September 19, 2018
Web Feature

Systematic Water Conservation Errors Reduced in E3SM Atmosphere Model

Improving water conservation in the Energy Exascale Earth System Model's atmosphere component has important implications for projecting sea level change

water

After diagnosing and correcting a water conservation error in the atmosphere component in DOE's Energy Exascale Earth System Model, the artifact affecting sea level rise was negligible (less than 0.002 cm per century). This makes the updated version of E3SM much more accurate for predictions related to Earth's water cycle.

The Science

For computer models that simulate the evolution of Earth's climate, conserving the total amount of atmospheric water is an important feature. Even small inaccuracies in the water budget can lead to sizable errors in projecting sea level change in century-long simulations. A study led by researchers at the U.S. Department of Energy's (DOE) Pacific Northwest National Laboratory quantified and reduced various sources of water conservation errors in the atmosphere component of DOE's Energy Exascale Earth System Model (E3SM).

The Impact

Reduction of systematic water conservation errors in atmosphere models is important for accurately simulating components of Earth's water cycle, such as global mean precipitation and sea level. In an earlier version of the E3SM Atmosphere Model (EAM), which is E3SM's atmosphere component, water conservation contained errors that could have produced spurious sea level changes comparable to those observed in the 20th century. After researchers identified and addressed several sources of water conservation errors in EAM, such errors became negligible and insensitive to model resolution in EAM version 1, which improved the overall water conservation property of E3SM.

 

Reference: K. Zhang et al., "Impact of Numerical Choices on Water Conservation in the E3SM Atmosphere Model version 1 (EAMv1)." Geoscientific Model Development 11, 1971-1988 (2018). [https://doi.org/10.5194/gmd-11-1971-2018]

Published: September 19, 2018

Research Team

Kai Zhang, Philip J. Rasch, Hui Wan, L. Ruby Leung, Po-Lun Ma, Balwinder Singh, Susannah Burrows, Jin-Ho Yoon (now at Gwangju Institute of Science and Technology in South Korea), Hailong Wang, and Yun Qian, PNNL
Mark A. Taylor, Sandia National Laboratories
Jean-Christophe Golaz, Qi Tang, Peter Caldwell, and Shaocheng Xie, Lawrence Livermore National Laboratory
Jon Wolfe, Los Alamos National Laboratory
Wuyin Lin, Brookhaven National Laboratory

Research topics