The Community Earth System Model: A Framework for Collaborative Research

Hurrell, James W.; Holland, Marika M.; Gent, Peter R.; Ghan, Steven J.; Kay, J. E.; Kushner, Paul J.; Lamarque, J. F.; Large, William G.; Lawrence, David M.; Lindsay, Keith; Lipscomb, William H.; Long, Matthew C.; Mahowald, N. M.; Marsh, D. R.; Neale, Rich; Rasch, Philip J.; Vavrus, Stephen J.; Vertenstein, Mariana; Bader, David C.; Collins, William D.; Hack, James J.; Kiehl, J. T.; Marshall, Shawn J.

doi:10.1175/bams-d-12-00121.1

Cited by 2,088 publications

(1,210 citation statements)

References 95 publications

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“…This is a fully-coupled, global climate model consisting of interactive atmosphere (CAM4), ocean (POP2), sea ice (CICE4) and land (CLM4) components. CESM1 was developed from the Community Climate System Model (CCSM) version 4 (Gent et al 2011); its enhancements include the incorporation of biogeochemical cycles and atmospheric chemistry (Hurrell et al 2013;Moore et al 2013). The atmospheric model was run at T31 resolution, which corresponds to 3.75° by 3.75° horizontal resolution, with 26 vertical levels, while the ocean horizontal resolution is 3° by 3° with 60 vertical levels.…”

Section: Methodsmentioning

confidence: 99%

Mechanisms rectifying the annual mean response of tropical Atlantic rainfall to precessional forcing

Tigchelaar

Timmermann

2015

Clim Dyn

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Section: Methodsmentioning

confidence: 99%

Mechanisms rectifying the annual mean response of tropical Atlantic rainfall to precessional forcing

Tigchelaar

Timmermann

2015

Clim Dyn

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“…For simulations, we use historical and RCP4.5 runs from 44 different GCMs from the CMIP5 archive [Taylor et al, 2012;Bi et al, 2013;Xin et al, 2013;Ji et al, 2014;von Salzen et al, 2013;Meehl et al, 2012;Hurrell et al, 2012;Scoccimarro et al, 2011;Voldoire et al, 2013;Rotstayn et al, 2010;Hazeleger et al, 2010;Li et al, 2013;Delworth et al, 2006;Donner et al, 2011;Schmidt et al, 2014;Smith et al, 2010;Collins et al, 2011;Jones et al, 2011;Volodin et al, 2010;Dufresne et al, 2013;Hourdin et al, 2013;Sakamoto et al, 2012;Watanabe et al, 2010Watanabe et al, , 2011Giorgetta et al, 2013;Yukimoto et al, 2012;Bentsen et al, 2013], and from the 100 realization single-model large ensemble of the MPI-ESM [Giorgetta et al, 2013]. The large ensemble uses the model version MPI-ESM1.1 in low resolution (LR) configuration, with resolution T63 and 47 vertical levels in the atmosphere and 1.5 ∘ resolution and 40 vertical levels in the ocean.…”

Section: Datamentioning

confidence: 99%

Internal variability in simulated and observed tropical tropospheric temperature trends

Suárez-Gutiérrez

Thorne

et al. 2017

Geophysical Research Letters

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We explore the extent to which internal variability can reconcile discrepancies between observed and simulated warming in the upper tropical troposphere. We compare all extant radiosonde‐based estimates for the period 1958–2014 to simulations from the Coupled Model Intercomparison Project phase 5 multimodel ensemble and the 100 realization Max Planck Institute large ensemble. We consider annual mean temperatures and all available 30‐and 15‐year trends. Most observed trends fall within the ensemble spread for most of the record, and trends calculated over 15‐year periods show better agreement than 30‐year trends, with generally larger discrepancies for the older observational products. The simulated amplification of surface warming aloft in the troposphere is consistent with observations, and the linear correlation between surface and simultaneous tropospheric warming trends decreases with trend length. We conclude that trend differences between observations and simulations of tropical tropospheric temperatures are dominated by observational uncertainty and chaotic internal variability rather than by systematic errors in model performance.

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“…Here we describe and validate radiative kernels calculated with CESM-CAM5 (Hurrell et al, 2013) for the top of the atmosphere and the surface. These radiative feedback kernels were calculated with CESM version 1.1.2, the same as that used for the 40-member CESM large ensemble (Kay et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Surface and top-of-atmosphere radiative feedback kernels for CESM-CAM5

Pendergrass

Conley

Vitt

2018

Earth Syst. Sci. Data

123

149

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Abstract. Radiative kernels at the top of the atmosphere are useful for decomposing changes in atmospheric radiative fluxes due to feedbacks from atmosphere and surface temperature, water vapor, and surface albedo. Here we describe and validate radiative kernels calculated with the large-ensemble version of CAM5, CESM1.1.2, at the top of the atmosphere and the surface. Estimates of the radiative forcing from greenhouse gases and aerosols in RCP8.5 in the CESM large-ensemble simulations are also diagnosed. As an application, feedbacks are calculated for the CESM large ensemble. The kernels are freely available at https://doi.org/10.5065/D6F47MT6, and accompanying software can be downloaded from https://github.com/apendergrass/cam5-kernels.

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The Community Earth System Model: A Framework for Collaborative Research

Abstract: By simulating biogeochemical cycles, the Greenland ice sheet, and more-with reach to the lower thermosphere-this system gives the research community a flexible, state-of-thescience tool for understanding climate variability and change.

Cited by 2,088 publications

References 95 publications

Mechanisms rectifying the annual mean response of tropical Atlantic rainfall to precessional forcing

Mechanisms rectifying the annual mean response of tropical Atlantic rainfall to precessional forcing

Internal variability in simulated and observed tropical tropospheric temperature trends

Surface and top-of-atmosphere radiative feedback kernels for CESM-CAM5

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