Description and evaluation of a new four-mode version of the Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model

Liu, X.; Ma, P. -L.; Wang, H.; Tilmes, S.; Singh, B.; Easter, R. C.; Ghan, S. J.; Rasch, P. J.

doi:10.5194/gmd-9-505-2016

Description and evaluation of a new four-mode version of the Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model

Journal Article · Mon Feb 08 04:00:00 EST 2016 · Geoscientific Model Development (Online)

DOI:https://doi.org/10.5194/gmd-9-505-2016· OSTI ID:1243191

Liu, X. ^[1]; Ma, P. -L. ^[2]; Wang, H. ^[2]; Tilmes, S. ^[3]; Singh, B. ^[2]; Easter, R. C. ^[2]; Ghan, S. J. ^[2]; Rasch, P. J. ^[2]

Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Univ. of Wyoming, Laramie, WY (United States)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
National Center for Atmospheric Research, Boulder, CO (United States)

Atmospheric carbonaceous aerosols play an important role in the climate system by influencing the Earth's radiation budgets and modifying the cloud properties. Despite the importance, their representations in large-scale atmospheric models are still crude, which can influence model simulated burden, lifetime, physical, chemical and optical properties, and the climate forcing of carbonaceous aerosols. In this study, we improve the current three-mode version of the Modal Aerosol Module (MAM3) in the Community Atmosphere Model version 5 (CAM5) by introducing an additional primary carbon mode to explicitly account for the microphysical ageing of primary carbonaceous aerosols in the atmosphere. Compared to MAM3, the four-mode version of MAM (MAM4) significantly increases the column burdens of primary particulate organic matter (POM) and black carbon (BC) by up to 40 % in many remote regions, where in-cloud scavenging plays an important role in determining the aerosol concentrations. Differences in the column burdens for other types of aerosol (e.g., sulfate, secondary organic aerosols, mineral dust, sea salt) are less than 1 %. Evaluating the MAM4 simulation against in situ surface and aircraft observations, we find that MAM4 significantly improves the simulation of seasonal variation of near-surface BC concentrations in the polar regions, by increasing the BC concentrations in all seasons and particularly in cold seasons. However, it exacerbates the overestimation of modeled BC concentrations in the upper troposphere in the Pacific regions. As a result, the comparisons suggest that, to address the remaining model POM and BC biases, future improvements are required related to (1) in-cloud scavenging and vertical transport in convective clouds and (2) emissions of anthropogenic and biomass burning aerosols.

View Accepted Manuscript (DOE)

Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 1243191

Report Number(s):: PNNL-SA--110649; KP1703020

Journal Information:: Geoscientific Model Development (Online), Journal Name: Geoscientific Model Development (Online) Journal Issue: 2 Vol. 9; ISSN 1991-9603

Publisher:: European Geosciences UnionCopyright Statement

Country of Publication:: United States

Language:: English

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The Summertime Precipitation Bias in E3SM Atmosphere Model Version 1 over the Central United States Zheng, X.; Golaz, J. ‐C.; Xie, S. Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 16 https://doi.org/10.1029/2019jd030662	journal	August 2019
Modeling Dust in East Asia by CESM and Sources of Biases Wu, Mingxuan; Liu, Xiaohong; Yang, Kang Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 14 https://doi.org/10.1029/2019jd030799	journal	July 2019
The Whole Atmosphere Community Climate Model Version 6 (WACCM6) Gettelman, A.; Mills, M. J.; Kinnison, D. E. Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 23 https://doi.org/10.1029/2019jd030943	journal	December 2019
Understanding Monsoonal Water Cycle Changes in a Warmer Climate in E3SMv1 Using a Normalized Gross Moist Stability Framework Harrop, Bryce E.; Ma, Po‐Lun; Rasch, Philip J. Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 20 https://doi.org/10.1029/2019jd031443	journal	October 2019
An Overview of the Atmospheric Component of the Energy Exascale Earth System Model Rasch, P. J.; Xie, S.; Ma, P. ‐L. Journal of Advances in Modeling Earth Systems, Vol. 11, Issue 8 https://doi.org/10.1029/2019ms001629	journal	August 2019
Improved Simulation of the QBO in E3SMv1 Richter, Jadwiga H.; Chen, Chih‐Chieh; Tang, Qi Journal of Advances in Modeling Earth Systems, Vol. 11, Issue 11 https://doi.org/10.1029/2019ms001763	journal	November 2019
Climate Forcing and Trends of Organic Aerosols in the Community Earth System Model (CESM2) Tilmes, S.; Hodzic, A.; Emmons, L. K. Journal of Advances in Modeling Earth Systems, Vol. 11, Issue 12 https://doi.org/10.1029/2019ms001827	journal	December 2019
Impact of Nudging Strategy on the Climate Representativeness and Hindcast Skill of Constrained EAMv1 Simulations Sun, Jian; Zhang, Kai; Wan, Hui Journal of Advances in Modeling Earth Systems, Vol. 11, Issue 12 https://doi.org/10.1029/2019ms001831	journal	December 2019
Aerosols in the E3SM Version 1: New Developments and Their Impacts on Radiative Forcing Wang, Hailong; Easter, Richard C.; Zhang, Rudong Journal of Advances in Modeling Earth Systems, Vol. 12, Issue 1 https://doi.org/10.1029/2019ms001851	journal	January 2020
The DOE E3SM Coupled Model Version 1: Description and Results at High Resolution Caldwell, Peter M.; Mametjanov, Azamat; Tang, Qi Journal of Advances in Modeling Earth Systems, Vol. 11, Issue 12 https://doi.org/10.1029/2019ms001870	journal	December 2019
The Community Earth System Model Version 2 (CESM2) Danabasoglu, G.; Lamarque, J. ‐F.; Bacmeister, J. Journal of Advances in Modeling Earth Systems, Vol. 12, Issue 2 https://doi.org/10.1029/2019ms001916	journal	February 2020
Unraveling driving forces explaining significant reduction in satellite-inferred Arctic surface albedo since the 1980s Zhang, Rudong; Wang, Hailong; Fu, Qiang Proceedings of the National Academy of Sciences, Vol. 116, Issue 48 https://doi.org/10.1073/pnas.1915258116	journal	November 2019
A Review of the Representation of Aerosol Mixing State in Atmospheric Models Stevens, Robin; Dastoor, Ashu Atmosphere, Vol. 10, Issue 4 https://doi.org/10.3390/atmos10040168	journal	March 2019
Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation Fanourgakis, George S.; Kanakidou, Maria; Nenes, Athanasios ETH Zurich https://doi.org/10.3929/ethz-b-000353115	text	January 2019
Effective radiative forcing in the aerosol-climate model CAM5.3-MARC-ARG Grandey, Benjamin S.; Rothenberg, Daniel; Avramov, Alexander arXiv https://doi.org/10.48550/arxiv.1804.06158	text	January 2018
Impacts of global open-fire aerosols on direct radiative, cloud and surface-albedo effects simulated with CAM5 Jiang, Yiquan; Lu, Zheng; Liu, Xiaohong Atmospheric Chemistry and Physics, Vol. 16, Issue 23 https://doi.org/10.5194/acp-16-14805-2016	journal	January 2016
Aerosols at the poles: an AeroCom Phase II multi-model evaluation Sand, Maria; Samset, Bjørn H.; Balkanski, Yves Atmospheric Chemistry and Physics, Vol. 17, Issue 19 https://doi.org/10.5194/acp-17-12197-2017	journal	January 2017
Source attribution of black carbon and its direct radiative forcing in China Yang, Yang; Wang, Hailong; Smith, Steven J. Atmospheric Chemistry and Physics, Vol. 17, Issue 6 https://doi.org/10.5194/acp-17-4319-2017	journal	January 2017
Metrics to quantify the importance of mixing state for CCN activity Ching, Joseph; Fast, Jerome; West, Matthew Atmospheric Chemistry and Physics, Vol. 17, Issue 12 https://doi.org/10.5194/acp-17-7445-2017	journal	January 2017
Effective radiative forcing in the aerosol–climate model CAM5.3-MARC-ARG Grandey, Benjamin S.; Rothenberg, Daniel; Avramov, Alexander Atmospheric Chemistry and Physics, Vol. 18, Issue 21 https://doi.org/10.5194/acp-18-15783-2018	journal	January 2018
Radiative effect and climate impacts of brown carbon with the Community Atmosphere Model (CAM5) Brown, Hunter; Liu, Xiaohong; Feng, Yan Atmospheric Chemistry and Physics, Vol. 18, Issue 24 https://doi.org/10.5194/acp-18-17745-2018	journal	January 2018
A simple model for the time evolution of the condensation sink in the atmosphere for intermediate Knudsen numbers Ezhova, Ekaterina; Kerminen, Veli-Matti; Lehtinen, Kari E. J. Atmospheric Chemistry and Physics, Vol. 18, Issue 4 https://doi.org/10.5194/acp-18-2431-2018	journal	January 2018
Seasonal variation and light absorption property of carbonaceous aerosol in a typical glacier region of the southeastern Tibetan Plateau Niu, Hewen; Kang, Shichang; Wang, Hailong Atmospheric Chemistry and Physics, Vol. 18, Issue 9 https://doi.org/10.5194/acp-18-6441-2018	journal	January 2018
Strong impacts on aerosol indirect effects from historical oxidant changes Karset, Inger Helene Hafsahl; Berntsen, Terje Koren; Storelvmo, Trude Atmospheric Chemistry and Physics, Vol. 18, Issue 10 https://doi.org/10.5194/acp-18-7669-2018	journal	January 2018
Significant climate impacts of aerosol changes driven by growth in energy use and advances in emission control technology Zhao, Alcide; Bollasina, Massimo A.; Crippa, Monica Atmospheric Chemistry and Physics, Vol. 19, Issue 23 https://doi.org/10.5194/acp-19-14517-2019	journal	January 2019
Variability, timescales, and nonlinearity in climate responses to black carbon emissions Yang, Yang; Smith, Steven J.; Wang, Hailong Atmospheric Chemistry and Physics, Vol. 19, Issue 4 https://doi.org/10.5194/acp-19-2405-2019	journal	January 2019
Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation Fanourgakis, George S.; Kanakidou, Maria; Nenes, Athanasios Atmospheric Chemistry and Physics, Vol. 19, Issue 13 https://doi.org/10.5194/acp-19-8591-2019	journal	January 2019
The acidity of atmospheric particles and clouds Pye, Havala O. T.; Nenes, Athanasios; Alexander, Becky Atmospheric Chemistry and Physics, Vol. 20, Issue 8 https://doi.org/10.5194/acp-20-4809-2020	journal	January 2020
Aerosols at the Poles: An AeroCom Phase II multi-model evaluation Sand, Maria; Samset, Bjørn H.; Balkanski, Yves Atmospheric Chemistry and Physics Discussions https://doi.org/10.5194/acp-2016-1120	posted_content	February 2017
A simple model for the time evolution of the condensation sink in the atmosphere for intermediate Knudsen numbers Ezhova, Ekaterina; Matti-Kerminen, Veli; Lehtinen, Kari E. J. Atmospheric Chemistry and Physics https://doi.org/10.5194/acp-2017-986	posted_content	November 2017
Impact of numerical choices on water conservation in the E3SM Atmosphere Model version 1 (EAMv1) Zhang, Kai; Rasch, Philip J.; Taylor, Mark A. Geoscientific Model Development, Vol. 11, Issue 5 https://doi.org/10.5194/gmd-11-1971-2018	journal	January 2018
The path to CAM6: coupled simulations with CAM5.4 and CAM5.5 Bogenschutz, Peter A.; Gettelman, Andrew; Hannay, Cecile Geoscientific Model Development, Vol. 11, Issue 1 https://doi.org/10.5194/gmd-11-235-2018	journal	January 2018
A production-tagged aerosol module for Earth system models, OsloAero5.3 – extensions and updates for CAM5.3-Oslo Kirkevåg, Alf; Grini, Alf; Olivié, Dirk Geoscientific Model Development, Vol. 11, Issue 10 https://doi.org/10.5194/gmd-11-3945-2018	journal	January 2018
Regionally refined test bed in E3SM atmosphere model version 1 (EAMv1) and applications for high-resolution modeling Tang, Qi; Klein, Stephen A.; Xie, Shaocheng Geoscientific Model Development, Vol. 12, Issue 7 https://doi.org/10.5194/gmd-12-2679-2019	journal	January 2019
CAM6 simulation of mean and extreme precipitation over Asia: sensitivity to upgraded physical parameterizations and higher horizontal resolution Lin, Lei; Gettelman, Andrew; Xu, Yangyang Geoscientific Model Development, Vol. 12, Issue 8 https://doi.org/10.5194/gmd-12-3773-2019	journal	January 2019
Improved methodologies for Earth system modelling of atmospheric soluble iron and observation comparisons using the Mechanism of Intermediate complexity for Modelling Iron (MIMI v1.0) Hamilton, Douglas S.; Scanza, Rachel A.; Feng, Yan Geoscientific Model Development, Vol. 12, Issue 9 https://doi.org/10.5194/gmd-12-3835-2019	journal	January 2019

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