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Estimation of daily cloud-free, snow-covered areas from MODIS based on variational interpolation

机译：基于变分插值的MODIS估计每日无云，大雪覆盖的区域

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摘要

NASA's MODIS global snow-covered area (SCA) products are one of the mission's major objectives that frequently contain cloud hindrances, which degrade their practical usability. Many techniques have been developed to mitigate the problem but with no assurance of eliminating all of the clouds. An image-processing algorithm with its kernel based on the variational interpolation theorem is developed to automatically obtain cloud-free dynamic SCA maps from MODIS. Two cases consisting of "accumulation" and "melting" phases are processed and validated using observations at 121 ground-snow sensors over the Sierra Nevada Mountains in California. The results show that the algorithm cleared all the cloud hindrance over the period of study. In terms of accuracy, the retrieved cloud-free snow cover for the accumulation case had an average omission error of around 22.5% and average commission error of around 2.1%, as compared to all available ground sensors. These high percentages of errors basically came from the input data of Terra and Aqua, which had omission errors of 14.3% and 20.2% (and the commission errors of ～0.5%), respectively. For the melting case, when there were fewer clouds and hence more sensors available, the errors of omission and commission between the algorithm and direct observations from Terra and Aqua were close to each other (5.7-5.0% for omission and 0% for commission).
机译：NASA的MODIS全球冰雪覆盖地区（SCA）产品是任务的主要目标之一，该目标经常包含云障碍，这会降低其实际可用性。已经开发了许多技术来缓解该问题，但不能保证消除所有云。提出了一种基于变分插值定理的图像处理算法，其内核可以从MODIS自动获取无云动态SCA图。使用在加利福尼亚内华达山脉上空的121个地面雪传感器进行的观测，处理和验证了由“累积”和“融化”两个阶段组成的两种情况。结果表明，该算法消除了研究期间的所有云障碍。在准确性方面，与所有可用的地面传感器相比，针对积聚案例检索到的无云积雪平均遗漏误差约为22.5％，平均佣金误差约为2.1％。这些高百分比的误差基本上来自Terra和Aqua的输入数据，它们的遗漏误差分别为14.3％和20.2％（佣金误差为〜0.5％）。对于融化情况，当云量减少，因此可用传感器更多时，算法与Terra和Aqua的直接观测值之间的遗漏和委托误差彼此接近（遗漏为5.7-5.0％，委托为0％） 。

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  • 来源
    《Water resources research》 |2012年第9期|W09523.1-W09523.9|共9页
  • 作者

    Qing Xia; Xiaogang Gao; Wei Chu; Soroosh Sorooshian;

  • 作者单位

    Department of Civil and Environmental Engineering, University of California, E/4130 Engineering Gateway, Irvine,CA 92697-2175, USA;

    Department of Civil and Environmental Engineering, University of California, Irvine, California, USA;

    Department of Civil and Environmental Engineering, University of California, Irvine, California, USA;

    Department of Civil and Environmental Engineering, University of California, Irvine, California, USA;

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