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Effective Radiative Forcing in the Aerosol–Climate Model CAM5.3-MARC-ARG Reprint 2018-15 Effective radiative forcing in the aerosol–climate model CAM5.3-MARC-ARG B.S. Grandey, D. Rothenberg, A. Avramov, Q. Jin, H. Lee, X. Liu, Z. Lu, S. Albani and C. Wang Reprinted with permission from Atmospheric Chemistry & Physics, 18: 15783–15810. © 2018 the authors The MIT Joint Program on the Science and Policy of Global Woods Hole and short- and long-term visitors—provide the united Change combines cutting-edge scientific research with independent vision needed to solve global challenges. policy analysis to provide a solid foundation for the public and At the heart of much of the program’s work lies MIT’s Integrated private decisions needed to mitigate and adapt to unavoidable global Global System Model. Through this integrated model, the program environmental changes. Being data-driven, the Joint Program uses seeks to discover new interactions among natural and human climate extensive Earth system and economic data and models to produce system components; objectively assess uncertainty in economic and quantitative analysis and predictions of the risks of climate change climate projections; critically and quantitatively analyze environmental and the challenges of limiting human influence on the environment— management and policy proposals; understand complex connections essential knowledge for the international dialogue toward a global among the many forces that will shape our future; and improve response to climate change. methods to model, monitor and verify greenhouse gas emissions and To this end, the Joint Program brings together an interdisciplinary climatic impacts. group from two established MIT research centers: the Center for This reprint is intended to communicate research results and improve Global Change Science (CGCS) and the Center for Energy and public understanding of global environment and energy challenges, Environmental Policy Research (CEEPR). These two centers—along thereby contributing to informed debate about climate change and the with collaborators from the Marine Biology Laboratory (MBL) at economic and social implications of policy alternatives. —Ronald G. Prinn and John M. Reilly, Joint Program Co-Directors MIT Joint Program on the Science and Policy Massachusetts Institute of Technology T (617) 253-7492 F (617) 253-9845 of Global Change 77 Massachusetts Ave., E19-411 [email protected] Cambridge MA 02139-4307 (USA) http://globalchange.mit.edu Atmos. Chem. Phys., 18, 15783–15810, 2018 https://doi.org/10.5194/acp-18-15783-2018 © Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License. Effective radiative forcing in the aerosol–climate model CAM5.3-MARC-ARG Benjamin S. Grandey1, Daniel Rothenberg2, Alexander Avramov2,3, Qinjian Jin2, Hsiang-He Lee1, Xiaohong Liu4, Zheng Lu4, Samuel Albani5,6, and Chien Wang2,1 1Center for Environmental Sensing and Modeling, Singapore-MIT Alliance for Research and Technology, Singapore, Singapore 2Center for Global Change Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA 3Department of Environmental Sciences, Emory University, Atlanta, Georgia, USA 4Department of Atmospheric Science, University of Wyoming, Laramie, Wyoming, USA 5Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, New York, USA 6Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Gif-sur-Yvette, France Correspondence: Benjamin S. Grandey ([email protected]) Received: 1 February 2018 – Discussion started: 2 May 2018 Revised: 19 October 2018 – Accepted: 21 October 2018 – Published: 2 November 2018 Abstract. We quantify the effective radiative forcing (ERF) 0:04 W m−2 produced by MAM3 and −1:53 ± 0:04 W m−2 of anthropogenic aerosols modelled by the aerosol–climate produced by MAM7. The regional distribution of ERF also model CAM5.3-MARC-ARG. CAM5.3-MARC-ARG is a differs between MARC and MAM3, largely due to differ- new configuration of the Community Atmosphere Model ences in the regional distribution of the shortwave cloud ra- version 5.3 (CAM5.3) in which the default aerosol mod- diative effect. We conclude that the specific representation of ule has been replaced by the two-Moment, Multi-Modal, aerosols in global climate models, including aerosol mixing Mixing-state-resolving Aerosol model for Research of state, has important implications for climate modelling. Climate (MARC). CAM5.3-MARC-ARG uses the ARG aerosol-activation scheme, consistent with the default con- figuration of CAM5.3. We compute differences between sim- ulations using year-1850 aerosol emissions and simulations 1 Introduction using year-2000 aerosol emissions in order to assess the ra- diative effects of anthropogenic aerosols. We compare the Aerosol particles influence the earth’s climate system by aerosol lifetimes, aerosol column burdens, cloud properties, perturbing its radiation budget. There are three primary and radiative effects produced by CAM5.3-MARC-ARG mechanisms by which aerosols interact with radiation. First, with those produced by the default configuration of CAM5.3, aerosols interact directly with radiation by scattering and ab- which uses the modal aerosol module with three log-normal sorbing solar and thermal infrared radiation (Haywood and modes (MAM3), and a configuration using the modal aerosol Boucher, 2000). Second, aerosols interact indirectly with ra- module with seven log-normal modes (MAM7). Compared diation by perturbing clouds, acting as the cloud condensa- with MAM3 and MAM7, we find that MARC produces tion nuclei on which cloud droplets form and the ice nuclei stronger cooling via the direct radiative effect, the short- that facilitate freezing of cloud droplets (Fan et al., 2016; wave cloud radiative effect, and the surface albedo radia- Rosenfeld et al., 2014); for example, an aerosol-induced in- tive effect; similarly, MARC produces stronger warming crease in cloud cover would lead to increased scattering via the longwave cloud radiative effect. Overall, MARC of “shortwave” solar radiation and increased absorption of produces a global mean net ERF of − 1:79 ± 0:03 W m−2, “longwave” thermal infrared radiation. Third, aerosols can which is stronger than the global mean net ERF of −1:57 ± influence the albedo of the earth’s surface; for example, the deposition of absorbing aerosol on snow reduces the albedo Published by Copernicus Publications on behalf of the European Geosciences Union. 15784 B. S. Grandey et al.: Effective radiative forcing in the model CAM5.3-MARC-ARG of the snow, causing more solar radiation to be absorbed at the aerosol radiative effects produced by a new configu- the earth’s surface (Jiao et al., 2014). ration of the Community Atmosphere Model version 5.3 The “effective radiative forcing” (ERF) of anthropogenic (CAM5.3). In this new configuration – CAM5.3-MARC- aerosols, defined as the top-of-atmosphere radiative effect ARG – the default modal aerosol module has been replaced caused by anthropogenic emissions of aerosols and aerosol with the two-Moment, Multi-Modal, Mixing-state-resolving precursors, is often used to quantify the radiative effects of Aerosol model for Research of Climate (MARC). We com- aerosols (Boucher et al., 2013). In contrast to instantaneous pare the aerosol fields and aerosol radiative effects produced radiative forcing, ERF allows rapid adjustments – including by CAM5.3-MARC-ARG with those produced by the default changes to clouds – to occur (Sherwood et al., 2015). The an- modal aerosol module in CAM5.3. thropogenic aerosol ERF is approximately equivalent to “the radiative flux perturbation associated with a change from preindustrial to present-day [aerosol emissions], calculated 2 Methodology in a global climate model using fixed sea surface tempera- ture” (Haywood et al., 2009). This approach “allows clouds 2.1 Modal aerosol modules (MAM3 and MAM7) to respond to the aerosol while [sea] surface temperature is prescribed” (Ghan, 2013). The Community Earth System Model version 1.2.2 The primary tools available for investigating the anthro- (CESM 1.2.2) contains the Community Atmosphere Model pogenic aerosol ERF are state-of-the-art global climate mod- version 5.3 (CAM5.3). Within CAM5.3, the default aerosol els. However, there is widespread disagreement among these module is a modal aerosol module that parameterises the models, especially regarding the magnitude of anthropogenic aerosol size distribution using three log-normal modes aerosol ERF (Quaas et al., 2009; Shindell et al., 2013). (MAM3), each assuming a total internal mixture of a set of The magnitude of the ERF of anthropogenic aerosols is fixed chemical species (Liu et al., 2012). Optionally, a more highly uncertain; estimates of the global mean anthropogenic detailed modal aerosol module with seven log-normal modes aerosol ERF range from −1:9 to −0:1 W m−2 (Boucher et (MAM7; Liu et al., 2012) can be used instead of MAM3. al., 2013). Much of this uncertainty can be attributed to More recently, a version containing four modes (MAM4; Liu uncertainty in pre-industrial aerosol emissions (Carslaw et et al., 2016) has also been coupled to CAM5.3, but we do not al., 2013). Model parameterisations constitute another large consider MAM4 in this study. source of uncertainty. Of particular importance are model pa- The seven modes included in MAM7 are Aitken, accumu- rameterisations relating to aerosol–cloud interactions, such lation, primary carbon, fine soil dust, fine sea salt, coarse soil as the aerosol-activation scheme (Rothenberg et al., 2018), dust, and coarse sea salt.
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