Atmospher Sci & Global Chg
Research Highlights

September 2018

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.

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. Enlarge Image.

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.

Summary

Global Earth system simulations require massive numerical calculations. Because of limited computing resources to perform these detailed simulations, models use mathematical approximations to improve computational efficiency. Although the inaccuracies associated with such approximations can seem small in short tests, they can add up to significant amounts in longer simulations. For example, in a prototype version of E3SM, researchers diagnosed a spurious source of atmospheric water arising from approximations. If all of that extra water had condensed and rained out to the surface, it would lead to an artificial sea level rise of more than 10 centimeters (cm) per simulated century in the low-resolution model, and over 30 cm per century at higher resolutions. The actual sea level rise in the 20th century was estimated to be 17-20 cm, so these offsets, or biases, were significant.

In this study, researchers identified, quantified, and corrected several sources of water conservation error within EAM. Using new techniques in both short (five-day) and long (multi-year) sensitivity experiments, they found the largest error sources in the equations for specific interactions between different physical phenomena in the Earth system. The largest errors resulted from the numerical coupling between the resolved dynamics and the parameterized subgrid physics. A hybrid coupling using different methods for fluid dynamics and tracer transport provided a reduction of water conservation error by a factor of 50 at 1 degree horizontal resolution.

The second largest error source was the use of an overly simplified relationship between the surface moisture flux and latent heat flux at the interface between the host model and the turbulence parameterization. This error was prevented by applying the same (correct) relationship throughout the entire model.

Two additional types of conservation error that resulted from correcting the surface moisture flux and clipping negative water concentrations were avoided by using massconserving fixers. With all four error sources addressed, the artifact affecting sea level rise was negligible (less than 0.002 cm per century). This makes the updated version of E3SM a much more accurate tool for predictions related to Earth's water cycle.

Acknowledgments

Sponsors and User Facilities: This research was supported as part of the Energy Exascale Earth System Model project, funded by the U.S. Department of Energy (DOE) Office of Science, Biological and Environmental Research. Pacific Northwest National Laboratory (PNNL) is operated for DOE by Battelle Memorial Institute under contract No. DE-AC06-76RLO 1830. Work at Lawrence Livermore National Laboratory was performed under the auspices of DOE by LLNL under contract No. DE-AC52-07NA27344. Jin-Ho Yoon was partially supported by the National Research Foundation grant NRF-2017R1A2B4007480.

This research used high-performance computing resources from the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, supported by the DOE Office of Science under contract No. DE-AC05-00OR22725; PNNL Institutional Computing; and the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science user facility supported under contract No. DE-AC02-05CH11231.

Research Area: Climate and Earth Systems Science

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; and Wuyin Lin, Brookhaven National Laboratory