Estimation of Thin-Ice Thickness and Discrimination of Ice Type From AMSR-E Passive Microwave Data

被引:31
|
作者
Nakata, Kazuki [1 ,2 ]
Ohshima, Kay, I [3 ,4 ]
Nihashi, Sohey [5 ]
机构
[1] Hokkaido Univ, Grad Sch Environm Sci, Sapporo, Hokkaido 0600810, Japan
[2] Remote Sensing Technol Ctr Japan, Res & Dev Dept, Tokyo 1050001, Japan
[3] Hokkaido Univ, Inst Low Temp Sci, Sapporo, Hokkaido 0600819, Japan
[4] Hokkaido Univ, Arctic Res Ctr, Sapporo, Hokkaido 0010021, Japan
[5] Tomakomai Coll, Dept Engn Innovat, Natl Inst Technol, Tomakomai 0591275, Japan
来源
关键词
Antarctic coastal polynya; frazil ice; passive microwave; thin-ice thickness; NOVA BAY POLYNYA; SEA-ICE; COASTAL-POLYNYA; MULTISENSOR SATELLITE; FRAZIL ICE; ROSS SEA; DYNAMICS; MODEL; SSM/I; VALIDATION;
D O I
10.1109/TGRS.2018.2853590
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Detection of thin-ice thickness with microwave radiometers, such as the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), is very effective for the estimation of sea-ice production, which causes dense water driving ocean thermohaline circulation. In previous thin-ice thickness algorithms, ice thickness is estimated by utilizing a negative correlation between ice thickness and polarization ratio (PR) of AMSR-E. However, in these thin-ice algorithms, the relationship has large dispersion. We consider that the problem is caused by not taking account of ice type. We classified thin-ice regions around Antarctica into two ice types: 1) active frazil, comprising frazil and open water and 2) thin solid ice, areas of the relatively uniform thin ice, using Moderate Resolution Imaging Spectroradiometer and Advanced Synthetic Aperture Radar data. For each ice type, we examined the relationship between the AMSR-E PR of 36 GHz and ice thickness, showing that the active frazil type has a much smaller thickness than the thin solid ice type for the same PR. The two ice types can be discriminated by a simple linear discriminant method in the plane of the PR and gradient ratio of AMSR-E, with the misclassification of 3%. From these results, we propose a new thin-ice algorithm. The two ice types are classified by the linear discriminant method, and then empirical equations are used to obtain the ice thickness for each ice type. This algorithm significantly improves the accuracy of the thin-ice thickness.
引用
收藏
页码:263 / 276
页数:14
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