CAM-SE: A scalable spectral element dynamical core for the Community Atmosphere Model

By John M. Dennis, Jim Edwards, Katherine J. Evans, Oksana Guba, Peter H. Lauritzen, Arthur A. Mirin, Amik St.-Cyr, Mark A. Taylor, Patrick H. Worley. The international journal of high performance computing applications, 2012

383 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/065d85a805318950fbecec91ed9d35cc1ef9c66a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. J. Golaz
2. V. Larson
3. Richard B. Neale
4. Wuyin Lin
5. J. Richter
6. Xiaohong Liu
7. Philip J. Rasch
8. S. Xie

In Global and Planetary Change

1. J. Golaz
2. V. Larson
3. Richard B. Neale
4. J. Richter
5. Philip J. Rasch
6. Xiaohong Liu
7. Wuyin Lin
8. S. Xie

Citations in the corpus

• An Overview of the Atmospheric Component of the Energy Exascale Earth System Model (2019, methodology): “Both models also have a more active hydrologic cycle than indicated by the Global Precipitation Climate Project (GPCP) observational estimate, although that estimate may be low by as much as 10% (see, e.g., Stephens et al., 2012). EAMv1 has higher water paths than CAM5 and lower ice water paths, but”
• Understanding Cloud and Convective Characteristics in Version 1 of the E3SM Atmosphere Model (2018, background): “, 2012), which has a resolution of 1° in horizontal and 30 layers in vertical, but it adopts the SE dynamical core (Dennis et al., 2012) and makes a few adjustments to the physical parameter settings to achieve energy”
• The DOE E3SM Coupled Model Version 1: Description and Results at High Resolution (2019, background): “The atmospheric component is based on the spectral-element atmospheric dynamical core (Dennis et al., 2012) with 72 vertical levels.”