摘要
被动微波辐射计AMSR-E在89GHz频段的空间分辨率几乎是其它低频段的2倍。到目前为止,已经有成熟的算法采用AMSR-E 89GHz频段的数据来反演整体海冰的密集度,而本文根据89GHz频段亮温数据针对一年冰、多年冰以及无冰水面的不同特性,提出了一种反演多年冰密集度的方法(AC)。计算了2007年北极的整体海冰和多年冰密集度,并与NASA TEAM算法(NT)的结果作了比较。对于整体海冰密集度,两种算法反演的结果基本一致。从日平均上来看,AC算法得到的整体海冰覆盖面积只比NT算法多25万km2。但是对于多年冰的反演结果,AC算法得到的结果比NT的结果要多出146万km2,冬季差别尤其大。造成这种差别的原因可能是AC算法对于北极表面气温的变化比较敏感。另外,AC算法计算得到2007年最大海冰覆盖面积为1400万km2,最小海冰覆盖面积为400万km2,这与其它研究结果一致。
The 89 GHz channels of the passive microwave sensor AMSR-E have more than twice the horizontal resolution of its other lower frequency channels. The retrieval of total ice concentration based on the 89 GHz channels was well established, while retrieval of the muhiyear ice concentration was little explored until now. The brightness temperatures of the AMSR-E 89 GHz channels are used to characterize their response to multiyear ice, first-year ice and open water. A simple algorithm, called Algorithm Currently ( AC), has been developed and used to retrieve the total ice and multiyear ice concentrations in the Arctic in 2007. The results are compared with those from the NASA TEAM algorithm (NT). For the total ice cover and concentration, the annual variations of the ice covered areas found by the two algorithms are in good agreement. On the average, the AC produces merely 0.25 million km^2 more ice cover compared with results of the NT. For multiyear ice area and concentration, however, the AC seems to overestimate considerably ( as much as 1.46 million km^2 in area) against results from the NT, particularly during the winter season. One possible reason would be that the AC is more sensitive to the surface temperature in the Arctic. On the other hand, the maximum ( 14 million km^2) and minimum (4 million km^2) ice cover extent in 2007 are obtained quite accurately applying our algorithm. Those results are consistent with other studies.
出处
《极地研究》
CAS
CSCD
北大核心
2009年第3期186-196,共11页
Chinese Journal of Polar Research
基金
欧盟DAMOCLES项目第6个框架计划(018509-DAMOCLES)资助
关键词
AMSR-E
北极
多年冰
亮温
遥感
AMSR-E, Arctic, multiyear ice, brightness temperature, microwave remote sensing.