4.7 Article

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

Journal

JOURNAL OF CLIMATE
Volume 29, Issue 5, Pages 1689-1716

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-15-0429.1

Keywords

Climatology; Models and modeling; Model evaluation/performance; Climate models; Southern Ocean; Geographic location/entity; Physical Meteorology and Climatology; Antarctica

Funding

  1. National Science Foundation (NSF) [1235231, 1048899]
  2. NSF [1043580]
  3. U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison
  4. Directorate For Geosciences
  5. Div Atmospheric & Geospace Sciences [1048899] Funding Source: National Science Foundation
  6. Office of Polar Programs (OPP)
  7. Directorate For Geosciences [1043580] Funding Source: National Science Foundation

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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 degrees-60 degrees 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.

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