolarski, H. Struthers,M. Takahashi and J. Pyle for general comments.
References
Austin, J. et al., 2003: Uncertainties and assessments of chemistry-climate models of the stratosphere, Atmos. Chem. Phys., 3, 1-27.
Anderson, J. L. et al., 2004: The new GFDL global atmosphere and land model AM2/LM2: Evaluation with prescribed SST simulations, J. Climate, in press.
Austin, J., 2002: A three-dimensional coupled chemistry-climate model simulation of past stratospheric trends, J. Atmos. Sci., 59, 218-232.
Austin, J. and N. Butchart, 2003: Coupled chemistry-
climate model simulation for the period
1980 to 2020: ozone depletion and the start of
ozone recovery, Q. J. R. Meteorol. Soc., 129,
3,225-3,249.
Beagley, S.R. et al., 1997: Radiative-dynamical climatology of the first-generation Canadian Middle Atmosphere Model, Atmos.-Ocean, 35, 293-331.
Braesicke, P. and J. A. Pyle, 2003: Changing ozone and changing circulation: Possible feedbacks?, Geophys. Res. Lett., 30(2), 1059, doi:10.1029/2002GL015973.
Braesicke, P. and J. A. Pyle, 2004: Sensitivity of dynamics and ozone to different representations of SSTs in the Unified Model, Q. J. R. Meteorol. Soc., 130, 2,033-2,046.
Dameris, M. et al., 2005: Long-term changes and
variability in a transient simulation with a chemistry-
climate model employing realistic forcings,
Atmos. Chem. Phys. Discuss., 5, 2297-2353.
de Grandpré, J. et al., 2000: Ozone climatology
using interactive chemistry: Results from the
Canadian Middle Atmosphere Model, J.
Geophys. Res., 105, 26,475-26,491.
Egorova, T. et al., 2005: Chemistry-climate
model SOCOL: a validation of the present-day
climatology, Atmos. Chem. Phys. Discuss., 5,
509-555.
Eyring,V. et al., 2004: Comprehensive Summary on the Workshop on “Process-Oriented Validation of Coupled Chemistry-Climate Models”, SPARC Newsletter No. 23, p. 5-11, http://www.atmosp.physics.utoronto.ca/SPARC /News23/23_Eyring.html.
Eyring,V. et al., 2005: A strategy for process-oriented validation of coupled chemistry-climate models, Bull. Am. Meteorol. Soc., in press.
IPCC, 2000: Emission Scenarios. A Special Report of IPCC Working Group III, Cambridge, University Press, Cambridge, UK.
Jöckel, P. et al., 2005: Technical Note: The Modular Earth Submodel System (MESSy) - a new approach towards Earth System Modeling, Atmos. Chem. Phys., 5, 433-444.
Labitzke, K. et al. 2002: The Berlin stratospheric data series.Meteorological Institute, Free University of Berlin, CD-ROM.
Langematz, U. et al., 2005: Chemical effects in
11-year solar cycle simulations with the Freie
Universitaet Berlin Climate Middle Atmosphere
Model (FUB-CMAM-CHEM), Geophys. Res.
Lett., in press.
Lean, J. et al., 1997: Detection and parameterization of variations in solar mid and near ultrviolet radiation (200 to 400 nm). J. Geophys. Res., 102, 29,939-29,956.
Manzini, E. et al., 2003: A new interactive chemistry climate model. 2: Sensitivity of the middle atmosphere to ozone depletion and increase in greenhouse gases: implications for recent stratospheric cooling, J. Geophys. Res.,108(D14), 4429, doi:10.1029/2002JD002977.
Nagashima, T. et al., 2002: Future development of the ozone layer calculated by a general circulation model with fully interactive chemistry, Geophys. Res. Lett., 29 (8), 1162, doi: 10.1029/2001GL014026.
Naujokat, B., 1986: An update of the observed quasi-biennial oscillation of the stratospheric winds over the tropics. J. Atmos. Sci., 43, 1873- 1877.
Pawson, S. et al., 2000: The GCM-Reality Intercomparison Project for SPARC: Scientific Issues and Initial Results, Bull. Am. Meteorol. Soc., 81,781-796.
Pitari, G. et al., 2002: Feedback of future climate and sulfur emission changes an stratospheric aerosols and ozone, J. Atmos. Sci., 59(3), 414–440.
Rayner, N. A. et al., 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century, J. Geophys. Res., 108, No. D14, 4407 10.1029/2002JD002670.
Roeckner E. et al., 2003: The atmospheric general circulation model ECHAM5, Part 1, MPI Report, No. 349, ISSN 0937-1060.
Salawitch, R. J. et al., 2005: Sensitivity of Ozone to Bromine in the Lower Stratosphere, Geophys. Res. Lett., in press.
Sander, R. et al., 2005: Technical Note: The new comprehensive atmospheric chemistry module MECCA, Atmos. Chem. Phys., 5, 445-450.
Sassi, F. et al., 2005: The effects of interactive ozone chemistry on simulations of the middle atmosphere, Geophys. Res. Lett., submitted.
Schmidt, G. A. et al., 2005a: Present day atmospheric simulations using GISS ModelE: Comparison to in-situ, satellite and reanalysis data, J. Climate, in press.
Schmidt, H. et al., 2005b: The HAMMONIA Chemistry Climate Model: Sensitivity of the Mesopause Region to the 11-year Solar Cycle and CO2 Doubling, J. Climate, submitted.
Shibata, K and M. Deushi, 2005: Partitioning
between resolved wave forcing and unresolved
gravity wave forcing to the quasi-biennial oscillation
as revealed with a coupled chemistry-climate
model, Geophys. Res. Lett., in press.
Shibata, K. et al., 2005: Development of an MRI
chemical transport model for the study of
stratospheric chemistry, Papers in Geophysics
and Meteorology, 55, 75-118, in press.
Steil, B. et al., 2003: A new interactive chemistry
climate model. 1: Present day climatology and
interannual variability of the middle atmosphere
using the model and 9 years of
HALOE/UARS data, J. Geophys. Res., 108(D9),
4290,doi:10.1029/2002JD002971.
Takigawa, M. et al., 1999: Simulation of ozone
and other chemical species using a Center for
Climate Systems Research/National Institute for
Environmental Studies atmospheric GCM with
coupled stratospheric chemistry, J. Geophys.
Res., 104, 14,003-14,018.
Tian, W. and M.P. Chipperfield, 2005: A New coupled chemistry-climate model for the stratosphere: The importance of coupling for future O3-climate predictions, Q. J. Roy. Met. Soc., 131, 281-303.
WMO, 2003: Scientific Assessment of Ozone Depletion: 2002, Global Ozone Research and Monitoring Project - Report No. 47, 498 pp,Geneva.
Wong, S. et al., 2004: A global climate-chemistry
model study of present-day tropospheric chemistry
and radiative forcing from changes in tropospheric
O3 since the preindustrial period, J. Geophys.
Res., 109, No. D11,doi:10.1029/2003JD003998.