Improving BC Mixing State and CCN Activity Representation With Machine Learning in the Community Atmosphere Model Version 6 (CAM6)

Wenxiang Shen, Minghuai Wang, Nicole Riemer, Zhonghua Zheng, Yawen Liu, Xinyi Dong

Research output: Contribution to journalArticlepeer-review


Representing mixing state of black carbon (BC) is challenging for global climate models (GCMs). The Community Atmosphere Model version 6 (CAM6) with the four-mode version of the Modal Aerosol Module (MAM4) represents aerosols as fully internal mixtures with uniform composition within each aerosol mode, resulting in high degree of internal mixing of BC with non-BC species and large mass ratio of coating to BC (RBC, the mass ratio of non-BC species to BC in BC-containing particles). To improve BC mixing state representation, we coupled a machine learning (ML) model of BC mixing state index trained on particle-resolved simulations to the CAM6 with MAM4 (MAM4-ML). In MAM4-ML, we use RBC to partition accumulation mode particles into two new modes, BC-free particles and BC-containing particles. We adjust RBC to make the modeled BC mixing state index (χmode) match the one predicted by the ML model (χML). On a global average, the mass fraction of BC-containing particles in accumulation mode decreases from 100% (MAM4-default) to 48% (MAM4-ML). The globally averaged χmode decreases from 78% (MAM4-default) to 63% (MAM4-ML, 19% reduction) and agrees well with χML (66%). The RBC decreases by 52% for accumulation mode and better agrees with observations. The hygroscopicity drops by 9% for BC-containing particles in accumulation mode, leading to a 20% reduction in the BC activation fraction. The surface BC concentration increases most (6.9%) in the Arctic, and the BC burden increases by 4%, globally. Our study highlights the application of the ML model for improving key aerosol processes in GCMs.

Original languageEnglish (US)
Article numbere2023MS003889
JournalJournal of Advances in Modeling Earth Systems
Issue number1
StatePublished - Jan 2024


  • aerosol CCN activation
  • black carbon aerosol
  • climate model improvement
  • machine learning
  • mixing state representation

ASJC Scopus subject areas

  • Global and Planetary Change
  • Environmental Chemistry
  • General Earth and Planetary Sciences


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