Overview of the New CCMVal Reference and Sensitivity Simulations in Support of Upcoming Ozone and Climate Assessments and the Planned SPARC CCMVal Report

Veronika Eyring, DLR-Institut für Physik der Atmosphäre, Germany (Veronika.Eyring@dlr.de),

Martyn P. Chipperfield, University of Leeds, UK (martyn@env.leeds.ac.uk),

Marco A. Giorgetta, Max Planck Institute for Meteorology, Germany (marco.giorgetta@zmaw.de),

Douglas E. Kinnison, National Center for Atmospheric Research, USA (dkin@ucar.edu),

Katja Matthes, Freie Universität Berlin, Germany (katja.matthes@met.fu-berlin.de)

Paul A. Newman, NASA Goddard Space Flight Center, USA (Paul.A.Newman@nasa.gov),

Steven Pawson, NASA Goddard Space Flight Center, USA (pawson@gmao.gsfc.nasa.gov),

Theodore G. Shepherd, University of Toronto, Canada (tgs@atmosp.physics.utoronto.ca),

Darryn W. Waugh, Johns Hopkins University, Baltimore, USA (waugh@jhu.edu).

On behalf of the CCM Validation Activity for SPARC (CCMVal)

The overriding concept behind the choice of these reference and sensitivity simulations is to achieve the best possible scientific results. Accordingly, the first requirement is to evaluate the models against observations. That is the rationale behind REF0, a time-slice experiment performed under conditions equivalent to 2000, for the period for which the highest density in observations is available. A long reference run will provide good statistics for the model comparison. The second requirement is to see how well the models can reproduce the past behaviour of stratospheric ozone. That is the rationale behind the 'past' transient reference simulation REF1, which is forced by observations. Experience in Eyring et al. [2006] showed that it is important to establish a good baseline from which to identify the effects of halogens on ozone, and to avoid spin-up problems. Based on this experience, REF1 requires around 10-years spin-up prior to a 1960 start. The third requirement is to see what the models predict for the future evolution of stratospheric ozone. That is the rationale behind the ‘future’ transient reference simulation REF2, which is forced by trace gas projections and modeled sea surface temperatures (SSTs). Experience in Eyring et al. [2007] showed that it is important to have a continuous time series from the models covering both past and future, in order to avoid inhomogeneity in the datasets (in terms of both absolute values and variability), and also that the simulations extend to 2100 in order to fully capture the process of ozone recovery from the effects of ozone-depleting substances (ODSs). Based on this experience, REF2 also requires around 10-years spin-up prior to a 1960 start, and extension to 2100. To provide continuity with Eyring et al. [2007], and track any changes in the models, REF2 is based on the same GHG scenario (SRES A1B, medium) as used in Eyring et al. [2007]. For both REF1 and REF2, it is recommended that groups perform at least a small ensemble (e.g. three simulations) so that an uncertainty range for the model results can be established.

1. CCMVal Reference Simulations

This section gives an overview of the main characteristics of the new CCMVal reference (REF) simulations. The key characteristics are also summarised in Table 1.

REF0 is a time-slice experiment for conditions equivalent to the year 2000, proposed to facilitate the comparison of model output against constituent datasets from various high-quality observational data sources and meteorological analyses under a period of high chlorine loading and peak ozone losses. Each simulation is integrated over 20 annual cycles following adequate spin-up (10 years is recommended). The model data of these 20 years are evaluated against contemporary observations (i.e., during the satellite measurement period of UARS, Aura, ENVISAT, Odin, SAGE, SBUV, TOMS, ACE, etc.) and compared to results of other CCMs. The 20 years of output are necessary in order to compare mean quantities with large variability (e.g., polar temperatures). It should be possible to start the analysis of runs based on REF0 much earlier than the other scenarios and to collect extended output, which will be useful for developing the diagnostics as well as providing a preliminary evaluation.

1.2 Reproduce the past: Reference Simulation 1 (REF1), Core Time Period 1960 to 2006

REF1 (1960-2006) is defined as a transient run from 1960 to the present and is designed to reproduce the well-observed period of the past 35 years during which ozone depletion is well recorded. It allows a more detailed investigation of the role of natural variability and other atmospheric changes important for ozone balance and trends. All forcings in this simulation are taken from observations.The set-up and forcings are very similar to the REF1 simulations that were evaluated in Eyring et al. [2006]. A re-assessment of temperatures, trace species and ozone in the CCM simulations will allow documenting progress of individual models and overall progress on the representation of key processes compared to the last CCM assessment. The comparison of CCM results with observations will also allow some groups to identify and correct previously unrecognised model errors and will help to indicate a range of model uncertainties. This transient simulation includes all anthropogenic and natural forcings based on changes in trace gases, solar variability, volcanic eruptions, quasi-biennial oscillation (QBO), and SSTs/SICs. REF1 covers the time period from at least 1960 to 2006 (with around 10 years spin-up prior to 1960) to examine model variability and to replicate as closely as possible the atmospheric state in this period.

Greenhouse Gases (N2O, CH4, and CO2) between 1950 and 1996 are taken from IPCC [2001] and merged with the NOAA observations forward through 2006. NOAA CO2, CH4, and N2O were scaled to agree on January 1996 with the historical IPCC data.Surface mixing ratios of Ozone Depleting Substances (CFC-11, CFC-12, CFC-113, CFC-114, CFC-115, CCl4, CH3CCl3, HCFC-22, HCFC-141b, HCFC-142b, Halon1211, Halon1202, Halon1301, and Halon2402) in REF1 are taken from Table 8-5 of WMO [2007]. The mixing ratios are calculated by a box model using yearly emissions and are given for the middle of the month. The time series does not contain a yearly variation in mixing ratios. Through 2004 the values are maximally forced to equal global estimates calculated from observations (for details see Chapter 8 of WMO [2007]). For models that do not wish to represent all the brominated and chlorinated species in Table 8-5 of WMO [2007], the halogen content of species that are considered should be adjusted such that model inputs for total chlorine and total bromine match the time series of total chlorine and bromine given in this table. Sea surface temperatures and sea ice concentrations in REF1 are prescribed as monthly mean boundary conditions following the global sea ice concentration and sea surface temperature (HadISST1) dataset provided by the UK Met Office Hadley Centre [Rayner et al., 2003]. This dataset is based on combined satellite and in situ observations. To prepare the data for use in forcing a model, and in particular to correct for the loss of variance due to time-interpolation of monthly mean data, it is recommended that each group follows the procedures described on the C20C project website (see http://grads.iges.org/c20c/c20c_forcing/karling_instruct.html). This describes how to apply the AMIP II variance correction method (see http://www-pcmdi.llnl.gov/projects/amip/AMIP2EXPDSN/BCS/amip2bcs.php for details) to the HadISST1 data.

• Surface Area Densities (SADs) from observations are considered in REF1. A monthly zonal mean time series for SADs from 1979 to 2005 was created using data from the SAGE I, SAGE II, SAM II, and SME instruments (units: square microns per cubic centimeter). This time series was published in SPARC [2006]. In addition, uncertainties of the SAGE II dataset are described in detail in Thomason et al. [2007]. The altitude and latitude range of this dataset is 12 - 40 km and 80°S – 80°N respectively. The SPARC SAD dataset does have data gaps, which occur mainly in lower tropical altitudes (below 16 km) and during the El Chichón period. Above 26 km there are large data gaps in the mid-to-high latitude region. There are also missing data at all altitudes in the high latitude polar regions. The NCAR group modified this new SPARC SAD dataset for CCM applications by filling the missing data using a linear interpolation approach in altitude and latitude. Large gaps of data above 26 km were filled with background values of 0.01 square microns per cubic centimeter. In the upper troposphere, tropical latitudes, data gaps were filled without scientific considerations.  The previous CCMVal SAD dataset was created by D. Considine and used in Eyring et al. [2006]. The modified SPARC SAD time series shows minor deviations from the previous CCMVal SAD time series in the mid-latitudes and tropics. The most significant changes occur in high latitude regions, specifically during the period influenced by major volcanic eruptions. Here, the previous CCMVal SAD time series is consistent with background values (see description in the header of the previous CCMVal SAD time series input file for details on how this dataset was created). The Agung eruption in 1963 is not covered by this dataset. To correct for this eruption, the method described in Dameris et al. [2005] was applied. The well documented years following the eruption of Mt. Pinatubo (1991–1994) have been adopted and associated with the period 1963–1966 with modifications based on published results to account for differences in total mass of sulfate aerosols in the stratosphere, in maximum height of the eruption plumes, and in the geographical location of the volcanoes. Above the maximum vertical extent of Agung’s eruption plume the annual mean of 1979 has been incorporated. For the time periods 1950–1962 and 1968–1978 the annual mean of 1979 has been adopted.  For the new CCMVal simulations, we recommend using the new modified SPARC SAD time series described above, in particular for those models that have a heterogeneous chemistry halogen activation approach based solely on the occurrence of super cooled ternary (STS) PSCs.

• Stratospheric warming and tropospheric-surface cooling due to volcanic eruptions are either calculated online by using aerosol data or by prescribing heating rates and surface forcing. For those models that do not calculate this effect online, pre-calculated zonal mean aerosol heating rates (K/day) and net surface radiative forcing (W/m2) monthly means from January 1950 to December 1999 for all-sky condition are available on the CCMVal website. They were calculated using volcanic aerosol parameters from Sato et al. [1993], Hansen et al. [2002] and GISS ModelE radiative routines and climatology [Schmidtet al., 2006; G. Stenchikov and L. Oman, pers. communication, 2007]. In addition to the larger volcanic eruptions (Agung, 1963; El Chichón, 1982; Pinatubo, 1991), smaller ones like Fernandina (1968 in Galapagos) and Fuego (1974 in Guatemala) are included. The surface radiative forcing is negative, corresponding to cooling caused by volcanic aerosols. The right way to use these datasets to mimic effect of volcanic eruptions would be to apply heating rates to the atmosphere and cooling flux to the surface. Heating rates and surface forcing would characterise the entire volcanic effect, i.e. stratospheric warming and tropospheric-surface cooling. If the focus is on stratospheric processes only aerosol heating rates could be used without causing any problem.
• Solar variability. To account for the highly variable and wavelength-dependent changes in solar irradiance, daily spectrally resolved solar irradiance data from 1 Jan 1950 to 31 Dec 2006 (in W/m2/nm) are provided. The data are derived with the method described in Lean et al. [2005] and are available with the following spectral resolution:1 nm bins from 0 to 750 nm; 5 nm bins from 750 to 5000 nm; 10 nm bins from 5000 to 10000 nm; 50 nm bins from 10000 to 100000 nm. Each modelling group is required to integrate these data over the individual wavelength intervals (a) in their radiation scheme (to adjust the shortwave heating rates) and (b) in their chemistry scheme (to adjust the photolysis rates). It is recommended to use the provided solar flux data directly (integrated over the respective intervals in the radiation and chemistry schemes), rather than a parameterisation with the F10.7 cm radio flux previously used.Additional information as well as the data can be found on the SOLARIS website at http://www.geo.fu-berlin.de/en/met/ag/strat/research/SOLARIS/Input_data/index.html.
• Quasi-Biennial Oscillation. The QBO is generally described by zonal wind profiles measured at the equator. The QBO is an internal mode of variability of the atmosphere that dominates the interannual variability in wind in the tropical stratosphere and contributes to the variability in the extratropical dynamics. It is recognised that the QBO is important for understanding interannual variability in ozone and other constituents of the middle atmosphere, in the tropics and extratropics. Currently only a few atmospheric GCMs or CCMs simulate a realistic QBO and hence QBO related influences. Simulated QBOs are generally independent of observed time series because their phase evolutions are not bound by external boundary conditions. Realistic simulated QBOs, however, have similar periods, amplitudes and composite structures in observations. The assimilation of the QBO, for example by a relaxation of zonal winds in the QBO domain ("nudging"), hence may be useful for two reasons: First to obtain a QBO in GCMs that do not simulate the QBO internally, so that for example QBO effects on the general circulation are present; and second to synchronise the QBO simulated in a GCM with a given QBO time series, so that simulated QBO effects, for example on ozone, can be compared to observed signals. Datasets for this purpose and examples for the "nudging" of the QBO in a GCM are discussed on the CCMVal web site.
• Ozone and aerosol precursors (CO, NMVOC, NOx and SO2) from 1960 to 2000 are taken from the extended dataset of the RETRO project [Schultz et al., 2007]. For the spin-up period from 1950 to 1959 we recommend using the 1960 values from this dataset. The dataset will be extended through 2006 by using trend estimates and will be harmonised so that regional totals are the same as in RETRO for the year 2000.

Top

Table 1: Summary of proposed CCMVal reference simulations. For better resolution, please contact the SPARC IPO

 

1.3 Making predictions: Reference simulation 2 (REF2), Core time period 1960 to 2100

REF2 is an internally consistent simulation from the past into the future. The objective of REF2 is to produce best estimates of the future ozone-climate change up to 2100 under specific assumptions about GHG increases (Scenario SRES A1B) and decreases in halogen emissions (adjusted Scenario A1) in this period. REF2 only includes anthropogenic forcings. External natural forcings such as solar variability and volcanic eruptions are not considered, as they cannot be known in advance, and the QBO is not externally forced (also as it cannot be known in advance; furthermore it represents the internal dynamics of the model). To avoid introducing inhomogeneity into the time series, these natural forcings are not applied in the past either.

2. CCMVal Sensitivity and Control Simulations

The following CCMVal sensitivity and control experiments are proposed:

SCN1 (1960-2006, REF1 with additional organic bromine):Observations suggest that stratospheric inorganic bromine (Bry) derived from the breakdown of long-lived (>3 years) organic source gases (i.e., CH3Br, halon-1211, halon-1301, and halon-2402) underestimate the Bry abundance in the stratosphere by about 5 ppt, with estimates ranging from 3 to 8 pptv. Observations also suggest that very short-lived substances (VSLS) with atmospheric lifetimes of less than 0.5 years make up the missing stratospheric Bry [Chapter 2 of WMO 2003, 2007]. The supply of bromine from VSLS can result in a substantial fractional increase to the amount of bromine in the lowermost stratosphere, with important consequences for ozone trends and the photochemical budget of ozone, particularly during times of high aerosol loading.  SCN1 was developed to quantify the effect of bromine on ozone from VSLS. This scenario is consistent with REF1 with the exception that an additional source of 5 pptv of Bry from VSLS is included. In SCN1, we are proposing to add the species dibromomethane (CH2Br2) to the chemical mechanism of participating CCMs. The lifetime of CH2Br2 is approximately 120 days at 5 km [Table 2.3, WMO 2007] and the reaction with OH is the dominant loss process [Table 2.4, WMO 2003]. The estimated fraction of CH2Br2 mixing ratio in the tropical upper troposphere relative to the abundance in the marine boundary layer is approximately 0.8 [Table 2.2, WMO 2007]. Therefore, if the surface abundance of CH2Br2 is set to 3 pptv, the stratospheric Bry abundance should increase by approximately 5 pptv (i.e., 5 pptv total Bry / 2 Br per CH2Br2 molecule / 0.8 is equal to ~3.0 pptv CH2Br2). If modelling groups prefer not to add a new species to their CCM, we propose adding 5 pptv of total bromine to the shortest-lived organic bromine source gas currently included in the chemical mechanism.

SCN2b (1960-2100, REF2 with halogens fixed at 1960 levels) is a transient simulation similar to REF2, but withhalogens fixed at levels corresponding to 1960 throughout the simulation, whereas GHGs and SSTs/SICs are the same as in REF2. It is designed to address the science question of what are the effects of halogens on stratospheric ozone and climate, in the presence of climate change. By comparing SCN2b with REF2, the impact of halogens can be identified and it can be assessed at what point in the future the halogen impact is undetectable, i.e. within climate variability. This was the definition of full recovery of stratospheric ozone from the effects of ODSs that was advanced in WMO [2007].

SCN2c (1960-2100, REF2 with GHGs fixed at 1960 levels) is a transient simulation similar to REF2, but withGHGs fixed at levels corresponding to 1960 throughout the simulation, whereas the adjusted scenario A1 halogens are the same as in REF2. It is designed to address the science question of how nonlinear are the atmospheric responses to ozone depletion/recovery and climate change. To that end, GHGs are fixed at 1960 levels throughout the simulation. SSTs/SICs will be a 1955-1964 average of the values used in REF2. By comparing the sum of SCN2b and SCN2c (each relative to the 1960 baseline) with REF2, the nonlinearity of the responses can be assessed. SCN2c also addresses the policy-relevant (if academic) question of what would be the impact of halogens on the atmosphere in the absence of climate change.

SCN2d(1960-2100, REF2 with natural forcings and QBO) is designed to address the impact of ‘realistic’ natural variability on the REF2 simulations, for which the natural variability is underestimated. This sensitivity simulation is 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/SICs are simulated or prescribed as in REF2. GHGs and halogens will be the same as in REF2. We recommend using a repeating solar cycle based on the observed daily spectra described in Lean et al. [2005]. It is proposed to repeat the solar cycles 20 to 23 (1962-2004) and therefore neglect the extreme solar cycle 19 (peaking in 1957/58).

CTL0 (mininum 20 years, REF0 but for 1960 conditions) is a time-slice simulation under 1960 conditions designed to establish a baseline control simulation for the reference and sensitivity simulations. The objective is to provide a statistical characterisation of the internal variability of the CCMs prior to major perturbations of the ozone layer. The control 1960 simulation has ODSs, GHGs, and solar irradiance held fixed. SSTs/SICs in this simulation are (analogous to REF0) prescribed from observations by using a climatological mean derived from years 1955 to 1964 of the HadISST1 dataset, repeating every year. Given these design constraints, the only source of variability is the internal dynamics of the atmosphere (and land properties like snow cover and soil moisture), while natural variability arising from solar variability and volcanic eruptions is excluded. Moreover, there are no secular changes in greenhouse gases and halogens, hence no long-term trends, which will allow a statistical characterisation of random short-term trends. This is important for assessing the statistical significance of trends in the reference and sensitivity simulations. After a spin-up period of about 10 years, each simulation is integrated over at least 20 annual cycles for analysis. However, the goal of a 46-year control simulation is strongly encouraged, 46 years being the length of the REF1 simulation. Some of the reference and sensitivity simulations could branch off from CTL0, thereby reducing their respective spin-up periods to a few years.

• Trace gas forcings are characteristic of 1960 levels for both ODSs and GHGs. The surface concentrations of GHGs are based on IPCC [2001] while the surface halogens are based on Table 8-5 of WMO [2007] for the year 1960. Both ODSs and GHGs repeat every year.
• Background aerosol is prescribed from the extended SPARC [2006] SAD climatology (see REF1) for the year 1979.
• Solar irradiance is averaged over 1-solar cycle to provide a mean solar flux for the year 1960.
• Emissions of ozone and aerosol precursors (CO, NMVOC, NOx and SO2) for 1960 conditions are taken from the extended RETRO dataset and averaged over the period 1960 to 1962.
• Sea surface temperatures and sea ice concentrations in this simulation are prescribed from observations by using a climatological mean derived from the years 1955 to 1964 HadISST1 dataset provided by the UK Met Office Hadley Centre [Rayner et al., 2003]. Prescribed SSTs and ice distribution repeat each year in CTL0.
• Quasi-Biennial Oscillation. In this run the QBO is not externally forced and only included by models that internally generate a QBO.

Top

Table 2: Summary of proposed CCMVal control and sensitivity simulations. For better resolution, please contact the SPARC IPO

3. Summary and Outlook

CCM groups are encouraged to run the proposed reference simulations with the specified 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 inter-comparisons. Any updates as well as detailed explanation and further discussion will be placed on this website. In addition to the reference runs, the groups are encouraged to run as many sensitivity simulations as possible. The hope is that these additional runs will be available in time to provide useful input for the anticipated UNEP/WMO Ozone Assessment in 2010, so that the ozone projections from the CCMs can be assessed for different halogen and GHG scenarios, and not just from one scenario as in WMO [2003, 2007].

The proposed simulations will be evaluated as part of the planned SPARC CCMVal Report by 2009 in time for consideration in the anticipated UNEP/WMO Ozone Assessment in 2010. The SPARC CCMVal report itself has two major aims: 1) provide valuable base material for that assessment, and 2) improve the understanding of the strengths and weaknesses of CCMs and thus increase their integrity and credibility. Regarding mechanisms for model evaluation, a set of standard diagnostics has been agreed at the first CCMVal workshop (Grainau, Germany, November 2003) and further refined at the second workshop (NCAR, Boulder, USA, October 2005). Output for these standard diagnostics [Eyring et al., 2005] and possible additional diagnostics needed for the individual chapters of the SPARC CCMVal report will be collected in Climate and Forecast (CF) standard compliant netCDF format from all models in the central database at the British Atmospheric Data Centre (BADC). In addition it is anticipated to obtain observational datasets for the core diagnostics. The specified forcings for the new reference simulations and the new data request will be made available for download at the CCMVal website. The proposed timeline for the SPARC CCMVal report can be found at http://www.pa.op.dlr.de/CCMVal/SPARC_CCMValReport/SPARC_CCMValReport_Timeline.html.

Acknowledgements

References

Collins, W. D. et al. (2006), The Community Climate System Model version 3 (CCSM3), J. Clim., 19, 2122-2143.

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., 5, 2121-2145.

Eyring, V. et al. (2005), A strategy for process-oriented validation of coupled chemistry-climate models, Bull. Am. Meteorol. Soc., 86, 1117–1133.

Eyring, V. et al. (2006), Assessment of temperature, trace species and ozone in chemistry-climate model simulations of the recent past, J. Geophys. Res., 111, D22308, doi:10.1029/2006JD007327.

Eyring, V. et al. (2007), Multi-model projections of ozone recovery in the 21st century, J. Geophys. Res., 112, D16303, doi:10.1029/2006JD008332.

Giorgetta, M. A., and L. Bengtsson (1999), The potential role of the quasi-biennial oscillation in the stratosphere-troposphere exchange as found in water vapor in general circulation model experiments, J. Geophys. Res., 104, 6003-6020.

Hansen, J., et al. (2002), Climate forcings in Goddard Institute for Space Studies SI2000 simulations, J. Geophys. Res., 107(D18), 4347, doi:10.1029/2001JD001143.

IPCC (Intergovernmental Panel on Climate Change) (2000), Special report on emissions scenarios: a special report of Working Group III of the Intergovernmental Panel on Climate Change, 599 pp., Cambridge University Press, Cambridge, U.K.

IPCC (Intergovernmental Panel on Climate Change) (2001), Climate change 2001: The scientific basis. Contribution of Working Group 1 to the Third Assessment Report, J.T. Houghton (Eds.), Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Johns, T. C. et al. (2006), The new Hadley Centre climate model HadGEM1: Evaluation of coupled simulations, Journal of Climate, 19, 1327-1353.

JPL (Jet Propulsion Laboratory) (2006), Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies. Evaluation 15, JPL Publication No. 06-2, NASA Panel for Data Evaluation, NASA Aeronautics and Space Administration, Pasadena, CA, USA, 73.

Large, W. G., and G. Danabasoglu (2006), Attribution and Impacts of Upper-Ocean Biases in CCSM3. J. Climate, 19, 2325-2346.

Lean, J. L. et al.(2005), SORCE contributions to new understanding of global change and solar variability, Solar Phys., 230:27-53.

Meehl G. A., K. Hibbard et al. (2007), Summary report: A Strategy for Climate Change Stablization Experiments with AOGCMs and ESMs, WCRP Informal Report N° 3/2007; ICPO Publication N° 112, IGBP Report N° 57.

Oldenborgh, G. J. van , S. Y. Philip, and M. Collins (2005), El Niño in a changing climate: a multi-model study, Ocean Sci., 1, 81-95.

Olivier, J. et al. (2005), Recent trends in global greenhouse gas emissions: regional trends and spatial distribution of key sources, In: "Non-CO2 Greenhouse Gases (NCGG-4)", van Amstel, A. (coord.), 325-330, Millpress, Rotterdam, ISBN 90 5966 043 9.

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.

Sato, M. et al. (1993), Stratospheric aerosol optical depths, 1850-1990, J. Geophys. Res., 98, 22987-22994.

Schmidt, G. A., et al. (2006), Present-day atmospheric simulations using GISS ModelE: Comparison to in situ, satellite, and reanalysis data, J. Clim., 19, 153-192.

Schultz, M., et al. (2007), Emission data sets and methodologies for estimating emissions (http://retro.enes.org/reports/D1-6_final.pdf), REanalysis of the TROpospheric chemical composition over the past 40 years, A long-term global modeling study of tropospheric chemistry funded under the 5th EU framework programme, EU-Contract No. EVK2-CT-2002-00170.

SPARC (2006), SPARC Assessment of Stratospheric Aerosol Properties (ASAP), Tech. Rep. WMO-TD No. 1295, WCRP Series Report No. 124, SPARC Report No. 4, Berrieres le Buisson Cedex.

Thomason, L. W. et al. (2007), SAGE II measurements of stratospheric aerosol properties at non-volcanic levels, Atmos. Chem. Phys. Discuss., 7, 6959-6997.

Van Aardenne, J. et al. (2001), A 1 x 1 degree resolution dataset of historical anthropogenic trace gas emissions for the period 1890-1990. Global Biogeochemical Cycles, 15(4), 909-928.

Van Aardenne, J. et al. (2005), The EDGAR 3.2 Fast Track 2000 dataset (32FT2000), Technical documentation, http://www.mnp.nl/edgar/model/v32ft2000edgar.

World Meteorological Organization (WMO)/United Nations Environment Programme (UNEP) (2007), Scientific Assessment of Ozone Depletion: 2006, World Meteorological Organization, Global Ozone Research and Monitoring Project, Report No. 50, Geneva, Switzerland.

Top