期刊文献+

AMSR-E辐射计反演南大洋实时海面气温 被引量:3

Real-time sea surface air temperature retrieval over Southern Ocean using AMSR-E data
原文传递
导出
摘要 利用中国南极第24次至第26次(2008年—2010年)考察获取的实测数据和AMSR-E辐射计亮温资料开展南大洋实时海面气温的反演研究,分析了AMSR-E的各通道亮温与海面气温的相关性,未发现与海面气温相关性较强的观测通道,相关性最高的是23.8GHz水平通道,相关系数为0.38。将实测数据与亮温资料进行数据匹配,得到有效的建模数据集,然后利用多元回归和神经网络两种方法建立海面气温实时反演模型。基于全通道多元回归建立了高纬、低纬海域AMSR-E亮温的反演模型,对反演结果利用实测数据进行验证,高纬海域反演的结果均方根差为0.96℃,相关系数为0.93;低纬海域反演结果均差差为1.29℃,相关性系数0.96。基于BackPropagation(BP)神经网络反演模型的反演结果均方根差为1.26℃,相关系数为0.98。 The AMSR-E satellite data and in-situ data were applied to retrieve sea surface air temperature (Ta) over the Southern Ocean. The in-situ data were obtained from the 24th —26th Chinese Antarctic Expeditions during 2008—2010. First,Ta was used to analyze the relativity with the bright temperature (Tb) from the twelve channels of AMSR-E, and no high relativity was found between Ta and Tb from any of the channels. The highest relativity was 0.38 (with 23.8 GHz). The dataset for the modeling was obtained by using in-situ data to match up with Tb, and two methods were applied to build the retrieval model. In multi-parameters regression method, the Tbs from 12 channels were used to the model and the region was divided into two parts according to the latitude of 50°S. The retrieval results were compared with the in-situ data. The Root Mean Square Error (RMS) and relativity of high latitude zone were 0.96℃and 0.93, respectively. And those of low latitude zone were 1.29 ℃ and 0.96, respectively. Artificial neural network (ANN) method was applied to retrieve Ta.The RMS and relativity were 1.26 ℃ and 0.98, respectively. The air-sea interaction over the Southern Ocean is so strong and unstable that it increases the retrieval difficulty and affects the accuracy of the results.
出处 《遥感学报》 EI CSCD 北大核心 2013年第A02期471-475,467,共9页 NATIONAL REMOTE SENSING BULLETIN
基金 国家高技术研究发展计划(863计划)(编号:2008AA121701 2007AA092202)~~
关键词 AMSR-E 海面气温 神经网络 多元回归 AMSR-E,sea surface air temperature,ANN,multi-parameters regression method
  • 相关文献

同被引文献57

  • 1龚迎春.试论《南极条约》体系确立的环境保护规范对各国的效力[J].外交评论(外交学院学报),1990,12(3):57-62. 被引量:4
  • 2齐述华,王军邦,张庆员,骆成凤,郑林.利用MOD IS遥感影像获取近地层气温的方法研究[J].遥感学报,2005,9(5):570-575. 被引量:45
  • 3Minnett P J, Barton I J. Remote sensing of the Earth´s surface temperature:Radiometric temperature measurements: II Applications[A]. In: Zhang Z M, Tsai B K, Machin G(eds.). Experimental Methods in the Physical Sciences, Vol 43[M]. Salt Lake City: Academic Press, 2010.
  • 4Merchant C J, Matthiesen S, Rayner N A, et al . The surface temperatures of the earth: steps towards integrated understanding of variability and change[J]. Geoscientific Instrumentation Methods and Data Systems, 2013,3:305-345.
  • 5Walton C C, Pichel W G, Sapper J F. The development and operational application of nonlinear algorithms for the measurement of sea surface temperatures with the NOAA polar-orbiting environmental satellites[J]. Journal of Geophysical Research, 1998,103(C12):27999-28012.
  • 6Merchant C J, Harris A R, Maturi E, et al . Sea surface temperature estimation from the Geostationary Operational Environmental Satellite-12 (GOES-12)[J]. Journal of Atmospheric and Oceanic Technology, 2009,26:570-581.
  • 7Karagali I, Hyer J L, Hasager C B. SST diurnal variability in the North Sea and the Baltic Sea[J]. Remote Sensing of Environment, 2012,121:159-170.
  • 8Chelton D B, Wentz F J. Global microwave satellite observations of sea surface temperature for numerical weather prediction and climate research[J]. Bulletin of the American Meteorological Society, 2005,86:1097-1115.
  • 9Hosoda K. A review of satellite-based microwave observations of sea surface temperatures[J]. Journal of Oceanography, 2010,66:430-473.
  • 10Bloszies C, Forman S L. Potential relation between equatorial sea surfacetemperaturesand historic water level variability for LakeTurkana, Kenya[J]. Journal of Hydrology, 2015,520:489-501.

引证文献3

二级引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部