A synthetic data set of high-spectral-resolution infrared spectra for the Arctic atmosphere
A synthetic data set of high-spectral-resolution infrared spectra for the Arctic atmosphere
复制标题
北极大气高光谱分辨率红外光谱的合成数据集
DOI：
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发表时间：
2016
期刊：
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通讯作者：
V. Walden
中科院分区：
文献类型：
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作者：
C. Cox;P. Rowe;S. Neshyba;V. Walden
摘要。云的微物理和宏观物理特性对于理解云在气候中的作用至关重要。这些特性通常是从地基和卫星红外遥感仪器中获取的。然而，如果没有比较标准，检索不确定度很难量化。在极地地区尤其如此，那里基于云气候学的地面数据很少，但云是天气和气候模式中不确定性的主要来源。我们描述了一个合成的高光谱分辨率红外数据集，该数据集旨在促进地面和卫星遥感仪器云检索算法的验证和开发。由于数据集是使用预定义的多云大气计算的，因此云的性质和大气状态是先验已知的。用于模拟的大气状态是从位于阿拉斯加巴罗（北纬71.325° ，西经156.615° ）的阿拉斯加北坡（NSA）大气辐射测量（ARM）站点的无线电探空仪测量得出的，该位置通常代表北极西部。每个模拟的云属性都是从过去现场测量得出的统计分布中选择的。利用逐行辐射传输模型（LBLRTM）和离散纵坐标法辐射传输代码（DISORT），模拟了260个阴天情况下50至3000 cm−1（3.3至200 µm）的上升流（60 km）和下升流（地表）红外光谱，分辨率为单色（逐行），间距为~ 0.01 cm−1。感兴趣的研究人员可以从NSF北极数据中心数据存储库（doi:10.5065/D61J97TT）免费获得这些光谱。
Abstract. Cloud microphysical and macrophysical properties are critical for understanding the role of clouds in climate. These properties are commonly retrieved from ground-based and satellite-based infrared remote sensing instruments. However, retrieval uncertainties are difficult to quantify without a standard for comparison. This is particularly true over the polar regions, where surface-based data for a cloud climatology are sparse, yet clouds represent a major source of uncertainty in weather and climate models. We describe a synthetic high-spectral-resolution infrared data set that is designed to facilitate validation and development of cloud retrieval algorithms for surface- and satellite-based remote sensing instruments. Since the data set is calculated using pre-defined cloudy atmospheres, the properties of the cloud and atmospheric state are known a priori. The atmospheric state used for the simulations is drawn from radiosonde measurements made at the North Slope of Alaska (NSA) Atmospheric Radiation Measurement (ARM) site at Barrow, Alaska (71.325° N, 156.615° W), a location that is generally representative of the western Arctic. The cloud properties for each simulation are selected from statistical distributions derived from past field measurements. Upwelling (at 60 km) and downwelling (at the surface) infrared spectra are simulated for 260 cloudy cases from 50 to 3000 cm−1 (3.3 to 200 µm) at monochromatic (line-by-line) resolution at a spacing of ∼ 0.01 cm−1 using the Line-by-line Radiative Transfer Model (LBLRTM) and the discrete-ordinate-method radiative transfer code (DISORT). These spectra are freely available for interested researchers from the NSF Arctic Data Center data repository ( doi:10.5065/D61J97TT ).