首页> 外文期刊>海洋学报(英文版) >A study of multiyear ice concentration retrieval algorithms using AMSR-E data
【24h】

A study of multiyear ice concentration retrieval algorithms using AMSR-E data

机译:基于AMSR-E数据的多年冰浓度反演算法研究

获取原文
获取原文并翻译 | 示例
       

摘要

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.
机译:近年来,北极海冰面积(SIA)和海冰范围(SIE)的快速下降,特别是多年期(MY)冰的下降,已对气候变化产生了重大影响。要准确了解MY冰浓度,要准确了解其不断变化,这非常重要且具有挑战性。系统评估了三种MY冰浓度反演算法。通过这些算法得出的总冰浓度相似,而检索到的MY海冰浓度彼此不同。从NASA TEAM算法得出的MY SIA相对稳定。其他两种算法造成MY SIA的季节性波动,尤其是在秋季和冬季。在本文中,我们提出了一种冰浓度检索算法,该算法通过添加使用AMSR-E 6.9 GHz亮度温度数据和使用89.0 GHz数据的海冰浓度来开发NASA TEAM算法。与参考MY SIA和参考MY Ice的参考MY SIA的比较表明,从本研究算法得出的MY SIA的均值差和均方根(rms)差在1月至3月为0.65×106 km2和0.69×106 km2。 9月至12月分别为0.06×106 km2和0.14×106 km2。与科罗拉多大学提供的每周冰河年龄数据得到的MY SIE的比较表明,平均差和均方根差分别为0.69×106 km2和0.84×106 km2。与来自冰河年龄数据的参考MY ice和MY SIE相比,本研究中提出的已开发算法的差异小于Wang,Lomax和NASA TEAM算法。

著录项

  • 来源
    《海洋学报(英文版)》 |2015年第9期|102-109|共8页
  • 作者

    HAO Guanghua; SU Jie;

  • 作者单位

    Key Laboratory of Physical 0ceanography, 0cean University of China, Qingdao 266100, China;

    Key Laboratory of Physical 0ceanography, 0cean University of China, Qingdao 266100, China;

  • 收录信息 中国科学引文数据库(CSCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号