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First-year sea ice spring melt transitions in the Canadian Arctic Archipelago from time-series synthetic aperture radar data, 1992-2002

机译:根据时间序列合成孔径雷达数据,1992-2002年,加拿大北极群岛的第一年海冰春季融化转变

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This paper synthesizes 10-years' worth of interannual time-series space-borne ERS-1 and RADARSAT-1 synthetic aperture radar (SAR) data collected coincident with daily measurement of snow-covered, land-fast first-year sea ice (FYI) geophysical and surface radiation data collected from the Seasonal Sea Ice Monitoring and Modeling Site, Collaborative-Interdisciplinary Cryospheric Experiment and 1998 North Water Polynya study over the period 1992 to 2002. The objectives are to investigate the seasonal co-relationship of the SAR time-series dataset with selected surface mass (bulk snow thickness) and climate state variables (surface temperature and albedo) measured in situ for the purpose of measuring the interannual variability of sea ice spring melt transitions and validating a time-series SAR methodology for sea ice surface mass and climate state parameter estimation. We begin with a review of the salient processes required for our interpretation of time-series microwave backscatter from land-fast FYI. Our results suggest that time-series SAR data can reliably measure the timing and duration of surface albedo transitions at daily to weekly time-scales and at a spatial scales that are on the order of hundreds of metres. Snow thickness on FYI immediately prior to melt onset explains a statistically significant portion of the variability in timing of SAR-detected melt onset to pond onset for SAR time-series that are made up of more than 25 images. Our results also show that the funicular regime of snowmelt, resolved in time-series SAR data at a temporal resolution of approximately 2.5 images per week, is not detectable for snow covers less than 25 cm in thickness.
机译:本文综合了10年的年际时间序列星载ERS-1和RADARSAT-1合成孔径雷达(SAR)数据,这些数据与每天对积雪的陆地快速第一年海冰(FYI)的每日测量相吻合。 )从1992年至2002年期间从季节性海冰监测和建模站点,合作跨学科冰冻圈实验和1998年北水波利尼亚研究中收集的地球物理和地面辐射数据。目的是调查SAR时间的季节性相互关系-系列数据集,具有选定的表面质量(大雪厚度)和气候状态变量(地表温度和反照率),是就地测量的,目的是测量海冰弹簧融化过渡的年际变化并验证海冰表面的时间序列SAR方法质量和气候状态参数估计。首先,我们回顾了解释陆上FYI的时间序列微波反向散射所需的显着过程。我们的结果表明,时间序列SAR数据可以可靠地测量每天至每周的时间尺度和数百米左右的空间尺度上地表反照率跃迁的时间和持续时间。在FYI融雪开始之前的积雪厚度解释了SAR时间序列中由SAR检测到的融雪开始到池塘发作的时间变化的统计学显着部分,该序列由25个以上的图像组成。我们的结果还表明,在时间序列SAR数据中以每周约2.5张图像的时间分辨率解决融雪的缆索缆车状态,对于厚度小于25 cm的积雪无法检测到。

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