Impact of downward longwave radiative deficits on Antarctic sea-ice extent predictability during the sea ice growth period

Ivana Cerovecki, Rui Sun, David H Bromwich, Xun Zou, Matthew R Mazloff, Sheng-Hung Wang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Forecasting Antarctic atmospheric, oceanic, and sea ice conditions on subseasonal to seasonal scales remains a major challenge. During both the freezing and melting seasons current operational ensemble forecasting systems show a systematic overestimation of the Antarctic sea-ice edge location. The skill of sea ice cover prediction is closely related to the accuracy of cloud representation in models, as the two are strongly coupled by cloud radiative forcing. In particular, surface downward longwave radiation (DLW) deficits appear to be a common shortcoming in atmospheric models over the Southern Ocean. For example, a recent comparison of ERA5 global reanalysis with the observations from McMurdo Station revealed a year-round deficit in DLW of approximately 50 Wm-2 in marine air masses due to model shortages in supercooled cloud liquid water. A comparison with the surface DLW radiation observations from the Ocean Observatories Initiative (OOI) mooring in the South Pacific at 54.08°S, 89.67°W, for the time period Jan 2016 - Nov 2018, confirms approximately 20 Wm-2 deficit in DLW in ERA5 well north of the sea-ice edge. Using a regional ocean model, we show that when DLW is artificially increased by 50 Wm-2 in the simulation driven by ERA5 atmospheric forcing, the predicted sea ice growth agrees much better with the observations. A wide variety of sensitivity tests show that the anomalously large, predicted sea-ice extent is not due to limitations in the ocean model and that by implication the cause resides with the atmospheric forcing.
Original languageEnglish (US)
JournalEnvironmental Research Letters
DOIs
StatePublished - Jun 30 2022
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-07-06
Acknowledged KAUST grant number(s): OSR-2016-RPP-3268.02
Acknowledgements: IC was supported by NASA grant 80NSSC19K1115. DHB, XZ, and SHW were supported by NSF grant 1823135. R.S. was supported by KAUST (King Abdullah University of Science and Technology) grant OSR-2016-RPP-3268.02. M. R. Mazloff acknowledges support from NASA Grants 80NSSC20K1076 and 80NSSC22K0387, and NSF Grants OCE-1924388, PLR-1425989, OPP-2149501, and OPP-1936222. We also appreciate the computational resources on supercomputer Shaheen II for implementing and testing the coupled model. Contribution number C-1618 of Byrd Polar and Climate Research Center. We thank the two anonymous reviewers for their constructive comments.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

ASJC Scopus subject areas

  • General Environmental Science
  • Public Health, Environmental and Occupational Health
  • Renewable Energy, Sustainability and the Environment

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