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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >PASSIVE MICROWAVE ALGORITHMS FOR SEA ICE CONCENTRATION - A COMPARISON OF TWO TECHNIQUES
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PASSIVE MICROWAVE ALGORITHMS FOR SEA ICE CONCENTRATION - A COMPARISON OF TWO TECHNIQUES

机译:用于海冰浓缩的被动微波算法-两种方法的比较。

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The most comprehensive large-scale characterization of the global sea ice cover so far has been provided by satellite passive microwave data. Accurate retrieval of ice concentrations from these data is important because of the sensitivity of surface flux (e.g., heat, salt, and water) calculations to small changes in the amount of open water (leads and polynyas) within the polar ice packs. Two algorithms that have been used for deriving ice concentrations from multichannel data are compared. One is the NASA Team algorithm and the other is the Bootstrap algorithm, both of which were developed at NASA's Goddard Space Flight Center. The two algorithms use different channel combinations, reference brightness temperatures, weather filters, and techniques. Analyses are made to evaluate the sensitivity of algorithm results to variations of emissivity and temperature with space and time. To assess the difference in the performance of the two algorithms, analyses were performed with data from both hemispheres and for all seasons. The results show only small differences in the central Arctic in winter but larger disagreements in the seasonal regions and in summer. In some areas in the Antarctic, the Bootstrap technique shows ice concentrations higher than those of the Team algorithm by as much as 25%; whereas, in other areas, it shows ice concentrations lower by as much as 30%. The differences in the results are caused by temperature effects, emissivity effects, and tie point differences. The Team and the Bootstrap results were compared with available Landsat, advanced very high resolution radiometer (AVHRR) and synthetic aperture radar (SAR) data. AVHRR, Landsat, and SAR data sets all yield higher concentrations than the passive microwave algorithms. Inconsistencies among results suggest the need for further validation studies. (C) Elsevier Science Inc., 1997. [References: 36]
机译:到目前为止,全球最广泛的海冰覆盖特征是卫星无源微波数据。由于表面通量(例如,热量,盐和水)计算对极地冰袋中的裸露水量(铅和polynyas)的微小变化非常敏感,因此从这些数据中准确获取冰浓度非常重要。比较了用于从多通道数据得出冰浓度的两种算法。一种是NASA团队算法,另一种是Bootstrap算法,这两种算法都是在NASA的戈达德太空飞行中心开发的。两种算法使用不同的通道组合,参考亮度温度,天气过滤器和技术。进行分析以评估算法结果对发射率和温度随时间和空间变化的敏感性。为了评估两种算法的性能差异,使用了来自两个半球以及所有季节的数据进行了分析。结果表明,冬季北极地区的差异很小,而季节性地区和夏季差异较大。在南极的某些地区,Bootstrap技术显示的冰浓度比Team算法的冰浓度高25%。而在其他地区,冰浓度降低了多达30%。结果的差异是由温度效应,发射率效应和连接点差异引起的。将该团队和Bootstrap的结果与可用的Landsat,先进的超高分辨率辐射计(AVHRR)和合成孔径雷达(SAR)数据进行了比较。与无源微波算法相比,AVHRR,Landsat和SAR数据集产生的浓度更高。结果之间的不一致表明需要进一步的验证研究。 (C)Elsevier Science Inc.,1997年。[参考:36]

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