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.
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.
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.
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)
Earth System Modeling
University of Michigan,
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.
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]
SC-23.1 Climate and Environmental Sciences Division, BER
BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER
Aug 24, 2019
New Approach for Studying How Microbes Influence Their Environment
A diverse group of scientists suggests a common framework and targeting of known microbial processes [more...]
Aug 08, 2019
Nutrient-Hungry Peatland Microbes Reduce Carbon Loss Under Warmer Conditions
Enzyme production in peatlands reduces carbon lost to respiration under future high temperatures. [more...]
Aug 05, 2019
Amazon Forest Response to CO2 Fertilization Dependent on Plant Phosphorus Acquisition
AmazonFACE Model Intercomparison. The Science Plant growth is dependent on the availabi [more...]
Jul 29, 2019
A Slippery Slope: Soil Carbon Destabilization
Carbon gain or loss depends on the balance between competing biological, chemical, and physical reac [more...]
Jul 15, 2019
Field Evaluation of Gas Analyzers for Measuring Ecosystem Fluxes
How gas analyzer type and correction method impact measured fluxes. The Science A side- [more...]
List all highlights (possible long download time)