AerChemMIP

Goal

Past climate change has been forced by a wide range of chemically reactive gases, aerosols, and well mixed greenhouse gases (WMGHGs), in addition to CO2. Scientific questions and uncertainties regarding chemistry-climate interactions range from regional scales (e.g., tropospheric ozone and aerosols interacting with regional meteorology), to long-range connections (e.g., hemispheric transport of air pollution, the impacts of lower stratospheric ozone and temperatures on surface climate), to global integration (e.g., the lifetimes of CH4 and N2O).

AerChemMIP proposes to contribute to CMIP6 through the following: 1) diagnose forcings and feedbacks involving NTCF s, (namely tropospheric aerosols, tropospheric O3 precursors, and CH4) and the chemically reactive WMGHGs (e.g., N2O, also CH4, and some halocarbons including impacts on stratospheric O3), 2) document and understand past and future changes in the chemical composition of the atmosphere, and 3) estimate the global-to-regional climate response from these changes.

To participate in the CMIP6/AerChemMIP project models will need to be run for the CMIP6 DECK experiments with the same setup, i.e. with the same levels of sophistication activated in the chemistry and aerosol schemes. In particular it will be essential to have PI control and Historical simulations with the full chemistry (where used) and aerosols. It is also realised that valuable contributions to answering the AerChemMIP scientific questions can be made by groups unable to participate in CMIP6. Participation from these groups is welcomed and encouraged in the wider AerChemMIP project but the data will not form part of the official CMIP6 submission.

Recently, WCRP endorsed “Biogeochemical forcings and feedbacks” as a Theme of Collaboration, similar in scope to the Grand Challenges. AerChemMIP is ideally suited to provide significant contributions to this theme through simulations in all Tiers. In particular, simulations Tier 1.3 look at the role of methane changes (which have an important biogeochemical component) on the historical climate. In addition, air quality is a theme central to AerChemMIP (see Tier 1.2 for example), and therefore will fulfill some of the goals of “Biogeochemical forcings and feedbacks” highlighted in http://www.wcrp-climate.org/images/documents/jsc/JSC36/WCRP-GC-biogeochemistry.pdf.

The AerChemMIP Tier 1 simulations focus primarily on understanding atmospheric composition changes (from NTCFs and other chemically-active anthropogenic gases) and their impact on climate. We have devised a series of experiments that contrast the forcing of various NTCFs with that of WMGHGs in historical and future climate change. In addition, the proposed chemistry-climate simulations will enable diagnosis of changes in regional air quality (AQ) through its coupling to large-scale changes in O3-CH4-PM2.5. We will work in collaboration with RFMIP and DAMIP to provide a comprehensive analysis of ERF and the regionally-resolved climate forcing signature from tropospheric NTCFs. For some of the specifically attributable climate forcings, in particular those at the 10s of mW m-2 level, the actual climate change will be difficult to detect in a transient simulation or even a time slice of several decades. AerChemMIP is a joint, consolidated effort for CMIP6 from two international communities -- Aerosol Comparisons between Observations and Models (AeroCom, http://aerocom.met.no/Welcome.html) and the IGAC/SPARC Chemistry-Climate Model Initiative (CCMI, http://www.met.reading.ac.uk/ccmi/). Experiments suggested for CCMI Phase 2 [Eyring et al., 2013b], which are traditionally run using chemistry-climate models (CCMs) with mostly prescribed sea surface temperatures and sea ice concentrations, complement this set of AerChemMIP/CMIP6 experiments. Further experiments in AeroCom phase III aim to understand sensitivity of aerosol forcing to aerosol formation and loss processes.

(We do not specifically consider the very long-lived F-gases (SF6, PFCs, and some HFCs) as their abundance is not affected by chemistry on a century time scale.)

Overview

Aerosols and ozone were identified in IPCC AR5 (Myhre et al., 2013) as the main sources of uncertainty in the radiative forcing since pre-industrial times. Uncertainties in projecting the chemically reactive WMGHGs as well as future air quality from global changes were also identified in AR5 [Kirtman et al., 2013]. In addition to changing anthropogenic emissions evaluated in AR5, natural aerosols originating from biogenic sources, dust or sea-salt are a primary contributor to the uncertainty in current forcing (Carslaw et al. 2013). Due to the nonlinear response of clouds to the background level of aerosols, the response of the climate system to human perturbations will depend critically on the natural aerosol background (Carlton et al., 2010).

Beyond aerosols, the biogeochemistry of ecosystems provides large sources of the WMGHGs CH4 and N2O, as well as O3 precursors (lightning and soil nitrogen oxides, volatile organic compounds, wildfire emissions). These sources are likely to be affected by climate change, leading to a variety of feedbacks that to date have only been quantified from a limited number of studies (and models) and thus demand for a coordinated set of simulations that allows for a consistent and clean comparison between models.

Anthropogenic emissions of NTCFs have been responsible for a climate forcing that is presently nearly equal in magnitude to CO2-forcing. These emissions have led to a variety of global climate impacts such as regional patterns of temperature and precipitation, with a magnitude similar to the global-mean equivalent ERF of WMGHG. In addition, NTCF ERF is inherently inhomogeneous, and there is some evidence that where NTCF on a regional scale is large, the climate response differs from the globally equivalent ERF – i.e., there is some regional response to regional ERF.

NTCF emissions are also responsible for driving regional and local air quality (AQ). This has led to the recognition that a combined strategy of mitigating climate change and air pollution together has clear economic benefits compared to separate mitigation (IPCC, 2014 – WG3 SPM). In our future world, most, if not all scenarios lead to changes in the emissions and meteorology that determine air quality and create pollution episodes. The knowledge base used to manage air pollution to date must be updated based on more comprehensive information that CMIP6 will provide on future air chemistry climatologies. The exposure risks of human health and assets (agriculture, built environment, ecosystems) will be driven by daily variations in surface ozone and particulate matter in addition to deposition of nitrate and sulfate and any land-use change interacting with atmospheric changes.

The forcing of climate by ozone changes results from tropospheric increases and lower stratospheric decreases, with interaction between those. They are the result of combined impacts from climate change and multiple emission changes. For example, one of the largest components of CH4 emissions’ ERF is that from the increase in tropospheric O3. In addition, stratospheric O3 losses due to ozone depleting substances (ODS) since the 1970s has led to significant cooling of the lower stratosphere, and through the Antarctic ozone hole is linked to changes in tropospheric circulation and rainfall patterns in the southern hemisphere, especially during summer (WMO, 2014). In the Southern Hemisphere, future summertime circulation changes are controlled by both the ozone recovery rate and the rate of GHG increases [Eyring et al., 2013a], indicating the need to account for ozone changes in future climate projections.

Since some models participating in CMIP6 do not have interactive chemistry schemes, AerChemMIP will also provide historical and future time-varying ozone, and stratospheric water vapour concentration fields for CMIP6. The ozone database will be an update of the database provided for CMIP5 by [Cionni et al., 2011]. These datasets will be generated from a mixture of CCMs and CTMs simulations which are not themselves part of CMIP6.

Because of the central role of aerosols in many of the AerChemMIP simulations and analysis, we suggest that climate models without prognostic aerosol schemes refrain from participating in AerChemMIP. It is important to note that the models participating in AerChemMIP must use for the corresponding, qualifying DECK and historical simulation emissions of aerosols and aerosol precursors provided by Smith et al. in the end of 2015. The CMIP6 aerosol forcing dataset shall not be used for DECK and historical simulations. However modeling groups are encouraged to participate with their AerChemMIP model version in the prescribed aerosol subset of RFMIP simulations, where the CMIP6 aerosol forcing dataset is required. In that case the aerosol radiative effects will have to be decoupled from the interactive aerosol scheme and prescribed optical properties from the RFMIP aerosol forcing dataset shall be used.

Overview of the Proposed Tier 1 Experiments

The AerChemMIP Tier 1 simulations focus on two science questions

1. How have NTCF and ODS emissions contributed to global ERF and affected regional climate over the historical period? 2. How will future policies (on climate/AQ/land use) affect the NTCFs and their climate impacts? 3. How have WMGHG concentrations forced climate (including through their chemical impacts) over the historical period?

In the following sections, we discuss each question separately and provide for each science question the description of the simulations necessary to answer the stated question. Note that we emphasize the use of the Effective Radiative Forcing (ERF) to measure climate forcing. We have provided at the end of this document a description of the methodology associated with this calculation.

1. How have NTCF and ODS emissions contributed to global ERF and affected regional climate over the historical period?

Anthropogenic non-CO2 emissions (e.g., NTCFs, GHGs like halocarbons and N2O,…) have led to a climate forcing that is commensurate to CO2-forcing on regional scales, especially over the last few decades.

By way of their associated large uncertainty in radiative forcing since pre-industrial times, ozone and aerosols in particular are a key factor behind the large uncertainty in constraining climate sensitivity over the record of observed data. These NTCFs have an inhomogeneous spatial distribution and the degree of regional temperature and precipitation responses to such heterogeneous forcing remains an open question within the scientific community. It is further unclear whether NTCFs, which are primarily located at Northern Hemisphere mid latitude land areas have led to a larger climate response there, relative to forcing from WMGHGs.

One unambiguous regional response to inhomogeneous climate forcing concerns the Southern hemisphere summertime surface circulation changes induced by the Antarctic ozone hole as an indirect response to ozone-depleting halocarbons. These changes have been argued to lead to changes in rainfall patterns, ocean circulation, and sea-ice cover. The relative role of these ozone-induced changes compared to other anthropogenic forcings and natural variability is not fully resolved by the scientific community (with some studies reaching contradictory conclusions). Hence there is a need for multi-model ensemble of simulations, especially with models resolving stratospheric chemistry that isolate the role of stratospheric ozone depletion.

Experiment 1.1: Transient historical coupled ocean climate impacts of NTCFs and of ozone depleting halocarbons (note: this builds on CMIP6-historical-simulation, which is used as the reference simulation, and requires AerChemMIP diagnostics therein)

1.1.1 Perturbation: Historical WMGHG (including halocarbon) concentrations, 1850 NTCF emissions. 165 years, 1-3 ensemble members 1.1.2 Perturbation: Historical WMGHG concentrations and NTCF emissions, 1950 halocarbons. 65 years (branched from CMIP6 historical in 1950), 1 up to the number of ensemble members performed for the CMIP6 historical

Experiment 1.2: Estimating ERFs through specified transient historical SST simulations (see note on ERFs below).

Note that these simulations uses transient SST from AOGCM simulations in Experiment 1.1 and not constant SST over the historical period. Perform 1850-2014 (1 ensemble member only) simulation with all forcings as in CMIP6 historical but with

1.2.1 1850 all NTCF emissions (including biomass burning). 165 years 1.2.2 1950 ODSs. 65 years (1950-2014)

Experiment 1.3. Time-slice simulations based on the 1850 control SSTs to compute the ERF for 1850 and 2014 for all NTCF (e.g. AR5 fig 8.15). This requires two simulations

1.3.1 Control: 1850 WMGHG concentrations and 1850 NTCF emissions. 30 years 1.3.2 Perturbation: 1850 WMGHG concentrations, 2014 NTCF emissions. 30 years

2. How will future policies (on climate/AQ/land use) affect the NTCFs and their climate impact? What are the patterns of associated climate forcing, and how do these patterns translate into temperature and precipitation changes?

For the upcoming decades policy makers will be making choices in 3 broadly defined areas 1) climate change policies (targeting mostly WMGHGs), 2) air quality policies (targeting mostly NTCF emissions including CH4 that are precursors of tropospheric aerosols and tropospheric ozone) and 3) land-use policies. AerChemMIP aims to identify the patterns of chemical change at the global and regional levels as well as the ERF associated with NTCF mitigation efforts (focusing on policy choices in areas 1 and 2 above), and their climate (surface temperature and precipitation) and environmental (health, ecosystem, visibility, …) impact between 2015 and 2055 (this is the time frame over which aerosol and precursor emissions are expected to be significant). The impact analysis will be performed by contrasting the following simulations: a) SSP3-7 from ScenarioMIP (note that additional diagnostics will have to be included for those simulations to be useful for AerChemMIP) since it has high aerosol emissions and b) a perturbation experiment where air quality policies (or maximum feasible reductions) are applied to the SSP3-7 NTCF emissions, and therefore lead to much reduced NTCF emissions. These perturbations will be designed in collaboration with ScenarioMIP to ensure that perturbations are consistent with the underlying story line of the scenario in consideration.

Experiment 2.1: Transient coupled ocean climate impacts

2.1.1 Reference: SSP3-7 (to be performed under ScenarioMIP) 2.1.2 Perturbation: SSP3-7 with reduced NTCF (aerosol and tropospheric ozone precursors, including methane) 41 years, 1-3 ensemble members (3 recommended)

Experiment 2.2: Estimating ERFs through fixed-SST simulations (SSTs from 2.1.1)

2.2.1 Control: as Experiment 2.1.1 using archived SSTs from 2.1.1 41 years, one ensemble 2.2.2 Perturbation: Only black carbon emissions as in Experiment 2.1.2 (this is to isolate the specific role of black carbon in near-term policy decisions) 41 years, one ensemble 2.2.3 Perturbation: All aerosol precursor emissions (but not NOx) as in 2.1.2, 41 years, one ensemble 2.2.4 Perturbation: All ozone precursors except methane kept the same as in 2.1.2, 41 years, one ensemble 2.2.5 Perturbation: Methane kept the same as in 2.1.2, 40 years, one ensemble

3. How have chemically reactive WMGHGs affected the forcing over the historical period? Under this question, we focus in Tier one on estimating the forcing from changes in methane on ozone (tropospheric and stratospheric), aerosol oxidation, and emissions of natural aerosols, including the climate impacts associated with those changes. Note that only ERF estimates are calculated, while the associated transient coupled simulations are in Tier 2.

Experiment 3.1: Estimating ERFs through specified SST simulations (SSTs taken from CMIP6 historical simulation)

Perform 1850-2015 (1 ensemble member only) simulation with all forcings (and including chemistry feedbacks on tropospheric and stratospheric ozone) as in transient historical but with

3.1.1 1850 CH4. 165 years

Total amount of Tier 1 simulation years Experiments 1.x.x: 540y - 940y (overlap w DAMIP ca ???y-???y) (overlap w RFMIP ca ??y) Experiments 2.x.x: 246y - 328y (excluding 2.1.1, run under ScenarioMIP) Experiments 3.x.x: 165y

Synergy with other MIPs – Model diagnostics Experiment 1.1.1/1.1.2 parallels similar forcing attribution simulations in DAMIP but include chemistry responses and diagnostics. Experiments 1.2.4/1.2.5/3.2.1/3.2.2: These parallel similar ERF calculations in RFMIP, but start from emission changes rather than concentration changes Experiments 2.1.1/2.1.2 extend the ScenarioMIP simulations to separate out the impact of AQ policies and NTCFs

Model diagnostics specific to AerChemMIP Tier 1 experiments need to be implemented also in the DECK and CMIP6-historical-simulation. The diagnostics will be contributed to the CMIP6 data request by AerChemMIP. If models have not all components to compute dynamic aerosols, tropospheric or stratospheric chemistry, models are requested to consider using the forcing fields of chemical compounds provided by AerChemMIP when performing AerChemMIP Tier 1 experiments.

Overview of the Proposed Tier 2 and 3 Experiments

AerChemMIP also includes additional experiments to document with an eventually more limited set of models complementing science questions, which are based on tier 1 experiments, and make efficient use of the general set-up of CMIP6. Tier 2 and 3 add detail to the Tier 1 experiments 1.1, 1.2, 1.3 and 3.1 by addressing extra combinations of NTCFs and reactive WMGHGs. They also add two additional science objectives.

4. Quantifying the climate feedbacks through changes in natural emissions (FDBCK) 5. Quantifying the uncertainties associated with anthropogenic emissions (ChemDOC)

Note that all except one Tier 2 and 3 simulations rely on AGCM simulations, i.e. sea-surface temperatures (and sea-ice distribution) are specified from an existing fully-coupled simulation in Tier 1. Experiment 1.1: Transient historical coupled ocean climate impacts of NTCFs and of ozone depleting halocarbons

1.1.3 Perturbation: Historical WMGHG (including halocarbon) concentrations, 1850 aerosol (but not NOx) emissions, 165 years, 1-3 ensemble members . Tier 2

Experiment 1.2: Estimating ERFs through specified transient historical SST

1.2.3 1850 all tropospheric ozone precursor emissions. 165 years. Tier 2 1.2.4 1850 all aerosol emissions (except NOx). 165 years. Tier 2

Experiment 1.3. Time-slice simulations based on the 1850 control SSTs to compute the ERF for 1850 and 2014 (e.g. AR5 fig 8.15).

1.3.3 Perturbation: 1850 WMGHG concentrations, 2014 aerosol (not NOx) emissions. 30 years. Tier 2 1.3.4 Perturbation: 1850 WMGHG concentrations, 2014 BC emissions. 30 years. Tier 2 1.3.5 Perturbation: 1850 WMGHG concentrations, 2014 tropospheric ozone precursor emissions. 30 years. Tier 2 1.3.6 Perturbation: 1850 WMGHG (except CH4) concentrations, 1850 NTCF emissions, 2014 CH4 concentrations. 30 years. Tier2 1.3.7 Perturbation: 1850 WMGHG (except N2O) concentrations, 1850 NTCF emissions, 2014 N2O concentrations. 30 years. Tier 2 1.3.8 Perturbation: 1850 WMGHG (except ODS) concentrations, 1850 NTCF emissions, 2014 ODS concentrations. 30 years. Tier 2 1.3.9 Perturbation: 1850 WMGHG concentrations, 2014 NOx emissions. 30 years. Tier 3 1.3.10 Perturbation: 1850 WMGHG concentrations, 2014 CO/VOC emissions. 30 years. Tier 3

Experiment 3.1: Estimating ERFs through specified SST simulations

3.1.2 1850 N2O. 165 years. Tier 2

4. Quantifying the climate feedbacks through changes in natural emissions Climate change will have affected (and will affect) the natural emissions of natural NTCFs and reactive WMGHGs. These natural emissions will have an ERF and so feedback onto climate change. Ideally experiments would analyse the effects of constant vs varying emissions, however this is too complex to implement. The experiments proposed here simply double the natural emissions. The ERFs of natural WMGHGs (e.g. wetland methane) are not calculated as these can be obtained from experiment 1.3. Experiment 4.1: Quantifying the ERFs of double natural emissions (based on 1850) control.

4.1.1 1850 doubled dust emissions. 30 years. Tier 2 4.1.2 1850 doubled sea salt emissions. 30 years. Tier 2 4.1.3 1850 doubled emissions of oceanic DMS. 30 years. Tier 3 4.1.4 1850 doubled fire emissions. 30 years. Tier 3 4.1.5 1850 doubled biogenic VOCs. 30 years. Tier 3 4.1.6 1850 doubled lightning NOx. 30 years. Tier 3 4.1.7. 1850 doubled wetland emissions of methane. 30 years. Tier 3

In addition, we will study the chemistry impact of land-use changes through biogenic emissions (LU-NTCF). This will be performed with AerChemMIP diagnostics, but using the same protocol as the land-use change experiment in LUMIP, i.e. based on SSP3-7 but with land use from SSP1-2.6.

Total amount of simulation years. Tier 2 = 900-1230, Tier 3 =140

Model Diagnostics and Performance Metrics for Model Evaluation

AerChemMIP will contribute to the CMIP6 data request by suggesting aerosol and chemistry related output that is required for model evaluation (including the characterization of air quality extremes) and for diagnosing radiative forcings from NTCFs. In addition, AerChemMIP will contribute to the development of the Earth System Model Evaluation Tools (ESMValTool, [Righi et al., 2014]), the documentation of aerosol parameters via the AeroCom tools and will include important chemistry-related diagnostics and performance metrics for CMIP6 model evaluation.

Design of Effective Radiative Forcing simulations.

The proposed simulations combine analysis of the effective radiative forcing (ERF) and the consequent climate impacts of NTCFs. The RF from WMGHGs will be provided by RFMIP. The ERFs are calculated by comparing the net TOA radiation fluxes between two runs with the same SSTs but with perturbed NTCF emissions (see below). Internal variability (mainly clouds) generates considerable noise therefore 30 years of simulation are needed to characterize the present day ERF from NTCFs. Alternatively, models that can nudge their simulated model winds (only, towards meteorological analyses or previously generated meteorological fields) should be able to identify a statistically-significant signal with as little as 3 years of simulation. In a similar way a pair of runs driven by evolving SSTs but with and without evolving NTCF emissions will provide the time evolution of the NTCF ERF. For the temperature and precipitation impacts, simulations with a coupled ocean are needed. Again, this requires a pair with and without evolving NTCF emissions in order to compute the impacts. The internal variability in the coupled ocean models is larger than with fixed SSTs, so at least 3 ensemble members will be needed.

The effective radiative forcing (ERF) was introduced in IPCC AR5 [Boucher et al., 2013; Myhre et al., 2013]. The definition is given as follows: ‘ERF is the change in net TOA downward radiative flux after allowing for atmospheric temperatures, water vapour and clouds to adjust, but with surface temperature or a portion of surface conditions unchanged’. This is different from the traditional radiative forcing (RF) concept where surface and tropospheric temperature and other variables such as water vapour and clouds must be kept fixed. Quantification of a climate driver by ERF and RF provides different results for some aerosol effects where the latter concept allows quantification of semi-direct effect and second indirect aerosol effect (ERF of aerosol-radiation interaction and aerosol-cloud interaction, respectively). For greenhouse gases RF and ERF are more similar in magnitude, but the latter has larger uncertainty.

Two ways to simulate ERF is currently used, namely; i) net TOA fluxes from fixed-sea surface temperature (SST) simulations and ii) regression of transient temperature response with the initial radiative perturbation [Gregory et al., 2004]. The two methods for simulating ERF are illustrated in [Boucher et al., 2013; Sherwood et al., 2014]. Both ERF methods have their advantages and disadvantages [Boucher et al., 2013; Myhre et al., 2013]. The regression method can be applied to many of the typical CMIP runs, but require long runs (at least 30 years) with a significant radiative perturbation. The fixed-SST method can by applied to relatively small radiative perturbations, but not all modelling groups have access to fixed-SST type simulations.

The fixed-SSTs approach can further be applied with additional radiation calls to diagnose the various aerosol effects [Ghan et al., 2012]. Separate diagnostics for shortwave and longwave changes are applied. To diagnose the indirect aerosol effect and semi-direct effect the scattering and absorption by aerosols are neglected by setting refractive indexes of anthropogenic aerosol to zero, see [Ghan et al., 2012] for further details.

References

Boucher, O., et al. (2013), Clouds and Aerosols, in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P. M. Midgley, pp. 571-657, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Cionni, I., V. Eyring, J. F. Lamarque, W. J. Randel, D. S. Stevenson, F. Wu, G. E. Bodeker, T. G. Shepherd, D. T. Shindell, and D. W. Waugh (2011), Ozone database in support of CMIP5 simulations: results and corresponding radiative forcing, Atmos. Chem. Phys. Discuss., 11(4), 10875-10933. Eyring, V., et al. (2013a), Long-term ozone changes and associated climate impacts in CMIP5 simulations, J Geophys Res-Atmos, 118(10), 5029-5060. Eyring, V., et al. (2013b), Overview of IGAC/SPARC Chemistry-Climate Model Initiative (CCMI) Community Simulations in Support of Upcoming Ozone and Climate Assessments, SPARC Newsletter, 40, 48-66. Ghan, S. J., X. Liu, R. C. Easter, R. Zaveri, P. J. Rasch, J.-H. Yoon, and B. Eaton (2012), Toward a minimal representation of aerosols in climate models: Comparative decomposition of aerosol direct, semi-direct and indirect radiative forcing, J. Climate, doi: 10.1175/JCLI-D-1111-00650.00651, in press. Gregory, J. M., W. J. Ingram, M. A. Palmer, G. S. Jones, P. A. Stott, R. B. Thorpe, J. A. Lowe, T. C. Johns, and K. D. Williams (2004), A new method for diagnosing radiative forcing and climate sensitivity, Geophysical Research Letters, 31(3), L03205. Kirtman, B., et al. (2013), Chapter 11. Near-term Climate Change: Projections and Predictability in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press Cambridge, United Kingdom. Myhre, G., et al. (2013), Anthropogenic and Natural Radiative Forcing, in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P. M. Midgley, pp. 659-740, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Righi, M., V. Eyring, K.-D. Gottschaldt, C. Klinger, F. Frank, P. Jöckel, and I. Cionni (2014), Quantitative evaluation of ozone and selected climate parameters in a set of EMAC simulations, Geosci. Model Dev. Discuss., 7, 6549-6627. Sherwood, S. C., S. Bony, and J. L. Dufresne (2014), Spread in model climate sensitivity traced to atmospheric convective mixing, Nature, 505(7481), 37-+.

Links

CMIP6