Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive

By Gavin A. Schmidt, M. Kelley, L. Nazarenko, R. Ruedy, G. Russell, I. Aleinov, M. Bauer, S. Bauer, M. Bhat, Rainer Bleck and 35 more. 2014

660 citations recorded by the source corpus.

We present a description of the ModelE2 version of the Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) and the configurations used in the simulations performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). We use six variations related to the treatment of the atmospheric composition, the calculation of aerosol indirect effects, and ocean model component. Specifically, we test the difference between atmospheric models that have noninteractive composition, where radiatively important aerosols and ozone are prescribed from precomputed decadal averages, and interactive versions where atmospheric chemistry and aerosols are calculated given decadally varying emissions. The impact of the first aerosol indirect effect on clouds is either specified using a simple tuning, or parameterized using a cloud microphysics scheme. We also use two dynamic ocean components: the Russell and HYbrid Coordinate Ocean Model (HYCOM) which differ significantly in their basic formulations and grid. Results are presented for the climatological means over the satellite era (1980–2004) taken from transient simulations starting from the preindustrial (1850) driven by estimates of appropriate forcings over the 20th Century. Differences in base climate and variability related to the choice of ocean model are large, indicating an important structural uncertainty. The impact of interactive atmospheric composition on the climatology is relatively small except in regions such as the lower stratosphere, where ozone plays an important role, and the tropics, where aerosol changes affect the hydrological cycle and cloud cover. While key improvements over previous versions of the model are evident, these are not uniform across all metrics.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/7dd47bf8891e733b98d897adb44b288d0f5ba39a

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Citations in the corpus

Industry 4.0 for the Construction Industry: Review of Management Perspective (2019, background): “0) was characterized by production with an inclination toward digitization and the adoption of “smart production” (Lasi et al. 2014; Lee and Lee 2015; Schmidt et al. 2014; Bahrin et al. 2016).”
The Earth Surface Mineral Dust Source Investigation: An Earth Science Imaging Spectroscopy Mission (2020, methodology): “1 is an update of the GISS Model E2 (Schmidt et al. 2014), used by Perlwitz et al. (2015a, b) and Pérez et al. (2015, 2016) and participated in the coordinated experiments of Coupled Model Intercomparison Project 6.”
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections (2015, methodology): “The data set contains the outcome of control simulations of the GISS global circulation model [20] and is part of the CMIP5 climate modeling ensemble.”
CMIP5 historical simulations (1850–2012) with GISS ModelE2 (2014, methodology): “While the models exhibit interannual variability in sea surface temperature in the equatorial East Pacific that resembles El Ni~no [Schmidt et al., 2014a], these events are primarily unforced and thus temporally uncorrelated with observed events.”