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HAO Guanghua,SU Jie. 2015. A study of multiyear ice concentration retrieval algorithms using AMSR-E data. Acta Oceanologica Sinica, 34(9):102-109
A study of multiyear ice concentration retrieval algorithms using AMSR-E data
基于AMSR-E数据的多年冰密集度反演算法研究
Received:September 19, 2014  Revised:March 23, 2015
DOI:10.1007/s13131-015-0656-1
Key words:multiyear ice concentration  retrieval algorithms  AMSR-E data
中文关键词:  多年冰密集度  反演算法  AMSR-E数据
基金项目:
Author NameAffiliationE-mail
HAO Guanghua Key Laboratory of Physical Oceanography, Ocean University of China, Qingdao 266100, China  
SU Jie Key Laboratory of Physical Oceanography, Ocean University of China, Qingdao 266100, China sujie@ouc.edu.cn 
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Abstract:
      In recent years, the rapid decline of Arctic sea ice area (SIA) and sea ice extent (SIE), especially for the multiyear (MY) ice, has led to significant effect on climate change. The accurate retrieval of MY ice concentration retrieval is very important and challenging to understand the ongoing changes. Three MY ice concentration retrieval algorithms were systematically evaluated. A similar total ice concentration was yielded by these algorithms, while the retrieved MY sea ice concentrations differs from each other. The MY SIA derived from NASA TEAM algorithm is relatively stable. Other two algorithms created seasonal fluctuations of MY SIA, particularly in autumn and winter. In this paper, we proposed an ice concentration retrieval algorithm, which developed the NASA TEAM algorithm by adding to use AMSR-E 6.9 GHz brightness temperature data and sea ice concentration using 89.0 GHz data. Comparison with the reference MY SIA from reference MY ice, indicates that the mean difference and root mean square (rms) difference of MY SIA derived from the algorithm of this study are 0.65×106 km2 and 0.69×106 km2 during January to March, -0.06×106 km2 and 0.14×106 km2 during September to December respectively. Comparison with MY SIE obtained from weekly ice age data provided by University of Colorado show that, the mean difference and rms difference are 0.69×106 km2 and 0.84×106 km2, respectively. The developed algorithm proposed in this study has smaller difference compared with the reference MY ice and MY SIE from ice age data than the Wang's, Lomax' and NASA TEAM algorithms.
中文摘要:
      近年来,北极多年冰的面积和范围快速减少,由此产生的气候效应具有重要意义,因而北极多年冰的反演的精度至关重要。本文较系统地总结分析了前人使用微波数据反演多年冰的3种算法,这些算法都能够很好的反演北极总的海冰密集度,但是对于多年冰的反演有较大的差异,相比于Wang和Lomax算法得到的多年冰面积在秋季和冬季过多而且变化明显,NASA TEAM算法得到的多年冰面积要稳定。本文在NASA TEAM算法的基础上改进了多年冰反演算法,同本文定义的参考多年冰面积相比,1-3月平均差异和均方根差异分别为0.65×106km2和0.69×106km2,9-12月平均差异和均方根差异分别为-0.06×106km2和0.14×106km2,同周平均的冰龄数据得到的海冰范围相比较,平均差异和均方根差异分别为0.69×106km2和0.84×106km2,在四种算法中,本文算法的差异最小。
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