An Algorithm to Screen Cloud-Affected Data for Sky Radiometer Data Analysis
An Algorithm to Screen Cloud-Affected Data for Sky Radiometer Data Analysis
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DOI：
10.2151/jmsj.87.189
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发表时间：
2009-02
影响因子：
3.1
通讯作者：
P. Khatri;T. Takamura
中科院分区：
文献类型：
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作者：
P. Khatri;T. Takamura
由天空辐射计获得的气溶胶光学参数不仅对研究气溶胶对气候变化的影响具有重要意义，而且对验证卫星反演和数值模拟的结果也具有重要意义。然而，最大的挑战是从天空辐射计测量的数据中分离出受云影响的数据和无云数据。在这项研究中，我们提出了一种算法来分离这种云影响和云免费的数据。所提出的算法进行了全面的测试与观测数据。该算法包括三个测试：（i）测试与全球辐照度数据，（ii）光谱变异性测试，和（iii）统计分析测试。尽管全球辐照度数据的测试是最强大的测试，但我们的研究表明它有一些局限性，有时会导致一些晴朗的天空数据被检测为受云影响的数据。为了科普这个问题，提出了一种改进的光谱变异性算法。作为第二个测试，修改后的光谱变率算法被应用于从被检测为受第一个测试影响的云的数据中过滤晴空数据。最后，执行统计分析测试以从由第一测试和第二测试检测到的晴空数据中移除任何离群值（如果存在的话）。结果表明，我们提出的算法可以更有效地筛选云影响的数据相比，其他云筛选算法。应用该算法对日本千叶地区一年的观测资料进行筛选，得到500 nm光学厚度（Angstrom指数）冬、春、夏、秋四季平均值分别为0.17（0.142）、0.38（0.98）、0.53（0.121）、0.21（0.28）。根据季节的不同，初始季节平均光学厚度在500 nm处减少了0.07至0.16，平均埃指数增加了0.087至0.162，由于云屏蔽。本文还讨论了该算法在含尘大气中的应用。该算法可以应用于任何天空辐射计观测站点，只要全球辐照度数据可用。
Aerosol optical parameters obtained from sky radiometer instrument are important not only for studying aerosol effects on climate change, but also for validating several results obtained from satellite retrievals and numerical simulations. However, the greatest challenge is to separate cloud-affected and cloud free data from data measured by sky radiometer. In this study, we present an algorithm to separate such cloud-affected and cloud free data. The proposed algorithm is comprehensively tested with observational data. The algorithm consists of three tests: (i) test with global irradiance data, (ii) spectral variability test, and (iii) statistical analyses test. Though the test with the global irradiance data is the most powerful test, our study shows that it has some limitations, which can sometimes cause some clear sky data to be detected as cloud-affected data. In order to cope with this problem, a modified version of spectral variability algorithm is proposed. As the second test, the modified spectral variability algorithm is applied to filter clear sky data from data detected as cloud-affected by the first test. Finally, statistical analyses tests are performed to remove any outlier, if exists, from clear sky data detected by the first and second tests. It is shown that our proposed algorithm can screen cloud-affected data more effectively in comparison to other cloud screening algorithms. An application of this algorithm to screen observation data of one year collected in Chiba, Japan produces the seasonal means of optical thickness at 500 nm (Angstrom exponent) as ∼0.17(∼1.42), ∼0.38(∼0.98), ∼0.53(∼1.21), and ∼0.21(∼1.28) for winter, spring, summer and autumn seasons, respectively. Depending on the season, the initial seasonal mean optical thicknesses at 500 nm decrease by ∼0.07 to ∼0.16 and mean Angstrom exponents increase by ∼0.087 to ∼0.162 due to cloud screening. An application of this algorithm to dust-loaded atmospheres is also discussed. The proposed algorithm can be applied to any sky radiometer observation site as long as global irradiance data are available.