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首页> 外文期刊>Atmospheric Measurement Techniques >Use of spectral cloud emissivities and their related uncertainties to infer ice cloud boundaries: methodology and assessment using CALIPSO cloud products
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Use of spectral cloud emissivities and their related uncertainties to infer ice cloud boundaries: methodology and assessment using CALIPSO cloud products

机译:使用光谱云发射率及其相关的不确定性来推断冰云边界:使用Calipso云产品的方法和评估

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摘要

Satellite-imager-based operational cloud property retrievals generally assume that a cloudy pixel can be treated as being plane-parallel with horizontally homogeneous properties. This assumption can lead to high uncertainties in cloud heights, particularly for the case of optically thin, but geometrically thick, clouds composed of ice particles. This study demonstrates that ice cloud emissivity uncertainties can be used to provide a reasonable range of ice cloud layer boundaries, i.e., the minimum to maximum heights. Here ice cloud emissivity uncertainties are obtained for three IR channels centered at 11, 12, and 13.3 mu m. The range of cloud emissivities is used to infer a range of ice cloud temperature and heights, rather than a single value per pixel as provided by operational cloud retrievals. Our methodology is tested using MODIS observations over the western North Pacific Ocean during August 2015. We estimate minimum-maximum heights for three cloud regimes, i.e., single-layered optically thin ice clouds, single-layered optically thick ice clouds, and multilayered clouds. Our results are assessed through comparison with CALIOP version 4 cloud products for a total of 11873 pixels. The cloud boundary heights for single-layered optically thin clouds show good agreement with those from CALIOP; biases for maximum (minimum) heights versus the cloud-top (base) heights of CALIOP are 0.13 km (-1.01 km). For optically thick and multilayered clouds, the biases of the estimated cloud heights from the cloud top or cloud base become larger (0.30/-1.71 km, 1.41/-4.64 km). The vertically resolved boundaries for ice clouds can contribute new information for data assimilation efforts for weather prediction and radiation budget studies. Our method is applicable to measurements provided by most geostationary weather satellites including the GK-2A advanced multichannel infrared imager.
机译:基于卫星 - 成像仪的操作云属性检索通常假设可以将多云像素视为与水平均匀性质平行的平面平行。这种假设可以导致云高度的高不确定性,特别是对于由冰颗粒组成的光学薄而是几何厚的云。本研究表明,冰云发射率不确定性可用于提供合理范围的冰云层边界,即最小高度。这里获得冰云发射率不确定性,以11,12和13.3μm为中心的三个红外频道获得。云发射率的范围用于推断一系列冰云温度和高度,而不是由操作云检索提供的每像素的单个值。我们在2015年8月期间使用Modis观测测试了我们的方法。我们估计三个云制度的最小最大高度,即单层光学薄冰云,单层光学厚冰云和多层云。我们的结果是通过与Caliop 4云产品的比较进行评估,总共11873个像素。单层光学薄云的云边界高度与来自卡利普的人表现出良好的一致;最大(最小)高度的偏差与卡利普的云顶(基地)高度为0.13公里(-1.01 km)。对于光学厚和多层云,云顶部或云底座的估计云高度的偏差变大(0.30 / -1.71km,1.41 / -4.64 km)。冰云的垂直解析边界可以为天气预报和辐射预算研究的数据同化努力提供新的信息。我们的方法适用于大多数地静止天气卫星提供的测量,包括GK-2A高级多通道红外成像器。

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