GEOS-Chem enables simulations of atmospheric composition on local to global scales. It can be used off-line as a 3-D chemical transport model driven by assimilated meteorological observations from the Goddard Earth Observing System (GEOS) of the NASA Global Modeling Assimilation Office (GMAO). It can also be used on-line as a chemical module coupled to weather and climate models. GEOS-Chem is developed and used by hundreds of research groups worldwide as a versatile tool for application to a wide range of atmospheric composition problems. It is open-access and can be downloaded through github. It is also fully supported for use on the Amazon Web Services cloud.
The off-line version of GEOS-Chem allows immediate simulations of atmospheric composition for any period from 1979 to present using the continuous global archive of NASA GEOS data packaged with GEOS-Chem. The operational GEOS-Forward Processing product (GEOS-FP) for 2012-present has a horizontal resolution of 0.25° latitude x 0.3125° longitude with 72 vertical levels. The MERRA-2 reanalysis product for 1979-present has a horizontal resolution of 0.5° latitude x 0.625° longitude, again with 72 vertical levels. Off-line simulations can be conducted with OpenMP shared-memory parallelization (GEOS-Chem Classic, called GC-Classic) or with MPI distributed-memory parallelization (GEOS-Chem high-performance, called GCHP). GC-Classic operates on a rectilinear grid and GCHP operates on a cubed-sphere grid. GEOS-Chem simulations can be conducted globally at the native grid resolution or at user-selected lower resolution. They can also be conducted over user-selected regions with dynamic boundary conditions (nested mode) or in stretched-grid mode with zoom over a region of interest.
On-line applications of GEOS-Chem use the stand-alone GEOS-Chem chemical module that performs chemistry, aerosol microphysics, radiation, emissions, and deposition on 1-D atmospheric columns for any grid specified at run time. In on-line applications, chemical transport is performed by a weather or climate model coupled to GEOS-Chem. The emission component of GEOS-Chem (HEMCO) can also be used independently of the rest of GEOS-Chem or as a generalized data broker in the weather/climate model. GEOS-Chem has in this manner been coupled with the NASA GEOS Earth System Model (ESM), the WRF weather model, the Beijing Climate Center ESM, and the NCAR CESM.
All versions of the GEOS-Chem model use the same standard code maintained by the GEOS-Chem Support Team. Updated versions of this standard code are released regularly. Detailed GEOS-Chem on-line documentation is available including a User's Guide. The code is fully modular and highly parallelized. It is presently being used on several types of Linux-like computing platforms running Ubuntu, Fedora, Red Hat, Rocky Linux, Alma Linux, Amazon Linux, MacOS, and similar operating systems. It supports Intel Fortran and the open-source GNU Fortran compilers.
An adjoint of the GEOS-Chem model is maintained by the GEOS-Chem community under the direction of Adjoint Model Scientist Daven Henze for inverse modeling, data assimilation, and sensitivity studies. See the GEOS-Chem Adjoint web site for more details.
Several software tools facilitate the processing of GEOS-Chem model outputs. This includes GCPy, a package of free and open-source Python tools specifically designed for GEOS-Chem output analysis and visualization.
GEOS-Chem is a freely accessible community model. It is owned and supported by its user community under the purview of Working Groups and an international Steering Committee. User participation, responsibility, and feedback are essential. See our welcome page for new users. The model is maintained as a robust state-of-the-science facility by combining a nimble grass-roots approach to code development with strong version control. All development is done by users in support of their own research needs and then shared with the community. General management of GEOS-Chem is supported by the US NASA Earth Science Division, the Canadian National Science and Engineering Research Council, and the Nanjing University of Information Sciences and Technology.