MISC

査読有り
2019年12月

Incorporation of satellite-derived thin-ice data into a global OGCM simulation

CLIMATE DYNAMICS
  • Takahiro Toyoda
  • ,
  • Katsushi Iwamoto
  • ,
  • L. Shogo Urakawa
  • ,
  • Hiroyuki Tsujino
  • ,
  • Hideyuki Nakano
  • ,
  • Kei Sakamoto
  • ,
  • Goro Yamanaka
  • ,
  • Yoshiki Komuro
  • ,
  • Shigeto Nishino
  • ,
  • Jinro Ukita

53
11
開始ページ
7113
終了ページ
7130
記述言語
英語
掲載種別
DOI
10.1007/s00382-019-04979-8
出版者・発行元
SPRINGER

The presence of thin sea ice is indicative of active freezing conditions in the polar ocean. We propose a simple yet effective method to incorporate information of thin-ice category into coupled ocean-sea-ice model simulations. In our approach, the thin-ice distribution restricts thick-ice extent and constrains atmosphere-ocean heat exchange through the sea ice. Our model simulation with the incorporation of satellite-derived thin-ice data for the Arctic Ocean showed much improved representation of sea-ice and upper-ocean fields, including sea-ice thickness in the Canadian Archipelago and the region north of Greenland, mixed-layer depth over the Central Arctic, and surface-layer salinity over the open ocean. Enhanced sea-ice production by the thin-ice data constraint increased the total sea-ice volume of the Arctic Ocean by 5x103-10x103 km(3). Subsequent sea-ice melting was also enhanced, leading to the greater amplitude of the seasonal cycle by approximately 2x103 km(3) (15% of the baseline value from the experiment without the thin-ice data incorporation). Overall, our results demonstrate that the incorporation of satellite-derived information on thin sea ice has great potential for the improvement of coupled ocean-sea-ice simulations.

リンク情報
DOI
https://doi.org/10.1007/s00382-019-04979-8
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000494681900035&DestApp=WOS_CPL
ID情報
  • DOI : 10.1007/s00382-019-04979-8
  • ISSN : 0930-7575
  • eISSN : 1432-0894
  • Web of Science ID : WOS:000494681900035

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