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Development of a synergetic sea ice retrieval method for the ERS-1 AMI wind scatterometer and SSM/I radiometer

机译:ERS-1 AMI风散射仪和SSM / I辐射仪协同海冰检索方法的开发

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Sea ice retrievals from the standard passive microwave NASA team algorithm for the Special Sensor Microwave/Imager (SSM/I) are compared to retrievals from a new ERS-1 Active Microwave Instrument (AMI) wind scatterometer sea ice retrieval algorithm. The main objective of the comparison is to develop a synergetic algorithm, with the combined advantages of both of the individual algorithms. The scatterometer algorithm is validated in reference to the SSM/I NASA team algorithm, and a high accuracy of 98-99% is obtained when a NASA team pixel is determined as ice covered when the concentration is 85% or higher. This rather high concentration threshold eliminates most mixed pixels from being treated as ice covered, as many of these mixed pixel signatures are in fact caused by atmospheric effects. It is evident from the results that the NASA team weather correction for SSM/I sea ice retrievals works well over ice-free ocean surfaces, although it cannot he applied over mixed pixels or ice. The scatterometer algorithm presented, however, does not appear to need a weather correction. Therefore, especially mixed pixel estimates, e.g., around ice edges or polynyas, could be enhanced by the use of both active (ERS-1 AMI wind scatterometer) and passive (SSM/I) microwaves. In addition, the results show that late summer ice type classification by the scatterometer algorithm is more reliable than the present SSM/I NASA team classification. This is due to the scatterometer classification procedure, which adapts to the ice season considered. Based on the results obtained, a synergetic algorithm for the ERS-1 AMI wind scatterometer and the SSM/I is introduced.
机译:将特殊传感器微波/成像器(SSM / I)的标准无源微波NASA团队算法中的海冰检索与新ERS-1有源微波仪器(AMI)风散射仪海冰检索算法中的检索进行比较。比较的主要目的是开发一种协同算法,兼具两种算法的优点。参照SSM / I NASA团队算法对散射仪算法进行了验证,当浓度为85%或更高时,将NASA团队像素确定为被冰覆盖时,可以获得98-99%的高精度。这个相当高的浓度阈值消除了大多数混合像素被视为冰覆盖的情况,因为这些混合像素签名中的许多实际上是由大气效应引起的。从结果中可以明显看出,NASA小组针对SSM / I海冰的天气校正在无冰的海洋表面上效果很好,尽管它不能应用于混合像素或冰上。但是,提出的散射仪算法似乎不需要天气校正。因此,特别是混合像素的估计,例如在冰边缘或多边形附近,可以通过使用有源(ERS-1 AMI风散射仪)和无源(SSM / I)微波来增强。此外,结果表明,通过散射仪算法进行的夏末冰类型分类比当前的SSM / I NASA团队分类更可靠。这归因于散射仪分类程序,该程序适用于所考虑的冰季。根据获得的结果,介绍了ERS-1 AMI风散射仪和SSM / I的协同算法。

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