首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >A framework based on 2-D Taylor expansion for quantifying the impacts of subpixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bispectral method
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A framework based on 2-D Taylor expansion for quantifying the impacts of subpixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bispectral method

机译:基于二维泰勒展开的框架,用于基于双光谱方法量化子像素反射方差和协方差对云光学厚度和有效半径检索的影响

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摘要

The bispectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (r_e) simultaneously from a pair of cloud reflectance observations, one in a visible or near-infrared (VIS/NIR) band and the other in a shortwave infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring subpixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and r_e. In the literature, the retrievals of τ and r_e are often assumed to be independent and considered separately when investigating the impact of subpixel cloud reflectance variations on the bispectral method. As a result, the impact on τ is contributed only by the subpixel variation of VIS/NIR band reflectance and the impact on r_e only by the subpixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of subpixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and r_e retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how subpixel cloud reflectance variations impact the τ and r_e retrievals based on the bispectral method. In particular, our framework provides a mathematical explanation of how the subpixel variation in VIS/NIR band influences the r_e retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in r_e retrievals, leading to a potential contribution of positive bias to the re retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from Moderate Resolution Imaging Spectroradiometer. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used to estimate the retrieval uncertainty from subpixel reflectance variations in operational satellite cloud products and to help understand the differences in τ and r_e retrievals between two instruments.
机译:双光谱方法同时从一对云反射率观测值中检索云的光学厚度(τ)和云滴有效半径(r_e),一个在可见或近红外(VIS / NIR)波段,另一个在短波红外(SWIR)中)乐队。通常假定在检索中浑浊像素在水平方向上是均匀的。忽略云反射率的亚像素变化会导致检索到的τ和r_e出现明显偏差。在文献中,当研究子像素云反射率变化对双光谱方法的影响时,通常假定τ和r_e的取回是独立的,并分别考虑。结果,对τ的影响仅由VIS / NIR频带反射率的子像素变化贡献,而对r_e的影响仅由SWIR频带反射率的子像素变化贡献。在我们的新框架中,我们使用二变量函数的泰勒展开来理解和量化VIS / NIR和SWIR云反射率的子像素方差及其对τ和r_e检索的协方差的影响。该框架考虑了以下事实:取回是由VIS / NIR和SWIR波段观测以相互依赖的方式确定的。与以前的研究相比,它基于双光谱方法对子像素云反射率变化如何影响τ和r_e检索提供了更全面的了解。特别是,我们的框架提供了关于VIS / NIR波段中的子像素变化如何影响r_e检索的数学解释,以及为什么它有时会超过SWIR波段中的变化影响并主导r_e检索中的误差,从而导致潜在的贡献对检索的积极偏见。我们使用来自大涡流模拟的合成云场和中分辨率成像光谱仪的实际观测值来测试我们的框架。基于我们框架的预测结果与数值模拟非常吻合。我们的框架可用于估算可操作卫星云产品中亚像素反射率变化带来的检索不确定性,并有助于了解两种仪器之间τ和r_e检索的差异。

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