論文

査読有り
2021年4月

Improved SSM/I Thin Ice Algorithm with Ice Type Discrimination in Coastal Polynyas

Journal of Atmospheric and Oceanic Technology
  • Haruhiko Kashiwase
  • ,
  • Kay I. Ohshima
  • ,
  • Kazuki Nakata
  • ,
  • Takeshi Tamura

38
4
開始ページ
823
終了ページ
835
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1175/jtech-d-20-0145.1
出版者・発行元
American Meteorological Society

<title>Abstract</title>Long-term quantification of sea ice production in coastal polynyas (thin sea ice areas) is an important issue to understand the global overturning circulation and its changes. The Special Sensor Microwave Imager (SSM/I), which has nearly 30 years of observation, is a powerful tool for that purpose owing to its ability to detect thin ice areas. However, previous SSM/I thin ice thickness algorithms differ between regions, probably due to the difference in dominant type of thin sea ice in each region. In this study, we developed an SSM/I thin ice thickness algorithm that accounts for three types of thin sea ice (active frazil, thin solid ice, and a mixture of two types), using the polarization and gradient ratios. The algorithm is based on comparison with the ice thickness derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) for 22 polynya events off the Ross Ice Shelf, off Cape Darnley, and off the Ronne Ice Shelf in the Southern Ocean. The algorithm can properly discriminate the ice type in coastal polynyas and estimate the thickness of thin sea ice (≤20 cm) with an error range of less than 6 cm. We also confirmed that the algorithm can be applied to other passive microwave radiometers with higher spatial resolution to obtain more accurate and detailed distributions of ice type and thickness. The validation of this algorithm in the Arctic Ocean suggests its applicability to the global oceans.

リンク情報
DOI
https://doi.org/10.1175/jtech-d-20-0145.1
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000644157500009&DestApp=WOS_CPL
URL
https://journals.ametsoc.org/view/journals/atot/38/4/JTECH-D-20-0145.1.xml
URL
https://journals.ametsoc.org/downloadpdf/journals/atot/38/4/JTECH-D-20-0145.1.xml
ID情報
  • DOI : 10.1175/jtech-d-20-0145.1
  • ISSN : 0739-0572
  • eISSN : 1520-0426
  • Web of Science ID : WOS:000644157500009

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