2019
DOI: 10.1029/2018ms001603
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The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution

Abstract: This work documents the first version of the U.S. Department of Energy (DOE) new EnergyExascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully coupled physical model designed to address DOE mission-relevant water cycle questions. Its components include atmosphere and land (110-km grid spacing), ocean and sea ice (60 km in the midlatitudes and 30 km at the equator and poles), and river transport (55 km) models. This base configuration will also serve as a foundation for additional… Show more

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Cited by 540 publications
(716 citation statements)
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References 131 publications
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“…The lower forcing estimate, consistent with Figure 24 of Golaz et al (), is sensitive to the presence of aerosols from stratospheric volcanoes (absent during the period Golaz et al focused on), which explains most of the difference in the estimates, but emission sources of anthropogenic aerosols were also significantly higher during the earlier (1980–2004) period. The differences compared to the F2000 emissions used in C2 may also be partially explained by the SSTs differences used in C2 and column 3—clouds and cloud responses to aerosols and GHG can be sensitive to surface temperature and the 1980–2014 period is characterized by very large El Niño events not present in the SST climatologies used in C2 or the later time period analyzed in Golaz et al (). The differences in emissions and small differences in methodology compared to that used in Golaz et al () and the Forster et al () result showed that forcing estimates can depend significantly on the length of analysis interval indicated the sensitivity of the calculation.…”
Section: Model Evaluationsupporting
confidence: 81%
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“…The lower forcing estimate, consistent with Figure 24 of Golaz et al (), is sensitive to the presence of aerosols from stratospheric volcanoes (absent during the period Golaz et al focused on), which explains most of the difference in the estimates, but emission sources of anthropogenic aerosols were also significantly higher during the earlier (1980–2004) period. The differences compared to the F2000 emissions used in C2 may also be partially explained by the SSTs differences used in C2 and column 3—clouds and cloud responses to aerosols and GHG can be sensitive to surface temperature and the 1980–2014 period is characterized by very large El Niño events not present in the SST climatologies used in C2 or the later time period analyzed in Golaz et al (). The differences in emissions and small differences in methodology compared to that used in Golaz et al () and the Forster et al () result showed that forcing estimates can depend significantly on the length of analysis interval indicated the sensitivity of the calculation.…”
Section: Model Evaluationsupporting
confidence: 81%
“…Golaz et al () noted a lower amplitude estimate of −1.65 W/m 2 for the 1995–2015 time period. In this case, both simulations included the same volcanic aerosols in the stratosphere so the differences must be associated with the higher anthropogenic aerosol sources or higher SSTs compared to the period analyzed by Golaz et al (). Column 5 shows CAM5 values reported in Gettelman and Morrison () with a total aerosol ERF of −1.6 W/m 2 .…”
Section: Model Evaluationmentioning
confidence: 95%
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“…In all EAMv1 simulations, emissions of anthropogenic and biomass burning aerosols are from CMIP6 data sets, except that SOAG emissions are derived from SOA formation rates from a S2015 simulation to improve the SOA representation in the model, as described in section . Instead of using yearly varying aerosol emissions for 2006–2007, we use the average between 2000–2014 to represent PD aerosol conditions by removing the interannual variation in emissions (Yang et al, , ) and in aerosol forcing estimates (e.g., Golaz et al, ). PI emissions use the CMIP6 data set for year 1850.…”
Section: Model Experiments For Sensitivity Tests and Aerosol Forcing mentioning
confidence: 99%
“…Therefore, mitigating the precipitation bias over the Central United States is important to GCM development. This is particularly important for the U.S. Department of Energy‐funded Energy Exascale Earth System Model project (Bader et al, ) due to its strong focus on understanding regional climate changes, especially those related to the water cycle over North America (Golaz et al, ).…”
Section: Introductionmentioning
confidence: 99%