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Investigation of GOSAT TANSO-CAI Cloud Screening Ability throughan Intersatellite Comparison

机译:通过卫星间比较研究GOSAT TANSO-CAI云筛查能力

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In this work, the Greenhouse Gases Observing Satellite (GOSAT) Thermal and Near-infrared Sensor for Carbon Observation-Cloud and Aerosol Imager (TANSO-CAI) cloud screening results, which are necessary for the retrieval of carbon dioxide (C0_2) and methane (CH_4) gas amounts from GOSATTANSO-Fourier Transform Spectrometer (FTS) observations, are compared with results from Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) in four seasons. A large number of pixels, acquired from both satelliteswith nearly coincident locations and times, are extracted for statistical comparisons. The same cloud screening algorithm was applied to both satellite datasets to focus on the performance of the individual satellite sensors, without concern for differences in algorithms. The comparisons suggest that CAI is capable of discriminating between clear and cloudy areas over water without sun glint and also may be capable of identifying thin cirrus clouds, which are generally difficult to detect without thermal infrared or near-infrared bands. On the other hand, cloud screening over land by CAI resulted in greater cloudy discrimination than that by MODIS, whereas detection of thin cirrus clouds tended to be more difficult over land than water, resulting in incorrect identification of thin cirrus as clear. The amount of missed thin cirrus had a seasonal variation, with the maximum occurring in summer. The cloudy tendency of CAI over half vegetation is caused by lack of an effective threshold test that can beapplied to MODIS. The statistical results of the comparison clarified the important points to consider when using the results of CAI cloud screening.
机译:在这项工作中,温室气体观测卫星(GOSAT)热和近红外传感器用于碳观测云和气溶胶成像仪(TANSO-CAI)的云筛查结果,这对于检索二氧化碳(C0_2)和甲烷(将GOSATTANSO-Fourier变换光谱仪(FTS)观测得到的CH_4)气体量与Aqua /中分辨率成像光谱仪(MODIS)在四个季节中得到的结果进行了比较。从两颗卫星获取的具有几乎一致的位置和时间的大量像素被提取出来用于统计比较。将相同的云筛选算法应用于两个卫星数据集,以关注各个卫星传感器的性能,而无需担心算法的差异。比较结果表明,CAI能够在水域的清澈和多云区域之间进行区分,而不会出现阳光闪烁,并且还能够识别薄的卷云,而如果没有热红外或近红外波段,通常很难检测到它们。另一方面,CAI对陆地进行的云筛查比MODIS进行的云判别更大,而在陆地上比在水上探测薄卷云的难度往往更大,从而导致将薄卷云识别为清晰的错误。稀疏卷云的丢失量具有季节性变化,最大值发生在夏季。 CAI在一半植被上的浑浊趋势是由于缺少可应用于MODIS的有效阈值测试引起的。比较的统计结果阐明了使用CAI云筛查结果时要考虑的重要点。

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