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GCClassic

GEOS-Chem is a versatile tool enabling simulations of atmospheric composition on various scales, from local to global. It operates offline as a 3-D chemical transport model, utilizing assimilated meteorological data from NASA’s Goddard Earth Observing System (GEOS) provided by the Global Modeling Assimilation Office (GMAO). Alternatively, it can function online as a chemical module integrated with weather and climate models.

This open-access software is employed by numerous research groups worldwide, addressing a wide array of atmospheric composition challenges. GEOS-Chem is available for download via GitHub and is fully supported for utilization on the Amazon Web Services cloud.

In its offline mode, GEOS-Chem facilitates immediate simulations of atmospheric composition from 1979 to the present, utilizing NASA GEOS data bundled with the tool. Two primary products, GEOS-FP and MERRA-2 reanalysis, offer varying horizontal resolutions and vertical levels. Simulations can be executed using shared-memory parallelization (GC-Classic) or distributed-memory parallelization (GCHP), operating on rectilinear and cubed-sphere grids, respectively.

GEOS-Chem allows global simulations at native or lower resolutions and offers options for nested mode or zoomed regions. The online version involves the stand-alone GEOS-Chem chemical module, conducting various atmospheric processes on specified grids. It can be coupled with different weather or climate models, including the NASA GEOS Earth System Model, WRF weather model, Beijing Climate Center ESM, and NCAR CESM.

The model follows a standardized code maintained by the GEOS-Chem Support Team, receiving regular updates. It is highly modular, parallelized, and compatible with various platforms and Fortran compilers. An adjoint of GEOS-Chem is maintained for inverse modeling and sensitivity studies.

The community-driven model is supported by working groups, a steering committee, and funding from various entities. User engagement, feedback, and contributions are fundamental to its continuous improvement and adaptation to research needs. Software tools like GCPy aid in processing GEOS-Chem model outputs, enhancing analysis and visualization capabilities.

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