Submitted as: model description paper 17 Nov 2021

Submitted as: model description paper | 17 Nov 2021

Review status: this preprint is currently under review for the journal GMD.

Chemistry Across Multiple Phases (CAMP) version 1.0: An integrated multi-phase chemistry model

Matthew L. Dawson1,4, Christian Guzman1, Jeffrey H. Curtis2,3, Mario Acosta1, Shupeng Zhu5, Donald Dabdub6, Andrew Conley4, Matthew West3, Nicole Riemer2, and Oriol Jorba1 Matthew L. Dawson et al.
  • 1Barcelona Supercomputing Center, Barcelona, Spain
  • 2Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
  • 3Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
  • 4Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, Colorado, USA
  • 5Advanced Power and Energy Program, University of California, Irvine, California, USA
  • 6Department of Mechanical and Aerospace Engineering, University of California, Irvine, California, USA

Abstract. A flexible treatment for gas- and aerosol-phase chemical processes has been developed for models of diverse scale, from box models up to global models. At the core of this novel framework is an "abstracted aerosol representation" that allows a given chemical mechanism to be solved in atmospheric models with different aerosol representations (e.g., sectional, modal, or particle-resolved). This is accomplished by treating aerosols as a collection of condensed phases that are implemented according to the aerosol representation of the host model. The framework also allows multiple chemical processes (e.g., gas- and aerosol-phase chemical reactions, emissions, deposition, photolysis, and mass-transfer) to be solved simultaneously as a single system. The flexibility of the model is achieved by (1) using an object-oriented design that facilitates extensibility to new types of chemical processes and to new ways of representing aerosol systems; (2) runtime model configuration using JSON input files that permits making changes to any part of the chemical mechanism without recompiling the model; this widely used, human-readable format allows entire gas- and aerosol-phase chemical mechanisms to be described with as much complexity as necessary; and (3) automated comprehensive testing that ensures stability of the code as new functionality is introduced. Together, these design choices enable users to build a customized multiphase mechanism, without having to handle pre-processors, solvers or compilers. Removing these hurdles makes this type of modeling accessible to a much wider community, including modelers, experimentalists, and educators. This new treatment compiles as a stand-alone library and has been deployed in the particle-resolved PartMC model and in the MONARCH chemical weather prediction system for use at regional and global scales. Results from the initial deployment to box models of different complexity and MONARCH will be discussed, along with future extension to more complex gas--aerosol systems, and the integration of GPU-based solvers.

Matthew L. Dawson et al.

Status: open (until 12 Jan 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Matthew L. Dawson et al.

Data sets

Box model and MONARCH outputs Matthew L Dawson, Christian Guzman, Jeffrey H Curtis, Mario Acosta, Shupeng Zhu, Donald Dabdub, Andrew Conley, Matthew West, Nicole Riemer, Oriol Jorba

Model code and software

MONARCH Klose, Martina; Jorba, Oriol; Gonçalves Ageitos, María; Escribano, Jerónimo; Dawson, Matthew L.; Obiso, Vincenzo; Di Tomaso, Enza; Basart, Sara; Montané Pinto, Gilbert; Macchia, Francesca; Pérez García-Pando, Carlos

PartMC v2.6.0 Matthew West; Nicole Riemer; Jeffrey Curtis; Matthew Michelotti; Rahul Zaveri; Jian Tian; Sylwester Arabas

CAMPv1.0 Matthew L. Dawson, Christian Guzman, Jeffrey H. Curtis, Matthew West

Matthew L. Dawson et al.


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Short summary
Progress in identifying complex, mixed-phase physicochemical processes has resulted in an advanced understanding of the evolution of atmospheric systems but has also introduced a level of complexity that few atmospheric models were designed to handle. We present a flexible treatment for multi-phase chemical processes for models of diverse scale, from box up to global models. This enables users to build a customized multiphase mechanism that is accessible to a much wider community.