U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


Earth System Model High-Latitude Temperature Biases can be Resolved by Incorporating Realistic Surface Longwave Emission
Published: January 01, 2018
Posted: April 10, 2018

The inclusion of physically-realistic infrared surface emissivity in an Earth System Model can greatly reduce that model's polar temperature and sea-ice biases, relative to observations.

The Science
This paper systematically evaluates the role of infrared surficial physics in controlling the high-latitude surface temperature and sea-ice biases that Earth System Models (ESMs) exhibit relative to observations. ESMs have conventionally considered the impact of surface emissivity to be small, and surfaces are assumed either to be perfect emitters of infrared radiation, or their emission is spatially and temporally invariant. However, frozen and unfrozen surfaces exhibit highly-contrasting infrared surface emissivity, therefore we evaluated the impact of physically-realistic emissivity representation in an ESM and consequently quantified the ice-emissivity feedback.

The Impact
This paper finds that the inclusion of realistic infrared surface emissivity reduces an ESM's cryospheric biases in wintertime Arctic surface temperature from -7.2 ± 0.9 K to -1.1 ± 1.2 K, relative to observations. This bias reduction is particularly prominent over the Arctic Ocean, suggesting that this physical process is central to the reduction in the persistent cold-pole biases that ESMs exhibit. Feedback analysis was also performed and revealed that the ice-emissivity feedback exhibits both spatial and temporal variability, and accounting for this variability could provide feedback assessments which differ in sign from conventional feedback analysis methods.

Summary
Earth System Models have exhibited cold biases in Arctic Ocean wintertime surface air temperature, with profound implications for their predictive abilities for both the cryosphere and low latitudes. The scientific focus to explain this bias has largely been on ice-albedo feedbacks, but this work, published in Journal Geophysical Research-Atmospheres, presents a comprehensive analysis that shows that, because frozen and unfrozen surfaces have significantly different emission properties, model representation of infrared surface emissivity plays a central role in ESM cold pole biases. This work shows that the inclusion of physically realistic values of this quantity largely eliminates Arctic wintertime temperature biases in an ESM, even though the magnitude of the top-of-atmosphere feedback is small and varies both spatially and temporally. Because of the reduction in bias by almost 6 °K, this work indicates that Earth System Models should incorporate physically-realistic values of surface emissivity across relevant model components to reduce significant, and avoidable, errors.

Contacts (BER PMs)
Dorothy Koch
Earth System Modeling
Dorothy.Koch@science.doe.gov

(PI Contacts)
Xianglei Huang,
University of Michigan,
xianglei@umich.edu

Funding
Earth System Modeling
This work was supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research Earth System Modeling Program and the Office of Science, Scientific Discovery through Advanced Computing, under contract DE-AC02-05CH11231. The authors used resources of the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under that same award.

Publication
Kuo, C., Feldman, D. R., Huang, X., Flanner, M., Yang, P., & Chen, X. "Time-dependent cryospheric longwave surface emissivity feedback in the Community Earth System Model." Journal of Geophysical Research: Atmospheres, 123, 789-813 (2018). [DOI:10.1002/2017JD027595]

Related Links
Project Description

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Cross-Cutting: Scientific Computing and SciDAC

Division: SC-23.1 Climate and Environmental Sciences Division, BER

 

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