Publication Date:
2019-09-12
Description:
Global modeling of atmospheric composition is a grand computational challenge because of the need to simulate large coupled systems of chemical species interacting with transport on all scales. Off-line chemical transport models (CTMs), where the chemical continuity equations are solved using meteorological data as input, have the advantages of simplicity and reproducibility, and are important vehicles for developing knowledge that can then be transferred to Earth system models. However, they have generally not been designed to take advantage of massively parallel computing architectures. Here we develop such a high-performance capability (GCHP) for GEOS-Chem, a CTM driven by GEOS meteorological data from the NASA Global Modeling and Assimilation Office (GMAO) and used by hundreds of research groups worldwide. GCHP is a grid-independent implementation of GEOS-Chem using the Earth System Modeling Framework (ESMF) that permits the same standard model to be run in a distributed-memory framework, scalable from six cores on a single machine up to hundreds of cores distributed across a network. GCHP also allows GEOS-Chem to take advantage of the native GEOS cubed-sphere grid for greater accuracy and computational efficiency in simulating transport. GCHP allows GEOS-Chem simulations to be conducted with high computational scalability up to at least 500 cores, so that global simulations of stratosphere-troposphere oxidant-aerosol chemistry at C180 spatial resolution (~0.50.625) or finer become routinely feasible.
Keywords:
Earth Resources and Remote Sensing
Type:
GSFC-E-DAA-TN58958
,
Geoscientific Model Development (ISSN 1991-959X) (e-ISSN 1991-9603); 11; 7; 2941-2953
Format:
application/pdf
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