The GFDL's Aerosol Microphysics Model (GLAMM) Part 1: Model Description and Aerosol Evaluation With Observational Constraints
4 affiliations
- 1Atmospheric and Oceanic Sciences Program Princeton University Princeton NJ USA
- 2NOAA/OAR Geophysical Fluid Dynamics Laboratory Princeton NJ USA
- 3NASA Goddard Institute for Space Studies New York NY USA
- 4Department of Atmospheric Sciences Texas A&M University College Station TX USA
Abstract
This paper describes the development and application of GLAMM (GFDL's Aerosol Microphysics Model) within the GFDL atmospheric model AM4.0 framework. Unlike the bulk aerosol schemes previously used in AM4.0, GLAMM employs a modal representation that explicitly tracks the evolution of aerosol mass and number concentrations and accounts for mixing state (internal and external) across multiple modes. The model includes prognostic treatments of key microphysical processes, including nucleation, coagulation, condensational growth, hygroscopic growth, dry and wet removal, and activation to cloud condensation nuclei. It also supports flexible configurations in which the number and combination of aerosol modes can be adjusted to trade off configuration complexity and computational cost. In this study, we evaluate the model's performance in a full 12‐mode configuration using a decadal AMIP simulation (2001–2010). We compare results against a comprehensive suite of observational constraints, including surface networks (IMPROVE, University of Miami, GAW), the global AERO‐MAP surface composition compilation, AERONET inversions, and in situ aircraft measurements from the ATom mission. GLAMM performs comparably to the bulk aerosol representation in AM4.0 in simulating aerosol mass concentrations. When evaluated against global observations, it reproduces both aerosol mass and number distributions with good overall agreement: simulated surface mass and number concentrations are mostly within a factor of five of observations. These results indicate that GLAMM provides a physically based and flexible framework for improved aerosol representation and aerosol–cloud interactions within the GFDL modeling system.
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BibTeX
@article{li2026gfdls,
title = {{The GFDL's Aerosol Microphysics Model (GLAMM) Part 1: Model Description and Aerosol Evaluation With Observational Constraints}},
author = {Xiaohan Li and Fabien Paulot and Uriel Ramirez and Susanne E. Bauer and Xiaohong Liu and Paul Ginoux},
journal = {Journal of Advances in Modeling Earth Systems},
year = {2026},
month = oct,
doi = {10.1029/2026ms005864},
url = {https://doi.org/10.1029/2026ms005864},
note = {CC BY},
}
RIS
TY - JOUR
TI - The GFDL's Aerosol Microphysics Model (GLAMM) Part 1: Model Description and Aerosol Evaluation With Observational Constraints
AU - Xiaohan Li
AU - Fabien Paulot
AU - Uriel Ramirez
AU - Susanne E. Bauer
AU - Xiaohong Liu
AU - Paul Ginoux
PY - 2026
DA - 2026/10/28
JO - Journal of Advances in Modeling Earth Systems
DO - 10.1029/2026ms005864
UR - https://doi.org/10.1029/2026ms005864
AB - This paper describes the development and application of GLAMM (GFDL's Aerosol Microphysics Model) within the GFDL atmospheric model AM4.0 framework. Unlike the bulk aerosol schemes previously used in AM4.0, GLAMM employs a modal representation that explicitly tracks the evolution of aerosol mass and number concentrations and accounts for mixing state (internal and external) across multiple modes. The model includes prognostic treatments of key microphysical processes, including nucleation, coagulation, condensational growth, hygroscopic growth, dry and wet removal, and activation to cloud condensation nuclei. It also supports flexible configurations in which the number and combination of aerosol modes can be adjusted to trade off configuration complexity and computational cost. In this study, we evaluate the model's performance in a full 12‐mode configuration using a decadal AMIP simulation (2001–2010). We compare results against a comprehensive suite of observational constraints, including surface networks (IMPROVE, University of Miami, GAW), the global AERO‐MAP surface composition compilation, AERONET inversions, and in situ aircraft measurements from the ATom mission. GLAMM performs comparably to the bulk aerosol representation in AM4.0 in simulating aerosol mass concentrations. When evaluated against global observations, it reproduces both aerosol mass and number distributions with good overall agreement: simulated surface mass and number concentrations are mostly within a factor of five of observations. These results indicate that GLAMM provides a physically based and flexible framework for improved aerosol representation and aerosol–cloud interactions within the GFDL modeling system.
SN - 1942-2466
ER -