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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-287
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-287
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: development and technical paper 26 Nov 2019

Submitted as: development and technical paper | 26 Nov 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

A Multiphase CMAQ Version 5.0 Adjoint

Shunliu Zhao1, Matthew G. Russell1, Amir Hakami1, Shannon L. Capps2, Matthew D. Turner3, Daven K. Henze4, Peter B. Percell5, Jaroslav Resler6, Huizhong Shen7, Armistead G. Russell7, Athanasios Nenes8,9,10, Amanda J. Pappin11, Sergey L. Napelenok12, Jesse O. Bash12, Kathleen M. Fahey12, Gregory R. Carmichael13, Charles O. Stanier13, and Tianfeng Chai14 Shunliu Zhao et al.
  • 1Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada
  • 2Civil, Architectural, and Environmental Engineering, Drexel University, Philadelphia, PA 19104, USA
  • 3SAIC, Stennis Space Center, MS 39529, USA
  • 4Mechanical Engineering Department, University of Colorado, Boulder, CO 80309, USA
  • 5Department of Earth & Atmospheric Sciences, University of Houston, Houston, TX 77204, USA
  • 6Institute of Computer Science of the Czech Academy of Sciences, Prague, 182 07, Czech Republic
  • 7School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30331, USA
  • 8School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30331, USA
  • 9School of Architecture, Civil & Environmental Engineering, Ecole polytechnique fédéralede Lausanne, 1015, Lausanne, Switzerland
  • 10Institute for Chemical Engineering Sciences, Foundation for Research and Technology Hellas, Patras, 26504, Greece
  • 11Air Health Effects Division, Health Canada, Ottawa, ON K1A 0K9, Canada
  • 12Atmospheric & Environmental Systems Modeling Division, U.S. EPA, Research Triangle Park, NC 27711, USA
  • 13Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, IA 52242, USA
  • 14College of Computer, Mathematical, and Natural Sciences, University of Maryland, College Park, MD 20742, USA

Abstract. We present the development of a multiphase adjoint for the Community Multiscale Air Quality (CMAQ) model, a widely used chemical transport model. The adjoint provides location- and time-specific gradients that can be used in various applications such as backward sensitivity analysis, source attribution, optimal pollution control, data assimilation and inverse modeling. The science processes of the CMAQ model include gas-phase chemistry, aerosols, cloud chemistry and dynamics, diffusion and advection. Discrete adjoints are implemented for all the science processes, with an additional continuous adjoint for advection. The development of discrete adjoints is assisted with Algorithmic Differentiation (AD) tools. Particularly, the Kinetic PreProcessor (KPP) is implemented for gas-phase and aqueous chemistry, and two different automatic differentiation tools are used for other processes such as clouds, aerosols, diffusion, and advection. The continuous adjoint of advection is developed manually. For adjoint validation, the brute-force or Finite Difference Method (FDM) is implemented process by process with box- or column-model simulations. Due to the inherent limitations of the FDM caused by numerical round-off errors, the Complex Variable Method (CVM) is adopted where necessary. The adjoint model often shows better agreement with the CVM than with the FDM. The adjoints of all science processes compare favorably with the FDM/CVM. In an example application of the full, multiphase adjoint model, we provide the first estimates of how emissions of PM2.5 affect public health across the US.

Shunliu Zhao et al.
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Status: open (until 21 Jan 2020)
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CMAQ 5.0 Adjoint Input Data S. Zhao, M. G. Russell, A. Hakami, S. L. Capps, M. D. Turner, D. K. Henze, P. B. Percell, J. Resler, H. Shen, A. G. Russell, A. Nenes, A. J. Pappin, S. L. Napelenok, and J. O. Bash, K. M. Fahey, G. R. Carmichael, C. O. Stanier, and T. Chai https://doi.org/10.5281/zenodo.3473444

Shunliu Zhao et al.
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