Preprints
https://doi.org/10.5194/gmd-2022-42
https://doi.org/10.5194/gmd-2022-42
Submitted as: development and technical paper
24 Feb 2022
Submitted as: development and technical paper | 24 Feb 2022
Status: this preprint is currently under review for the journal GMD.

Improved Advection, Resolution, Performance, and Community Access in the New Generation (Version 13) of the High Performance GEOS-Chem Global Atmospheric Chemistry Model (GCHP)

Randall V. Martin1, Sebastian D. Eastham2, Liam Bindle1, Elizabeth W. Lundgren3, Thomas L. Clune4, Christoph A. Keller4,5,a, William Downs3,b, Dandan Zhang1, Robert A. Lucchesi4, Melissa P. Sulprizio3, Robert M. Yantosca3, Yanshun Li1, Lucas Estrada3, William M. Putman4, Benjamin M. Auer4, Atanas L. Trayanov4, Steven Pawson5, and Daniel J. Jacob3 Randall V. Martin et al.
  • 1Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
  • 2Laboratory for Aviation and the Environment, Massachusetts Institute of Technology, Cambridge, MA, USA
  • 3John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
  • 4Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 5Universities Space Research Association, Columbia, MD, USA
  • anow at: Morgan State University, MD, USA
  • bnow at: Rosenstiel School of Marine and Atmospheric Science, University of Miami, FL, USA

Abstract. We describe a new generation of the high-performance GEOS-Chem (GCHP) global model of atmospheric composition developed as part of the GEOS-Chem version 13 series. GEOS-Chem is an open-source grid-independent model that can be used online within a meteorological simulation or off-line using archived meteorological data. GCHP is an offline implementation of GEOS-Chem driven by NASA Goddard Earth Observing System (GEOS) meteorological data for massively parallel simulations. Version 13 offers transformational advances in GCHP for ease of use, computational performance, versatility, resolution, and accuracy. Specific improvements include (a) stretched-grid capability for higher resolution in user-selected regions, (b) easier build with a build system generator (CMake) and a package manager (Spack), (c) software containers to enable immediate model download and configuration on local computing clusters, (d) better parallelization to enable simulation on thousands of cores, (e) multi-node cloud capability, and (f) more accurate transport with new native cubed-sphere GEOS meteorological archives including air mass fluxes at hourly temporal resolution with spatial resolution up to C720 (~12 km). The C720 data are now part of the operational GEOS Forward Processing (GEOS-FP) output stream, and a C180 (~50 km) consistent archive for 1998–present is now being generated as part of a new GEOS-IT data stream. Both of these data streams are continuously being archived by the GEOS-Chem Support Team for access by GCHP users. Directly using horizontal air mass fluxes rather than inferring from wind data significantly reduces global mean error in calculated surface pressure and vertical advection.

Randall V. Martin et al.

Status: open (until 28 May 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-42', Anonymous Referee #1, 24 Mar 2022 reply

Randall V. Martin et al.

Randall V. Martin et al.

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Short summary
Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as stand-alone models. The widely-used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the off-line high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores including on the cloud with improved access, performance, and accuracy.