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 NTCFs, (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.

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. -

Experiments Tier 1

The AerChemMIP Tier 1 simulations focus on three 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 WMGHGs 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).

Perform 1850-2014 (1 ensemble member only) simulation with all forcings as in CMIP6 historical but with

1.2.1 1850 tropospheric ozone precursor emissions (including biomass burning) 165 years 1.2.2 1850 all NTCF emissions (including biomass burning). 165 years 1.2.3 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 and natural aerosols (e.g. AR5 fig 8.15). This requires four simulations

1.3.1 Control: 1850 WMGHG concentrations and 1850 NTCF emissions. 20 years 1.3.2 Perturbation: 1850 WMGHG concentrations, 2014 NTCF emissions. 20 years 1.3.3. Perturbation: Doubled dust emissions. 20 years 1.3.4. Perturbation: Doubled sea salt emissions. 20 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) a reference experiment with high aerosol emissions (such as SSP3-7, but the final decision will be made with ScenarioMIP) imulations (with sufficient diagnostics) and b) perturbation experiments replacing NTCF emissions in reference experiment with 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 with reduced NTCF (aerosol and tropospheric ozone precursors, including methane) 40 years, 1-3 ensemble members

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 40 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) 40 years, one ensemble 2.2.3 Perturbation: All aerosol precursor emissions (but not NOx) as in 2.1.2, 40 years, one ensemble 2.2.4 Perturbation: All ozone precursors except methane kept the same as in 2.1.2, 40 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 on estimating the forcing from changes in methane and nitrous oxide 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 3.1.2 1850 N2O. 165 years

All Experiments

All Experiments in tier 1,2,3 are put in standard CMIP6 format as excel file.

Download excel file

Model Diagnostics Protocol

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.

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 20 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 20 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.

Scientific Steering Group

➢ Co-chairs of MIP

William Collins (UK) (W.Collins@reading.ac.uk) Jean-François Lamarque (US) (lamar@ucar.edu) Michael Schulz (Norway) (michael.schulz@met.no)

➢ Members of the Scientific Steering Committee

Olivier Boucher (France) (olivier.boucher@lmd.jussieu.fr) Veronika Eyring (Germany) (veronika.eyring@dlr.de) Arlene Fiore (US) (amfiore@ldeo.columbia.edu) Michaela Hegglin (UK) (m.i.hegglin@reading.ac.uk) Gunnar Myhre (Norway) (gunnar.myhre@cicero.oslo.no) Michael Prather (US) (mprather@uci.edu) Drew Shindell (US) (drew.shindell@duke.edu) Steve Smith (US) (ssmith@pnnl.gov) Darryn Waugh (US) (waugh@jhu.edu)

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