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An adaptive method for speeding up the numerical integration of chemical...

Shen, L., D. J. Jacob, M. Santillana, X. Wang, and W. Chen (2020), An adaptive method for speeding up the numerical integration of chemical mechanisms in atmospheric chemistry models: application to GEOS-Chem version 12.0.0, Geosci. Model. Dev., 13, 2475-2486, doi:10.5194/gmd-13-2475-2020.
Abstract: 

The major computational bottleneck in atmospheric chemistry models is the numerical integration of the stiff coupled system of kinetic equations describing the chemical evolution of the system as defined by the model chemical mechanism (typically over 100 coupled species). We present an adaptive method to greatly reduce the computational cost of that numerical integration in global 3-D models while maintaining high accuracy. Most of the atmosphere does not in fact require solving for the full chemical complexity of the mechanism, so considerable simplification is possible if one can recognize the dynamic continuum of chemical complexity required across the atmospheric domain. We do this by constructing a limited set of reduced chemical mechanisms (chemical regimes) to cover the range of atmospheric conditions and then pick locally and on the fly which mechanism to use for a given grid box and time step on the basis of computed production and loss rates for individual species. Application to the GEOS-Chem global 3-D model for oxidant–aerosol chemistry in the troposphere and stratosphere (full mechanism of 228 species) is presented. We show that 20 chemical regimes can largely encompass the range of conditions encountered in the model. Results from a 2-year GEOS-Chem simulation shows that our method can reduce the computational cost of chemical integration by 30 %–40 % while maintaining accuracy better than 1 % and with no error growth. Our method retains the full complexity of the original chemical mechanism where it is needed, provides the same model output diagnostics (species production and loss rates, reaction rates) as the full mechanism, and can accommodate changes in the chemical mechanism or in model resolution without having to reconstruct the chemical regimes.

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Research Program: 
Modeling Analysis and Prediction Program (MAP)