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Antarctic and Southern Ocean Surface Temperatures in CMIP5 Models in the Context of the Surface Energy Budget

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  • 1 Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, Colorado
  • 2 Department of Earth and Environmental Science, New Mexico Institute of Mining and Technology, Socorro, New Mexico
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Abstract

This study examines the biases, intermodel spread, and intermodel range of surface air temperature (SAT) across the Antarctic ice sheet and Southern Ocean in 26 structurally different climate models. Over the ocean (40°–60°S), an ensemble-mean warm bias peaks in late austral summer concurrently with the peak in the intermodel range of SAT. This warm bias lags a spring–summer positive bias in net surface radiation due to weak shortwave cloud forcing and is gradually reduced during autumn and winter. For the ice sheet, inconsistencies among reanalyses and observational datasets give low confidence in the ensemble-mean bias of SAT, but a small summer warm bias is suggested in comparison with nonreanalysis SAT data. The ensemble mean hides a large intermodel range of SAT, which peaks during the summer insolation maximum. In summer on the ice sheet, the SAT intermodel spread is largely associated with the surface albedo. In winter, models universally exhibit a too-strong deficit in net surface radiation related to the downward longwave radiation, implying that the lower atmosphere is too stable. This radiation deficit is balanced by the transfer of sensible heat toward the surface (which largely explains the intermodel spread in SAT) and by a subsurface heat flux. The winter bias in downward longwave radiation is due to the longwave cloud radiative effect, which the ensemble mean underestimates by a factor of 2. The implications of these results for improving climate simulations over Antarctica and the Southern Ocean are discussed.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-15-0429.s1.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: David P. Schneider, Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Box 3000, Boulder, CO 80307-3000. E-mail: dschneid@ucar.edu

Abstract

This study examines the biases, intermodel spread, and intermodel range of surface air temperature (SAT) across the Antarctic ice sheet and Southern Ocean in 26 structurally different climate models. Over the ocean (40°–60°S), an ensemble-mean warm bias peaks in late austral summer concurrently with the peak in the intermodel range of SAT. This warm bias lags a spring–summer positive bias in net surface radiation due to weak shortwave cloud forcing and is gradually reduced during autumn and winter. For the ice sheet, inconsistencies among reanalyses and observational datasets give low confidence in the ensemble-mean bias of SAT, but a small summer warm bias is suggested in comparison with nonreanalysis SAT data. The ensemble mean hides a large intermodel range of SAT, which peaks during the summer insolation maximum. In summer on the ice sheet, the SAT intermodel spread is largely associated with the surface albedo. In winter, models universally exhibit a too-strong deficit in net surface radiation related to the downward longwave radiation, implying that the lower atmosphere is too stable. This radiation deficit is balanced by the transfer of sensible heat toward the surface (which largely explains the intermodel spread in SAT) and by a subsurface heat flux. The winter bias in downward longwave radiation is due to the longwave cloud radiative effect, which the ensemble mean underestimates by a factor of 2. The implications of these results for improving climate simulations over Antarctica and the Southern Ocean are discussed.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-15-0429.s1.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: David P. Schneider, Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Box 3000, Boulder, CO 80307-3000. E-mail: dschneid@ucar.edu

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