Retracted: Time‐Dependent Cryospheric Longwave Surface Emissivity Feedback in the Community Earth System Model

• Published in: Journal of Geophysical Research: Atmospheres
• Main Authors: Kuo, Chaincy, Feldman, Daniel R, Huang, Xianglei, Flanner, Mark, Yang, Ping, Chen, Xiuhong
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: eScholarship, University of California 2018
• Subjects: Earth Sciences; Oceanography; Atmospheric Sciences; Climate Action; climate feedback; longwave; emissivity; temporal; radiative kernel; Physical Geography and Environmental Geoscience; Climate change science; albedo; Arctic Ocean; Climate change
• Online Access: https://escholarship.org/uc/item/8ps974q7; https://escholarship.org/content/qt8ps974q7/qt8ps974q7.pdf; https://doi.org/10.1002/2017jd027595

Frozen and unfrozen surfaces exhibit different longwave surface emissivities with different spectral characteristics, and outgoing longwave radiation and cooling rates are reduced for unfrozen scenes relative to frozen ones. Here physically realistic modeling of spectrally resolved surface emissivity throughout the coupled model components of the Community Earth System Model (CESM) is advanced, and implications for model high-latitude biases and feedbacks are evaluated. It is shown that despite a surface emissivity feedback amplitude that is, at most, a few percent of the surface albedo feedback amplitude, the inclusion of realistic, harmonized longwave, spectrally resolved emissivity information in CESM1.2.2 reduces wintertime Arctic surface temperature biases from −7.2 ± 0.9 K to −1.1 ± 1.2 K, relative to observations. The bias reduction is most pronounced in the Arctic Ocean, a region for which Coupled Model Intercomparison Project version 5 (CMIP5) models exhibit the largest mean wintertime cold bias, suggesting that persistent polar temperature biases can be lessened by including this physically based process across model components. The ice emissivity feedback of CESM1.2.2 is evaluated under a warming scenario with a kernel-based approach, and it is found that emissivity radiative kernels exhibit water vapor and cloud cover dependence, thereby varying spatially and decreasing in magnitude over the course of the scenario from secular changes in atmospheric thermodynamics and cloud patterns. Accounting for the temporally varying radiative responses can yield diagnosed feedbacks that differ in sign from those obtained from conventional climatological feedback analysis methods.