An adaptive auto-reduction solver for speeding up integration of chemical kinetics in atmospheric chemistry models: implementation and evaluation in the Kinetic Pre-Processor (KPP) version 3.0.0

This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint.

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Authors

Haipeng Lin , Michael S. Long, Rolf Sander, Robert M. Yantosca, Lucas A. Estrada, Lu Shen, Daniel J. Jacob

Abstract

Kinetic integration of large and stiff chemical mechanisms is a computational bottleneck in models of atmospheric chemistry. It requires implicit solution of the coupled system of kinetic differential equations with time-consuming construction and inversion of the Jacobian matrix. We present here a new version of the Kinetic Pre-Processor (KPP 3.0.0) for fast integration of chemical kinetics featuring a range of improvements over previous versions in performance, diagnostics, versatility, and community openness. KPP 3.0.0 includes a new adaptive auto-reduction solver to decrease the size of any mechanism locally and on the fly under conditions where full complexity is not needed, by partitioning species as “fast” or “slow” based on their local production and loss rates. Previous implementations of this adaptive solver suffered from excessive overhead in the repeated construction of the local Jacobian matrix or were hard-wired to specific mechanisms. Here we retain the general applicability of the method to any mechanism and avoid overhead by using pre-computed Jacobian matrix terms for the full mechanism and cropping the matrix locally to remove the slow species with no change in memory allocation. We apply this adaptive solver within KPP 3.0.0 to the GEOS-Chem global 3-D model of atmospheric chemistry and demonstrate a 32% reduction in solver time while maintaining a mean error lower than 1% for key species in the troposphere.

DOI

https://doi.org/10.31223/X5505V

Subjects

Environmental Engineering, Numerical Analysis and Scientific Computing

Keywords

chemical kinetics, atmospheric chemical mechanism, chemical solvers, adaptive mechanism reduction, chemical transport modeling, atmospheric chemistry

Dates

Published: 2022-07-15 12:05

Last Updated: 2022-08-15 16:58

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License

CC BY Attribution 4.0 International

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Conflict of interest statement:
None.

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